Hype Cycle for Security Operations, 2026
5 June 2026 - ID G00846365 - 116 min read
By Darren Livingstone, Jonathan Nunez
Security operations technologies and services enable the operational defense of organizations’ digital assets by helping identify, validate and manage threats and exposures. This Hype Cycle helps cybersecurity leaders strategize and select security operations capabilities and functions.
Analysis
What You Need to Know
Cybersecurity leaders face an overwhelming volume of vendor and media noise and an increasingly complex threat landscape, accelerated by the application of AI. This year’s Hype Cycle reveals an exceptionally fast-moving industry defined by massive structural corrections and a significant influx of innovations. Rather than a period of stable evolution, these innovations represent an industry aggressively correcting course.
Driven by an urgent need to abandon unscalable legacy architectures and shift from reactive models to proactive, continuous validation approaches, we are seeing sweeping structural shifts that can be categorized into three key themes: threat detection, investigation and response (TDIR) architectures being challenged; continuous threat exposure management (CTEM) continuing to be a growing priority for teams; and the evolution of threat intelligence.
To navigate these big changes, organizations must adopt a fundamentally new strategy. This means rigorously piloting emerging capabilities to separate hype from operational reality, modernizing legacy architectures with scalable platforms and prioritizing continuous adversarial validation. Crucially, cybersecurity leaders must recognize that no technology on the Hype Cycle can independently close remediation chokepoints. They must use this market shift as a catalyst to renegotiate workflows and establish shared accountability with the teams responsible for executing fixes, ensuring that every investment delivers measurable, objective-aligned resilience.
The Hype Cycle
This year’s security operations Hype Cycle sees massive shifts across three core areas:
- Traditional TDIR-based offerings are being challenged by newer, less complex solutions.
- Vulnerability management continues to evolve into CTEM.
- Threat Intelligence has undergone a transformation.
TDIR Architectures Are Being Challenged
The traditional SIEM market is actively being redefined and splitting as evolving buyer demands for TDIR drive migration toward competing alternatives. Newer solutions, such as security data lakes (SDL) and integrated security operations center (ISOC) systems, offer lower operational complexity, as well as more cost and data flexibility. This ongoing evolution is underscored by the shifting role of extended detection and response (XDR). As large security players increasingly co-opt and integrate XDR as a feature layer within broader platforms, previously hyped stand-alone variations are officially being rendered obsolete.
Expectations for artificial intelligence are rapidly pivoting from passive assistance to unproven, yet limited, autonomous capabilities. The scalability of conventional SIEM architecture is being drawn into question, with legacy ingest models causing organizations to either ingest too much, thus increasing their overall spend, or not ingest enough due to fear of rising costs. Consequently, we may see drastic changes to traditional SIEM licensing models in the coming year to keep pace with the innovation of newer solutions. SDLs are offering a much more cost-effective, flexible approach to the storage and retention of data, and integrated ISOC systems are offering a less complex, more out-of-the-box-ready solution for teams requiring simpler operations and quicker time to value.
Evolution of Vulnerability Management and Proactive Security
Threat exposure management (TEM) continues to move beyond point-in-time discovery toward continuous, threat-led validation. This is evidenced by an influx of new, cloud-delivered “as a service” entrants, including red teaming as a service (RTaaS), bug bounty as a service (BBaaS) and cyber ranges. While the concepts of red teaming, bug bounty and cyber ranges are not new, the shift to cloud delivery has effectively led to wider customer adoption, enabling teams to better operationalize the validation portion of their CTEM efforts.
In addition to this, the emergence of AI-enhanced vulnerability discovery, demonstrated by innovations such as Claude Mythos,1 has the potential to significantly reduce the time-to-exploit window for zero-day threats. This heightened risk profile is driving increased urgency across security operations centers, necessitating an accelerated commitment to proactive security disciplines to maintain organizational resilience and to enabling preventative mitigations through patching and configuration changes. Organizations that focus on scaling their core security fundamentals, such as IAM hygiene or network segmentation, will see more success when adopting newer services such as RTaaS or BBaaS.
Threat Intelligence Makeover
Threat Intelligence has undergone a significant evolution as organizations realize that relying on narrow, single-source threat feeds from disparate providers creates persistent blind spots. To combat the complex threat landscape, buyers are moving away from legacy models that simply track raw indicators of compromise, instead demanding deep curation, contextualization and automated actionability. To achieve this, organizations are relying on mature cyberthreat intelligence data and analytics to understand adversary motives and behaviors. To effectively operationalize this influx of data, they are turning to newly profiled cyberthreat intelligence management systems (CTIMS) to serve as dedicated investigation workbenches. Instead of just pushing rule updates, CTIMS centralizes threat data collection, allowing teams to track adversary campaigns, manage intelligence requirements and build a comprehensive understanding of attacker behaviors.
However, simply managing threat data is insufficient if it lacks the business context needed to prioritize remediation. Because narrow, indicator-centric threat intelligence produces blind spots, organizations must correlate diverse signals to make reliable decisions. Unified cyber risk intelligence (UCRI) addresses this by fusing internal telemetry with external threat signals into specialized analytical engines. This allows organizations to map their specific exposures to adversary intent, ensuring that teams invest their time and effort into mitigating the highest-risk pathways rather than chasing isolated, low-impact indicators.
![Hype Cycle for Security Operations, 2026 plots 31 innovations from the Innovation Trigger through the Plateau of Productivity] Innovations range from autonomous exposure remediation to AI SOC agents to endpoint detection and response.](/resources/846300/846365/Figure_1_Hype_Cycle_for_Security_Operations_2026.png)
The Priority Matrix
The Priority Matrix serves as a strategic compass, helping leaders navigate a fast-moving industry by clearly defining which initiatives to implement immediately and which to plan for in the future. To maximize immediate risk reduction, organizations should first deploy high-benefit capabilities maturing in the near term. These tactical solutions address current operational bottlenecks and secure expanding attack surfaces with a much faster time to value. Conversely, leaders must also balance these immediate wins by allocating resources toward transformational, long-term shifts. While these broader architectural changes will take five to more than 10 years to fully mature, planning for them now is important to optimizing existing processes and building unified, proactive defense platforms.
Organizations that evaluate, document, communicate and prioritize their business risks prior to investing in security operations services and capabilities are best-positioned to allocate resources effectively and maximize risk reduction. In an industry rampant with hype and change, avoiding the temptation to jump on the latest technological trends is critical. Cybersecurity leaders must be highly cautious of “GenAI washing” and unproven autonomous capabilities, ensuring that emerging solutions are rigorously piloted and integrated into well-defined processes rather than adopted simply for their novelty.
When developing a technology roadmap, the primary objective must be ensuring new solutions align with established security processes (see How to Build a Strong Foundation for Your Security Operations Metrics). Technologies rarely provide immediate benefits if they are not properly operationalized; therefore, adding complexity through disjointed point solutions is neither of high priority nor high benefit. Instead, cybersecurity leaders should focus on long-term initiatives that optimize existing processes and leverage modular and extensible security platforms to deliver measurable improvements to the organization’s risk profile.
Ultimately, technologies and services must be evaluated strictly on their ability to deliver actionable, measurable outcomes, and ideally they will have no overlapping features. Recognizing that no single capability is the perfect fit for every organization, cybersecurity leaders must prioritize investments that solve their unique operational bottlenecks and align with their unique attack surfaces.
Priority Matrix for Security Operations, 2026
| Benefit | Years to Mainstream Adoption | |||
|---|---|---|---|---|
| Less Than 2 Years | 2 to 5 Years | 5 to 10 Years | More Than 10 Years | |
Transformational | ||||
High | ||||
Moderate | ||||
Low | ||||
Source: Gartner (June 2026)
Off the Hype Cycle
Observability pipelines (previously tracked as telemetry pipelines) have been officially removed from the 2026 Hype Cycle for Security Operations. While these solutions remain highly valuable for collecting, enriching and routing massive volumes of telemetry data, their primary use cases and overall trajectory align much closer to broader IT monitoring and observability disciplines rather than strictly security operations. Furthermore, security-specific products focusing on this capability have seen increased acquisition activity by larger, more established cybersecurity vendors as part of a broader suite of tools, meaning further tracking is not warranted. Observability pipelines will continue to be tracked in the Hype Cycle for Monitoring and Observability, 2026.
On the Rise
Autonomous Exposure Remediation
Analysis By: Jeremy D'Hoinne, Dhivya Poole, Mitchell Schneider, Charanpal Bhogal
Benefit Rating: Transformational
Market Penetration: Less than 1% of target audience
Maturity: Embryonic
Definition:
Autonomous exposure remediation (AER) is an emerging discipline that aims to leverage generative AI techniques to support semi or fully autonomous identification of vulnerabilities in code, vulnerable software supply chain components and exposures in infrastructure. AER suggests and deploys fixes automatically, then integrates with infrastructure as code technologies to automate deployment, update vulnerable elements and roll back if necessary.
Why This Is Important
IT is changing faster than cybersecurity. Organizations cannot keep up with agentic-driven change in apps and infrastructure using manual fixes and actions. Agentic development is not only automating code creation but also changing the level of control organizations have on the applications they create. Infrastructure as code enables further automation of the application and infrastructure deployment.
Business Impact
Cybersecurity leaders hoping to keep pace with the agentic transformation of IT need to close the automation gap by integrating autonomous exposure remediation across code creation, application deployment, software and infrastructure updates to minimize their enterprise’s exposure window.
Drivers
- Agentic AI coding tools force a reset of application security practices, as point-in-time scanning cannot keep pace with continuous code generation.
- Enthusiasm about AI agent capabilities supports innovative initiatives and cross-team collaboration for creating “AI-native” processes. This inspires cybersecurity teams who are integrating automation directly in the agentic development pipeline through the creation of dedicated subagents.
- Recent announcements from Anthropic and OpenAI on improved large language model (LLM)-driven vulnerability scanning and the emergence of LLM-driven penetration testing startups open new technological possibilities for application security teams.
- Larger organizations are combining commercial tools with private LLMs to create semi or fully autonomous loops that include code scanning, vulnerability identification, exploit and fix creation.
- Forward-looking infrastructure teams experiment with the automation of software deployments by leveraging infrastructure as code. This opens new possibilities for end-to-end AER workflows.
- Automated exposure assessment for infrastructure assets is also making progress with technologies such as exposure assessment platforms and automated security configuration assessment, but automated remediation is more complex and still waits for a big leap.
- These improvements in automation in application development, infrastructure deployment and cybersecurity provide foundational building blocks to create entire AER workflows.
- Cybersecurity leaders set AER as a long-term objective in their ambitious multiyear roadmap to deliver an integrated secure agentic workflow. This workflow embeds cybersecurity at the time of development and reduces the exposing windows to the minimum for all assets of the organization.
Obstacles
- Technologies supporting AER are fragmented and mostly limited to custom code and web applications.
- End-to-end AER isn’t yet reliable or scalable for unmonitored production deployment.
- AER needs developer acceptance, which will improve if AI agents generate most of the code and require developers to own the process and the cybersecurity team to define the AER policies.
- Automating updated applications’ deployment is the most difficult part of AER workflows. Existing technologies can’t update critical infrastructure elements automatically. It requires comprehensive testing and simulations, high-availability infrastructure and automated rollback elements.
- Automation is accelerating but partial, focused on vulnerability discovery. This degrades cybersecurity instead of improving it, inflating application teams’ queue of fixes with limited resources.
- Extensive LLM-driven analysis, fix suggestion and deployment automation may inflate the cost of cybersecurity for application security projects.
User Recommendations
- Acknowledge the low maturity of AER supporting technology and communicate on reasonable multiyear roadmaps, rather than promising that buying a tool today will immediately improve mean time to remediate.
- Monitor the progress of AER technologies. Expect short-term disillusion with a high rate of false positives and low quality for fixes.
- Aim at aligning cybersecurity automation to the pace of application development by evaluating how to integrate vulnerability detection and fix suggestions in agentic development loops.
- Be sure to benchmark LLM-driven vulnerability assessments and fix suggestions against existing practices and tools. Don’t assume they will provide better results and lower false positives at this stage.
- Be careful about creating a remediation chokepoint by automating the discovery of vulnerabilities without updating prioritization and remediation practices.
- Engage in cost analysis early on to ensure cybersecurity is included in each project token allocation.
Gartner Recommended Reading
Unified Cyber Risk Intelligence
Analysis By: Jonathan Nunez
Benefit Rating: Transformational
Market Penetration: Less than 1% of target audience
Maturity: Embryonic
Definition:
Unified cyber risk intelligence (UCRI) is the fusion of all relevant threat signals across diverse internal (telemetry, logs) and external sources into specialized analytical engines (machine learning, predictive modeling). UCRI enables faster, more accurate detection of emerging and covert attack patterns, equipping organizations to proactively mitigate cybersecurity risk across all business functions.
Why This Is Important
Organizations can no longer rely on narrow or single‑source threat data; doing so leaves persistent blind spots across the attack life cycle. UCRI strengthens risk-based decisions by correlating diverse signals, enabling faster, more accurate threat validation and preparing security teams for AI‑driven, multisignal future operations.
Business Impact
- Elevates enterprise decision‑making by providing a highly corroborated, multi‑signal foundation that replaces fragmented insights.
- Exposes hidden adversary activity by fusing telemetry, exposure data and external threat signals to uncover subtle relationships and early‑stage attack patterns.
- Optimizes existing security investments by mapping organizational exposures to adversary intent, ensuring detection rules, mitigations, and hardening efforts concentrate on the highest‑risk pathways.
Drivers
- Multisignal intelligence demand: Organizations recognize that narrow indicator‑centric threat intelligence produces blind spots; expanding to diverse signals (telemetry, logs, external threat sources) creates the corroborated intelligence needed for reliable decisions.
- Rising complexity of threats: Adversaries employ multi‑step, multi‑vector tradecraft that requires analytical fusion of disparate signals to detect subtle, coordinated behavior.
- Shift toward proactive defense: UCRI enables early detection of emerging patterns, lateral‑movement paths, and subtle precursors that reactive threat intelligence (TI) misses.
- AI‑driven analytical advancements: Machine learning, predictive modeling, natural language processing (NLP) and other AI techniques enable organizations to correlate dispersed signals at scale, accelerating the move toward preemptive, risk‑aligned intelligence.
- Enterprise integration requirements: Security leaders need intelligence that spans business functions (risk, compliance, executive decision‑making), pushing demand for unified architectures that deliver contextualized, mission‑aligned insight.
Obstacles
- Signal disparity and data fragmentation: Integrating diverse internal and external data streams requires significant normalization work; without it, intelligence loses coherence and reliability.
- Implementation complexity of UCRI: Multisignal architectures demand sustained engineering, integration, and governance structures, creating operational hurdles for organizations without mature infrastructure.
- High analytical skill requirements: Effective fusion and interpretation of fused intelligence data requires expertise many security teams currently lack, limiting the speed of UCRI adoption.
- AI model oversight and assurance challenges: Advanced AI‑assisted analytics require robust validation and continuous tuning to maintain accuracy and avoid misinterpretation or overconfidence.
User Recommendations
- Expand intelligence inputs deliberately: Add new data sources through a structured process so correlations strengthen, investigative gaps close, and decision‑makers gain clearer insight into emerging and covert attack patterns.
- Prioritize contextualization over volume: Emphasize intelligence that links signals to risk, exposure, and business relevance rather than raw indicators or isolated alerts.
- Implement unified analytical workflows: Centralize signal aggregation, enrichment, and interpretation to build a coherent intelligence picture and ensure consistent decision support across relevant teams.
- Invest in AI capabilities: Upskill teams to leverage AI‑enabled summarization, pattern detection, and predictive modeling without losing critical domain expertise.
- Integrate intelligence into decision‑making structures: Ensure outputs inform risk committees, exposure management cycles, threat modeling, and executive strategies to maximize enterprise value.
Gartner Recommended Reading
Cybersecurity Mesh Architecture
Analysis By: Patrick Hevesi
Benefit Rating: Transformational
Market Penetration: Less than 1% of target audience
Maturity: Embryonic
Definition:
Cybersecurity mesh architecture (CSMA) is an approach for architecting composable, distributed security controls that share data and security insights. It enables secure, centralized security operations and oversight by supporting independent and composable security monitoring, predictive analytics, proactive enforcement, centralized intelligence and governance, and a common identity fabric.
Why This Is Important
CSMA is an evolution of current defense-in-depth strategies. Unlike poorly interconnected point solutions, CSMA integrates and normalizes data from multiple sources for greater accuracy and context. This foundation improves centralized security posture and exposure management, threat awareness, infrastructure integration, coordinated detection, harmonized reporting, proactive response, cross-tool collaboration, and attack predictability and prevention.
Business Impact
CSMA aims to address the growing complexity of managing security tools, intelligence and identity solutions. Many organizations are evolving toward a more flexible security architecture to mitigate the impact of rapidly changing attack types and reduce operational overhead created by the proliferation and churn of security tools. Investing in composable, interoperable and extensible security toolsets is essential to lower cost and increase consistency.
Drivers
- Organizations continue to be breached and increasingly require a more accurate view of the likelihood and impact of a threat or exposure to a threat factor. This level of detail is crucial for making better pro-business security decisions and shifting operations into a more real-time cyber response.
- Cybersecurity teams can be overwhelmed as they try to stay ahead of new, complex attacks and deploy the latest security tools across expanding infrastructure. Many teams lack the analytical capabilities and AI‑driven features needed to be proactive and dynamic in their enforcement and response decisions, and these decisions are often not fast enough to meet business needs.
- Organizations are looking to approaches such as CSMA to better integrate and interpret siloed security outputs in closer to real time, as many tools operate with limited awareness of others. Effective security and identity management requires a layered and integrated architecture.
- Organizations are frustrated by the lack of integration and consistent visibility within their current security workbenches. Security and risk management leaders need an architecture that not only responds to current issues but also delivers a coordinated, holistic approach to complex security challenges.
- Creating a collaborative ecosystem of security tools will reduce inconsistency and help minimize exposure in alignment with business expectations.
Obstacles
- As vendors continue to support CSMA principles in their products, vendor lock‑in will likely remain a concern. If a proprietary approach is employed, it may block rather than enable cross‑tool integration, leading to coverage gaps and increased costs driven by inflexibility.
- Organizations that choose to build their own CSMA platform will likely require significant engineering effort to integrate disparate products before standards mature. They may also face setbacks if the industry later converges on interoperability standards after substantial custom integration work has been completed.
- CSMA 3.1 continues to evolve as consumer IT advances and security technologies consolidate, making it difficult to plan for the level of flexibility needed to manage ongoing change.
- Organizations recognize the skills gaps and the volume of work involved but lack clear solutions to address these challenges.
User Recommendations
- Add purchasing requirements that prioritize integration and interoperability across multivendor tools aligned with CSMA principles.
- Choose a primary security analytics and intelligence layer (SAIL) platform that supports most of your tooling and integrate remaining layers into it.
- Mature your security infrastructure by selecting vendors that follow the CSMA reference architecture and adopt standards such as the Open Cybersecurity Schema Framework (OCSF).
- Evolve your identity infrastructure into an identity fabric by eliminating silos and enabling dynamic, real‑time identity capabilities that incorporate broader context and risk signals such as device proximity, posture, biometrics and location.
- Improve responsiveness by centralizing policy, posture and playbook management and creating an integrated single starting pane of glass for audiences such as the SOC, stakeholders and risk partners.
Gartner Recommended Reading
Detection Engineering Automation Solutions
Analysis By: Alex Tytarenko
Benefit Rating: Moderate
Market Penetration: 5% to 20% of target audience
Maturity: Emerging
Definition:
Detection engineering automation solutions (DEAS) are products and services that facilitate developing, testing, deploying and improving threat detection content. DEAS support version-controlled repositories, documentation, detection-as-code, peer reviews, validation, detection posture management and more. DEAS uses AI to lower barriers for detection engineering adoption. Organizations use DEAS to streamline consumption of threat detection content and collaborate with content providers.
Why This Is Important
Detection engineering (DE) practice is evolving from ad hoc analyst tasks to a key SecOps function, but adoption is slowed by reliance on in-house scripting and open source tools instead of integrated end-to-end DE suites. DEAS delivers automation, structure, and knowledge management; lowers expertise barriers; and eases collaboration. As demand matures, rapid innovation in AI-enabled DEAS offerings will continue.
Business Impact
- Strategic alignment: Detection priorities are aligned with business risk and threats, maximizing technology ROI by optimizing limited resources.
- Robust detections: DEAS facilitate “antibrittle” and relevant detections that withstand changes in attacker tactics and technology stacks.
- Efficiency and retention: Reduction of alert fatigue and analyst burnout fosters expertise and improves team retention.
- Cost optimization: SIEM data ingestion costs are optimized via informed, transparent decisions.
Drivers
- Mandate for proactive security and rapid iteration: The shift from a reactive security posture to a proactive, threat-informed approach is a key driver. This mandates short, agile cycles for the detection content life cycle, enabling rapid transitions from threat intelligence and exposure data to detection. Organizations need continuous, automated testing and quality assurance to ensure that detection capabilities are “antibrittle” and remain effective against evolving threats — a necessity that DEAS tooling is designed to facilitate.
- Mitigating expertise and skills gap challenges: Effective DE is an inherently multidisciplinary function, requiring expertise in threat intelligence, threat detection investigation and response (TDIR) tools, data engineering, and software development practices. This diverse skill set is rare and costly, creating a major barrier to DE adoption. DEAS lowers this expertise barrier by embedding these best practices and automation into a dedicated AI-augmented tool, making sophisticated DE workflows accessible to existing security teams.
- Need for automation and AI augmentation: DE activities are labor-intensive, often performed by understaffed teams. This drives the urgent need for automation and AI augmentation to handle high-volume, mundane tasks. DEAS addresses this by integrating AI and automation for use cases such as query language translation, data schema validation, automated testing, documentation generation and coverage mapping to security frameworks, freeing up expert analysts for more impactful strategic tasks.
- Operationalizing custom and open-source solutions: Organizations currently use a mix of custom scripting, SIEM/SOAR and point solutions, all of which are complex to build and maintain. Since out-of-the-box TDIR tools don’t cover unique organizational threats, content requires tailoring. DEAS is vital for overcoming this complexity, offering the structure and framework to evolve ad hoc custom solutions into a scalable, enterprise-ready DE practice.
Obstacles
- Many organizations acknowledge the strategic value of a dedicated DE function but have only made superficial changes, like updating job titles, without significantly maturing detection content practices.
- While DEAS capabilities appear on many vendors’ product roadmaps, they are currently available as bundled components within broader security solutions that often offer only limited DE functionality. This restricts adoption for organizations with established security stacks.
- Organizations may find native SIEM/TDIR detection content management sufficient, making them reluctant to invest in specialized DE solutions — not realizing that this can limit the maturity of DE practice.
- Organizations using external threat detection content or a managed SOC shift their DE focus to oversight, alignment and quality control instead of content development. Consequently, they have less reason to invest in a specialized DE product.
Analyst Note: Most DEAS capabilities are not yet available as dedicated, stand-alone products; instead, they are delivered as embedded modules within broader SecOps offerings:
- SOC Prime and Spectrum offer stand-alone/pure-play DEAS capabilities.
- Anvilogic, AttackIQ, Cardinal Ops and Fig Security offer capabilities that can function as a portable DEAS overlay for existing SIEM stacks.
- Hunters.ai, Matano, Mate Security, Panther, ReliaQuest and Sekoia.io have vendor-specific DEAS capabilities coupled with their native SOC offerings.
User Recommendations
- Prioritize the establishment of a formal DE practice, including a robust and systematic process for developing threat detection content, before investing in specialized tools.
- Verify whether a DEAS solution incorporates detection-as-code functionality and identify the specific detection language provided. This language may be vendor-agnostic, such as Sigma; a general-purpose programming language like Python; or a proprietary query language, such as SPL, KQL or EQL.
- Evaluate the DEAS features and functions that may already be present within your existing TDIR stack. Determine whether these can facilitate the end-to-end detection engineering life cycle.
- Examine the degree of automation and AI augmentation available for routine and high-volume tasks. These capabilities are essential for reducing entry barriers to the DE practice and enabling the team to concentrate on the core detection logic.
Gartner Recommended Reading
Security Data Lakes
Analysis By: Eric Ahlm
Benefit Rating: Moderate
Market Penetration: 5% to 20% of target audience
Maturity: Adolescent
Definition:
Security data lakes (SDLs) are an alternative to traditional security information and event management (SIEM) that aids security teams in threat detection, investigation, and response (TDIR) operations. A key advantage is the highly extensible data architecture that allows users to better control data usage as it impacts cost. Unlike general log and analysis solutions, SDL solutions must support TDIR operations with a reasonable amount of similarity to a SIEM solution.
Why This Is Important
Data management of telemetry used for security operations teams to perform TDIR has become a criterion of utmost importance for SIEM buyers. SDL solutions offer an alternative to SIEM platforms as a tool to be used at the center of security operations centers for performing TDIR where custom data analysis is a priority.
Business Impact
SDL solutions can impact business by:
- Helping reduce the cost of classic SIEM solutions by offering more options for security telemetry pipeline management, data ingestion methods, and data storage options, such as high compression.
- Extending extensibility for creating detection use cases though enhanced analytics and/or analyzing a larger security dataset.
- Providing flexible architectures that allow for a wide range of deployment models to support current and future needs for security data analysis.
Drivers
- The limitations of many traditional SIEM solutions are increasingly apparent in their data management capabilities, which struggle to handle the growing volume, diversity, and disparity of data without compromising security detections and investigations.
- A primary driver for clients seeking alternatives to existing SIEM solutions, as repeatedly highlighted in Gartner inquiry calls, is the high cost associated with massive data ingestion volumes and long-term data retention needs. Security data lake (SDL) solutions address this concern by providing enhanced data management methods and more-affordable storage options that enable customers to better control cost related to data ingestion and utilization.
- A key advantage of many SDL solutions is the capability to consolidate varied monitoring functions onto one unified platform by acting as a centralized log management solution as well.
Obstacles
- SDL solutions often lack the feature maturity of traditional SIEM systems in terms of advanced log correlation and machine learning for security use cases. Organizations must weigh the advantages of an SDL against the sacrifice of certain SIEM capabilities.
- SDL solutions offer the most value for clients who process large data volumes for TDIR. Conversely, clients with lower daily ingest rates on their traditional SIEM may not experience substantial cost control benefits from implementing an SDL.
- SDL solutions have less out-of-the-box usability and vendor-supplied security content as compared with a traditional SIEM. Users of SDL must be prepared for the development efforts involved as well as changes in operational functions required to use an SDL for their primary TDIR operations.
- Compliance and regulatory mandates specifically tailored for or traditionally addressed by SIEM solutions may not be inherently satisfied by SDL.
User Recommendations
- In security environments with high security data utilization, examine SDL solutions as an alternative to better manage the cost due to data ingestion and retention associated with most SIEM solutions.
- Plan for changes in operations when replacing SIEM solutions with SDL products. Some SDL products have limited features for building advanced queries, correlation rules, and custom dashboards. This may impact how your team performs TDIR actions and the staffing required.
- Prioritize SDL evaluations if your organization has the desire to consolidate telemetry analysis for cross disciplines such as security and observability.
- Evaluate the possible benefits an SDL solution can bring to your security operations practice by increasing the total amount of telemetry available for analysis. This could lead to an increased scope of coverage or improved detection through the analytics of broader data types and volumes.
Sample Vendors
Anvilogic; Cribl; Databricks; Datadog; Devo Technology; Hunters; Hydrolix; Panther; Securonix
Cybersecurity Incident Response Management
Analysis By: Eric Ahlm, Carlos De Sola Caraballo
Benefit Rating: Moderate
Market Penetration: 1% to 5% of target audience
Maturity: Emerging
Definition:
Cybersecurity incident response management (CIRM) solutions provide cyber incident response teams (CIRTs) with the capabilities required to manage the workflow, activities, forensic preservation, communication and collaboration required for handling incidents in large-scale organizations. CIRM solutions help address modern incident response (IR) challenges using integrations and automation.
Why This Is Important
CIRM allows cyber incident responders to have their own case management and workflow capabilities that allow for better overall management, higher performance and tracking of incident resolution, and a more forensically secure system of record. This leads to greater continuity in handling, faster execution in response and the ability to collaborate with a wider range of cross-team members.
Business Impact
CIRM solutions can help CIRTs:
- Achieve better cyber incident response management capabilities than those offered by basic ticketing or ITSM systems.
- Meet the demands of stakeholders and executives to be more involved in incident response management.
- Better track, report and optimize the overall incident response performance metrics and regulatory reporting for cyber incident handling.
- Reallocate supportive IR tasks (e.g., incident notifications, status updates, evidence documentation), allowing IR teams to concentrate on critical incident response actions and to reduce the response time.
Drivers
- Cyber incidents are increasing in both volume and complexity for large-scale organizations. The financial losses due to incidents are often related to incident handling from secondary teams, such as legal.
- Regulatory standards are requiring more noncyber team members to be involved in incident handling, which drives the need for increased workflow management.
- Meeting shareholder concerns about top KPIs, such as mean time to respond (MTTR), requires centralized tracking and trending data about workflow execution for incident response.
- Incidents are spanning multiple organizations in supply chain attacks, which requires close cooperation across company boundaries.
Obstacles
- CIRM solutions require a degree of client maturity in security operations, and are best-suited to support an established CIRT team.
- Many ITSM systems offer basic incident handling capabilities or cyber-incident-specific modules for increased functionality. However, these often come at a premium cost point.
- Shareholder interest in improving the overall incident response performance may limit some clients from seeking CIRM solutions.
- Security operations leaders may continue to use ITSM systems, native TDIR (SIEM/SOAR, XDR) ticketing capabilities or manual methods before considering CIRM solutions.
User Recommendations
- Consider using CIRM solutions for the entire case management solution for handling cyber incidents, or only for uplifting specialized functions such as communication and collaboration from existing ticketing systems.
- Investigate CIRM solutions if your organization faces regulations that require it to notify regulators, markets or shareholders quickly about an incident.
- Use CIRM solutions in very large organizations with many cross-team members that find the cyber incident management difficult to execute. CIRM solutions will streamline the process and add efficiency by using automation capabilities.
Sample Vendors
BreachRX; Cydarm; CYGNVS; Cytactic; incident.io; Motorola Solutions; PagerDuty; ServiceNow; StrangeBee
Exposure Management Services
Analysis By: Mitchell Schneider
Benefit Rating: High
Market Penetration: 20% to 50% of target audience
Maturity: Adolescent
Definition:
Exposure management services are fully managed, tech‑enabled offerings that help organizations continuously identify, validate, and prioritize exposures across their environment. These services combine attack surface discovery, vulnerability insights, and business context, while also leveraging customer‑provided scanning data when available. Providers deliver assessments, validated exposure intelligence, and actionable remediation guidance to augment internal teams and improve mobilization.
Why This Is Important
Exposure management services provide organizations with continuous visibility into their evolving attack surface and help validate and prioritize exposures using business context. These services strengthen internal teams by closing mobilization gaps, improving remediation timeliness and driving end-to-end exposure management process improvement.
Business Impact
These services reduce the likelihood and impact of cyber incidents by enabling faster, more focused remediation/mitigation and providing validated insight into the most critical exposures. They also improve operational efficiency, strengthen executive reporting, and help organizations align security actions with business‑level risk reduction outcomes.
Drivers
- Organizations with limited resources often struggle to coordinate remediation due to unclear ownership, lack of expertise, or bandwidth. Services address these gaps with structured prioritization, owner identification, guidance, and hands-on help — progressing stalled issues, reducing backlog, and achieving remediation that would otherwise be unrealistic.
- Small or overstretched security teams may lack capacity to verify exploitability, confirm risk, or filter false positives. Exposure management services provide validated findings, contextual interpretation, and prioritized guidance — turning raw detection data into clear, actionable steps for security operations.
- As digital environments grow, limited staffing can hinder ingestion, normalization, and correlation needed for meaningful exposure insights. Exposure management services integrate cloud, identity, SaaS, configuration, and behavioral telemetry, delivering unified visibility and actionable intelligence without extra internal resources.
- Many organizations lack skills to evaluate attack paths or test controls. Exposure management services continuously validate exposure chains, identify control failures, and confirm where attackers could succeed — ensuring that tool-identified issues represent real risk and deserve prioritization.
- Small or inexperienced teams often can’t produce consistent, defensible executive reporting. Exposure management services offer analyst-driven narratives, interpretable scoring, exposure reduction metrics, and reporting that links technical issues to business impact — improving executive understanding and supporting investment decisions.
Obstacles
- Many organizations lack foundational vulnerability management maturity, limiting their ability to operationalize richer exposure insights.
- Disparate data sources and poor asset inventories hinder investigation, prioritization, and remediation.
- Validation capabilities (attack path, control effectiveness) vary significantly across service providers.
- Security teams often struggle to convert findings into action due to unclear ownership, process gaps, or insufficient staffing.
- Technology coverage may be inconsistent when clients supply their own scanning data, while provider‑supplied tools can create visibility gaps or integration challenges.
- Executive stakeholders may expect consistent quantification and clear ROI, creating pressure in environments with tight budgets and competing security priorities.
User Recommendations
- Prioritize providers that deliver continuous visibility, validated findings, and business‑contextual prioritization rather than static, report‑only services (for example, periodic PDF summaries, unvalidated vulnerability lists, or one‑time assessment outputs).
- Select services that integrate tightly with threat detection, investigation and response (TDIR) to improve detection quality, validate control effectiveness, and accelerate remediation workflows.
- Choose providers able to ingest and correlate diverse data sources over time, including identity, SaaS, user behavior, and operational risk inputs.
- Engage services that include an exposure validation and response team to help interpret findings, guide mobilization, and ensure that remediation owners understand what to do and why.
- Evaluate how effectively the service measures program outcomes, including exposure reduction trends, remediation timeliness, and business‑aligned risk reporting.
Sample Vendors
Arctic Wolf Networks; CyberProof; eSentire; Integrity360; LevelBlue; Obrela Security Industries; Outpost24; Pondurance; Rapid7; Reveald
Automated Security Control Assessment
Analysis By: Evgeny Mirolyubov
Benefit Rating: Moderate
Market Penetration: 5% to 20% of target audience
Maturity: Adolescent
Definition:
Automated security control assessment (ASCA) is a technology that continuously analyzes, prioritizes and optimizes cybersecurity controls to reduce threat exposure. ASCA identifies control coverage gaps, configuration drift from a baseline, policy deficiencies, detection logic gaps, weak defaults and other misconfigurations in deployed cybersecurity controls. It then recommends and assists in implementing prioritized remediation steps to improve posture.
Why This Is Important
Without optimal configuration, cybersecurity tools are likely to fail to log, detect and block security threats, resulting in a poor return on investment. The complexity caused by the proliferation of cybersecurity tools is further compounded by organizational silos, tool-centric responsibilities, skills gaps, high administrator turnover and an evolving threat landscape. As a result, no organization has the resources to manage cybersecurity tools effectively without the use of automation.
Business Impact
ASCA reduces an organization’s risk of business disruption and financial loss by optimizing technical cybersecurity controls and reducing exposure to threats. Organizations that implement ASCA technologies enhance staff efficiency, minimize the impact of human error, maximize the value of their cybersecurity investments and improve resilience amid organizational change.
Drivers
- Misconfiguration of cybersecurity controls remains a persistent issue linked to breaches.
- Organizations with multivendor cybersecurity portfolios need a simpler way to optimize configurations, rather than relying on individual dashboards, annual audits or custom automation.
- Manual configuration reviews against best practice settings and occasional penetration tests are insufficient due to the likely impact on user experience, limited scope and low frequency.
- The use of AI by attackers lowers the barrier to entry, increasing the scale and speed of attacks like phishing and putting greater pressure on cybersecurity to minimize control and configuration gaps.
- Meaningfully improving cybersecurity posture requires going beyond compliance-driven assessments and evaluations focused on assessing the sole presence of cybersecurity controls.
- Continuously assessing and optimizing cybersecurity controls against specific threats, rather than best practices, is an effective risk mitigation strategy that ultimately reduces threat exposure.
Obstacles
- ASCA tools do not validate hypotheses or control behavior during actual attacks. Therefore, cybersecurity teams must validate recommendations regarding the effective course of resolution and complement ASCA with offensive testing.
- Early stages of ASCA deployments generate a large volume of findings. Cybersecurity teams are already overwhelmed, and adding another source of findings often creates more hindrance than help.
- Fully automating the process of implementing improvements based on ASCA findings remains unrealistic in the near future due to the heightened risk of business disruption.
- ASCA technologies overlap with several other, more established product categories, as well as built-in self-assessment capabilities of individual controls and vendor services for product adoption.
- ASCA does not align with a dedicated budget and rarely replaces existing technologies. Additional spending is hard to justify when budgets must be reallocated to higher priorities such as securing AI.
User Recommendations
- Pursue ASCA to support your continuous threat exposure management (CTEM) program, starting with incumbent providers. Justify ASCA investments through improved staff efficiency, faster exposure mitigation, reduced incidents and maximized cybersecurity stack utilization.
- Choose a third-party ASCA technology provider based on its ability to close identified capability gaps and integrate with current and planned cybersecurity products. Prioritize bidirectional integration with controls for endpoints, identity and email security.
- Use ASCA to go beyond exposure discovery or high-level coverage assessments. ASCA enhances exposure management by providing control context for prioritization, accelerating mitigation and facilitating control optimization to improve the overall protection.
- Preapprove automated remediation actions for non-negotiable, high-risk findings with minimal productivity impact. For fixes with higher potential business disruption, balance semiautomated and manual remediation.
Sample Vendors
Breeze Security; CardinalOps; Check Point (Veriti); Discern Security; Nagomi Security; Reach Security; Reclaim Security; Tidal Cyber; Zafran
Gartner Recommended Reading
Adversarial Exposure Validation
Analysis By: Dhivya Poole, Jonathan Nunez, Mitchell Schneider
Benefit Rating: Moderate
Market Penetration: 5% to 20% of target audience
Maturity: Early mainstream
Definition:
Adversarial exposure validation (AEV) provides consistent, continuous and automated empirical evidence of the feasibility and impact of an attack. AEV actively validates how potential attack scenarios and techniques successfully exploit environments and circumvent security controls, offering actionable, closed-loop evidence of exploitability. Delivered primarily as a SaaS solution, with optional agents, AEV integrates with mobilization workflows to support CTEM programs.
Why This Is Important
Organizations struggle to conduct frequent, consistent offensive security testing due to requirements such as deeper expertise, coordinated planning and complex tooling, leaving critical gaps unaddressed. AEV automates these processes, optimizing defensive posture, prioritizing exposures empirically and scaling offensive capabilities, transitioning from sporadic, ad hoc testing to continuous validation.
Business Impact
AEV confirms a potential exposure to a specific threat by taking the attackers’ view. It evaluates the efficacy of attacks through deployed security controls and can highlight exploitable paths leading to an organization’s most critical assets. This helps security teams prioritize remediation or mitigation efforts and evaluate the value of their invested technologies. It complements exposure assessments and provides a way to continuously execute attack scenarios.
Drivers
- Filter for relevant remediation actions: AEV highlights only attack paths that successfully execute, allowing organizations to prioritize fixes based on demonstrated exploitability, rather than theoretical risk lists.
- Emerging threat and zero‑day exposure identification: By incorporating current threat intelligence and continuously validating environments against newly observed and emerging TTPs, AEV uncovers exposures linked to zero days and emerging threats often missed by traditional assessments.
- Red team augmentation: Human-led red-teaming programs are difficult to initiate, needing a specific set of expertise, processes and tools that can be expensive to develop or procure. The progress in automation, AI and expanding number of providers help kick off red-teaming programs by starting small and demonstrating benefits early.
- Attack surface reduction: Organizations with established exposure validation programs use AEV technology primarily to ensure a consistent, yet improved, security posture over time and across multiple locations.
- Exceeding compliance requirements: AEV supports and strengthens mandatory or threat-led assurance activities by executing real attack behaviors, validating exposures more deeply than the checklist-driven exercises.
- Defense optimization: AEV tools integrate with security control technologies to test configuration strength and attack response, uncovering defensive gaps and pointing to where further tuning or investment is needed.
- Support continuous threat exposure management (CTEM) program: AEV enables deeper automation of the “validation” step. Adding automation to the red team’s toolkit can also help initiate such a program.
- Empirical objective justification: AEV delivers nonrefutable, real-world evidence of security control effectiveness, enabling cybersecurity leaders to justify spending, demonstrate ROI and objectively evaluate internal teams and service providers with quantifiable, data-driven assessments.
Obstacles
- Many AEV providers often don’t support all use cases equally, requiring buyers to prioritize desired outcomes (e.g., SLAs for zero-day inclusion or continual threat use case creation) before vendor selection.
- Although AEV vendors provide simplification of testing with predeveloped attack scenarios, buyers must commit operational resources and often new team structures to successfully reach desired outcomes.
- The results from AEV solutions are not often accepted by auditors as a replacement for a third-party penetration test. This forces buyers to increase their testing budget to acquire AEV solutions.
User Recommendations
- Prioritize the most impactful exposure scenarios. Assess the vendors’ capabilities to deliver simulated attacks as an easier way to convey the benefits of supporting an exposure management and resilience program.
- Integrate existing attack simulation and penetration testing scenarios in an AEV roadmap as part of a shift from vulnerability management to a CTEM program.
- Onboard existing red teams by demonstrating that the automation helps support more interesting human-led red-teaming activities while enabling a collaborative “purple-teaming” approach, which helps improve threat detection, investigation and response.
- Understand the benefits and challenges resulting from the various deployment options. Different options for testing, such as agent or agentless, can impact results.
Sample Vendors
AttackIQ; Cymulate; Filigran; FireCompass; Horizon3.ai; Pentera; Picus Security; Pikered; Ridge Security; SafeBreach; SCYTHE
Gartner Recommended Reading
At the Peak
CPS Security
Analysis By: Katell Thielemann
Benefit Rating: High
Market Penetration: More than 50% of target audience
Maturity: Early mainstream
Definition:
Cyber-physical systems (CPS) security is the overall discipline to ensure that CPS remain safe and resilient in the face of growing threats. CPS are engineered systems that orchestrate sensing, computation, control, networking and analytics to interact with the physical world (including humans). They are created as physical assets that become connected to each other or to enterprise IT systems and as automation and production robots are deployed. They may be called OT, IoT, ICS or SCADA.
Why This Is Important
CPS include everything from critical infrastructure equipment in energy, water systems, communications or smart cities, to autonomous vehicles and smart manufacturing. They connect digital technology with physical processes and outcomes and, therefore, mandate a unique security approach because human safety, production reliability and resilience are paramount. CPS are increasingly targeted by attackers seeking to steal data, demand ransom, derail production or sow geopolitical unrest.
Business Impact
Unlike IT systems that create, store, transact or transform data, consequences of a successful cyberattack in CPS environments can include operational shutdowns, environmental impacts, damage and destruction of property and equipment, and even personal and public safety risks. CPS security efforts, therefore, need to focus on human safety and operational resilience and consider all cybersecurity best practices, the laws of physics and industry-specific engineering decisions.
Drivers
- The last few years have seen a marked increase in attacks from nation states and extortionists alike that have led to loss of visibility or loss of control in manufacturing and critical infrastructure production environments. Because these areas are usually where value is created or essential public services are performed, CPS will continue to be targeted.
- Risks that extend to the physical world require measures above and beyond “regular” cybersecurity. Such risks include remote access, physical perimeter breaches, USB insertion, controller area network bus injections, GPS jamming, hacking, spoofing, tampering, command intrusion and malware implantation in physical assets.
- While the domains of ”regular” cybersecurity (the “whats”) largely apply, the “hows,” “whos” and “whens” differ to account for the nature of production mission-critical environments.
- The generic OT security market has evolved into specific CPS security categories. These include:
- CPS protection platforms
- CPS secure remote access
- CPS backup and recovery
- CPS security training and cyber ranges
- CPS risk management
- CPS network cloaking and segmentation
- CPS security services
- CPS removable media security
- CPS unidirectional gateways
- CPS threat intelligence
- CPS wireless security
- Because of the prevalence of CPS in critical infrastructure sectors, and the tight relationship between critical infrastructure and national security, governments worldwide are turning to security regulations and directives to mandate minimum security controls.
Obstacles
- CPS are often deployed by business units without consulting the security team.
- Most organizations still focus mainly on IT-centric risk management, focusing on data confidentiality, integrity and availability instead of safety and resilience.
- Many organizations do not have structured security programs or skills that sufficiently cover the scope of CPS, especially high-value/mission-critical assets.
- Because CPS product standards that guide security design and usage are still evolving, many manufacturers value “speed to market” over “secure to market.”
- Many CPS lack storage and compute power to facilitate security mechanisms and remain in use past traditional end-of-service/end-of-life timelines.
- The omnipresence of CPS devices in buildings, cities, homes and vehicles tests the scalability of traditional security methods.
User Recommendations
- Prioritize security controls and “secure by design” practices in new procurements.
- Discover all connected assets using tools designed specifically for CPS environments.
- Evaluate which CPS assets are high-value or mission-critical, identify specific CPS security controls already in place, and determine whether any gaps need to be prioritized based on potential organizational impact.
- Create an investment plan to update security and risk management strategies and programs in relation to CPS, starting with the high-value and mission-critical assets.
- Engage functional business leaders to establish clear risk ownership, define domain-specific controls for CPS, and balance trade-offs between growing the business and improving security.
- Evaluate the growing list of CPS security solutions, as there are more options than ever before.
Sample Vendors
Armis; Cisco; Claroty; Darktrace; Dragos; Forescout; Fortinet; Honeywell; Nozomi Networks; Palo Alto Networks; Tenable; TXOne Networks
Gartner Recommended Reading
Exposure Assessment Platforms
Analysis By: Mitchell Schneider, Dhivya Poole, Jonathan Nunez
Benefit Rating: High
Market Penetration: 20% to 50% of target audience
Maturity: Early mainstream
Definition:
Exposure assessment platforms (EAPs) continuously identify and prioritize exposures, such as vulnerabilities, misconfigurations and control gaps, across diverse asset classes. They visualize attack paths to business-critical assets and enable remediation through integration with ticketing systems, patching workflows and compensating controls. EAPs aggregate exposure data from external discovery tools or perform native discovery to centralize and contextualize exposures for unified visibility.
Why This Is Important
Without a comprehensive focus on continuous threat exposure management (CTEM), cybersecurity leaders risk reputational damage, regulatory fines, data loss and security breaches. EAPs are an essential technology element supporting CTEM programs by providing a comprehensive and prioritized view of exposures across a broad range of asset classes, streamlining remediation and addressing business risk.
Business Impact
EAPs enable organizations to proactively identify exposures most likely to be exploited and speed decisions on remediation or mitigation, helping prevent attackers from leveraging known exposures. EAPs improve operational efficiency, support business-driven prioritization and streamline remediation by consolidating results, automating identification of critical assets, assigning ownership and coordinating workflows. They also provide reporting and exposure-trend insights.
Drivers
- Organizations need a more advanced approach than just CVSS scores or basic external data for vulnerability prioritization. EAPs use richer internal context — asset and business criticality, environment details, control effectiveness and cybersecurity validation — to deliver actionable insights. Some vendors add predictive models for likely future exploits, but these also need internal context for meaningful prioritization.
- EAPs highlight the most significant exposures, deduplicate findings, and help prioritize remediation or compensating controls to prevent compromise. Attack path analysis adds insight by showing how exposures can chain together, refining which issues pose real risks.
- EAPs reduce operational overhead from misprioritized findings with a consolidated view, helping organizations retain talent and improve efficiency by focusing on higher-value activities. Automation features further cut manual triage and speed remediation.
- EAPs enhance SOC efforts like TDIR by providing contextual asset enrichment and multiple views (e.g., attack paths) to accelerate investigations. Deeper integration with SIEM and ITSM platforms enables more coordinated workflows.
- Organizations are broadening their scope to include not just traditional vulnerabilities but also exposures without CVEs, like misconfigurations, identity hygiene issues, SaaS risks and control gaps, driving demand for EAPs that unify discovery across the attack surface.
- Automated, closed-loop remediation is increasingly required. EAPs meet this need by integrating with ITSM, SOAR, EDR, CNAPP and patching tools, enabling faster, more consistent exposure treatment and reducing reliance on manual processes.
- Continuous, defensible insight into control effectiveness and exposure trends is essential for cyber GRC. EAPs provide telemetry-based reporting, ongoing validation and auditable remediation tracking, supporting continuous, data-driven compliance over checklist approaches.
Obstacles
- EAPs offer limited value when applied to broken, undefined or immature processes in vulnerability management. Without clear ownership, strong data hygiene and operational workflows, even advanced capabilities yield minimal improvement.
- Organizations that restrict EAP use to compliance mandates or static CVSS scoring will not realize full value, as this overlooks business context and criticality, exploitability, active threat behavior and cybersecurity control effectiveness.
- EAPs can produce attack path analysis, but it is also available through AEV tools that focus on attack simulation and cybersecurity validation. Organizations with existing AEV investments may not view passive attack‑path visualization features as providing meaningful added value.
- Organizations operating multiple overlapping platforms may face fragmented inventories, inconsistent data models and competing prioritization engines, reducing overall clarity and operational impact.
User Recommendations
- Implement an outcome-driven approach that:
- Identifies available context (e.g., stakeholder needs, compliance requirements) for prioritization and ensures data quality and ownership are sufficient to prevent negative impact.
- Correlates asset business context, threat intelligence, cybersecurity controls, security configurations and proprietary algorithms to calculate a dynamic, evidence-based risk rating.
- Shift from siloed tools to EAPs to centralize asset, attack surface and vulnerability management using AI-supported prioritization, automated remediation and attack path insights.
- Select vendors with strong bidirectional integrations to broaden attack surface visibility, refine prioritization and support coordinated, cross-team remediation.
- Deploy EAPs that evaluate exposure telemetry, starting with control configurations and expanding to cloud, identity and SaaS posture for a more actionable threat landscape.
Sample Vendors
Axonius; CrowdStrike; Microsoft; Nucleus Security; Qualys; Rapid7; ServiceNow; Tenable; Wiz; XM Cyber
Gartner Recommended Reading
Red Teaming as a Service
Analysis By: Dhivya Poole, Mitchell Schneider
Benefit Rating: High
Market Penetration: 5% to 20% of target audience
Maturity: Emerging
Definition:
Red teaming as a service (RTaaS) delivers continuous, on-demand threat-led adversarial testing through a subscription model that combines humans and automation. It emulates current, realistic adversary behavior and tactics, techniques, and procedures (TTPs) to evaluate the resilience of people, processes, and technology. RTaaS validates real-world, full kill-chain detection and response effectiveness across enterprisewide attack surfaces.
Why This Is Important
Defenders are falling behind as cloud, AI, and identity sprawl create attack surfaces that change daily, faster than annual assessments or static controls can track. RTaaS exposes these gaps by continuously validating whether people, processes, and technology can detect and respond to real‑world adversary behaviors. It operationalizes threat intelligence into actionable scenarios and helps security teams build resilience to counter threats that increasingly outpace internal capabilities.
Business Impact
RTaaS shifts cybersecurity from static testing to ongoing resilience validation. It reduces critical exposure windows and exploitable enterprise weaknesses across people, processes, and technology. Continuous adversarial testing provides leadership with evidence of defensive readiness and assurance that critical controls, including those protecting high‑value digital assets, perform effectively under real attack conditions.
Drivers
- Skills and capacity gap: Many organizations lack the offensive expertise required for high‑fidelity testing. RTaaS provides access to specialized talent without the fixed cost of staffing a full internal red team.
- Continuous improvement: RTaaS enables continuous resilience gains and maintains operational readiness through repeated adversarial testing that one-time red team tests cannot match.
- Escalating adversary behaviors: Attackers are evolving rapidly, evading detection better and exploiting broader attack surfaces. RTaaS allows organizations the flexibility to test whether their defenses can detect and contain these real-world behaviors before they cause material impact.
- Rising cost of cyberattacks: The global financial impact of cyberincidents is escalating, fueled by faster attacker progression, proliferation of extortion models, and higher recovery costs. RTaaS enables organizations to proactively test resilience against impactful intrusions to expose gaps earlier, reduce dwell time and exposure windows, and limit the operational and financial consequences of successful breaches.
- Regulatory momentum: Intelligence‑led resilience testing is increasingly expected to ensure operational and systemic resilience, accelerating adoption across regulated sectors, such as financial and critical national infrastructure.
Obstacles
- Operational risk: Live simulation on production systems can disrupt services or affect data integrity without strict scoping, monitoring, and kill‑switch controls.
- Maturity dependency: Organizations without security operations center (SOC) coverage, incident response (IR) playbooks or baseline detections may struggle to action findings, limiting the actionability of the findings and overwhelming teams.
- Legal and privacy constraints: Realistic exercises require tight governance over data access, monitoring boundaries, and cross‑jurisdictional compliance.
- Coordination complexity: Threat‑led programs demand sustained collaboration to manage scope, deconflict incidents, tune scenarios, and keep intelligence relevant, straining limited operational capacity.
User Recommendations
- Prioritize readiness validation: Start with a targeted engagement to establish foundational maturity in SOC, IR, and detection before expanding to a continuous model.
- Use intelligence-driven scenarios: Focus exercises on targets and workflows identified through threat intelligence as most likely to be targeted.
- Establish stringent rules of engagement (RoE): Establish clear RoE covering prohibited actions, escalation, data handling, and business-risk-linked safe-stop conditions.
- Mandate purple team replay: Conduct joint walk-throughs to allow defenders to observe scenarios and enhance detection and response.
- Mobilize findings: Integrate output into SOC tooling, SIEM/XDR rule refinement, ticketing systems, and IR workflows to drive continuous improvement.
- Measure critical metrics: Track dwell time, mean time to detect/contain, and detection coverage/performance against TTPs (new and historical) to objectively demonstrate resilience gains.
Sample Vendors
Bishop Fox; BreachLock; Bugcrowd; CovertSwarm; Google (Mandiant); IBM; NetSPI; Rapid7; Rootshell Security
Gartner Recommended Reading
AI SOC Agents
Analysis By: Eric Ahlm
Benefit Rating: Moderate
Market Penetration: 1% to 5% of target audience
Maturity: Embryonic
Definition:
AI SOC agent solutions use AI to help augment many of the common activities found within security operations. AI SOC agents can be used to augment investigation through natural language query, false-positive reduction, alert enrichment, attack path contextualization, reporting summarization and next-step advisory.
Why This Is Important
AI SOC agent tools are emerging, mostly unproven technologies promising to augment security operations workforces across a wide range of activities and roles. This augmentation can reduce the time needed for tasks like initial alert triage, managing false positives, lowering the required skill sets for activities, decreasing errors, and boosting the overall performance of security operations center (SOC) operations.
Business Impact
- Improving efficiency: Managing false positives, enriching alerts, providing natural-language query, generating attack timelines and summarizing reports are areas where efficiency can be improved.
- Augmenting staff: Enhancing the performance of team members, which allows for increased workload capacity without needing additional headcount.
- Lowering skill requirements: Simplifying some activities, thereby reducing the learning curve for junior team members to perform standard SOC tasks.
Drivers
- Lack of resources to perform valuable security operations activities is a universal problem. Although still unproven, AI SOC agents are at the forefront for security operations leaders seeking to augment their workforces.
- Recruiting, hiring and retaining security operation team members is a challenge. AI SOC agents allow junior members to focus on more critical tasks, which can lead to better job satisfaction and retention.
- Users are often forced to make concessions on what alerts are investigated due to resource constraints. AI SOC agents promise to autoinvestigate and close out any volume of raw alerts, allowing for analysis of all data collected with fewer concessions based on resource constraints.
Obstacles
- AI SOC agent tools are still emerging, and claimed benefits are mostly unproven. Diligence is required to ensure outcomes such as measurable team workflow augmentation improvements are obtainable and any AI washing is debunked.
- Vendors often license agents aligned to specific activities performed in the SOC. Cost models may limit the widespread use of AI SOC agents across the variety of team functions.
- Cost justification for AI SOC agents may be difficult for smaller teams, as the real value of the solution is providing measurable gains in the operational cycle over the current team baseline.
User Recommendations
- Baseline your current state of operations by documenting the larger or more common activities that need improvement. Additionally, use this analysis to define evaluation criteria and build the cost justification for an AI SOC agent solution.
- Initiate AI SOC agent pilots to determine use-case fit and estimate potential augmentation improvements to your team. Start with common SOC functions such as event triage or false-positive reduction.
- Consult with your larger incumbent security platform vendors of SIEM and XDR first before considering an AI SOC agent solution, as many vendors have workflow augmentation agent capabilities on their product roadmaps.
Sample Vendors
7AI; Arcanna.ai; Conifers.ai; Crogl; Dropzone AI; Exaforce; Intezer; Qevlar AI; Prophet Security; Simbian
Integrated Security Operations Center Systems
Analysis By: Eric Ahlm
Benefit Rating: High
Market Penetration: 5% to 20% of target audience
Maturity: Early mainstream
Definition:
ISOC systems offer a unified threat detection, investigation, and response (TDIR) strategy, often leveraging integrated technologies or services from a single vendor. They serve as an alternative to traditional SIEM platforms, sharing core features like data ingestion, analysis, and response. ISOC systems provide high out-of-the-box value, often prioritizing this over open flexibility. Consequently, they typically rely heavily on the vendor’s provided integrations and content.
Why This Is Important
Performing TDIR is essential to organizations of all sizes. However, many smaller to midsize organizations report challenges due to complexity and cost using traditional SIEM platforms. ISOC systems offer a simplified approach to TDIR as an alternative to classic SIEM.
Business Impact
ISOC systems can impact businesses by:
- Reducing the vendor sprawl and complexity of TDIR operations through more reliance on vendor-created integrations and out-of-the-box (OOTB) content.
- Allowing security operations teams to perform at higher scale through integrated workflow augmentation features such as AI and automation for common activities.
Drivers
- Managing detection stack dependencies, integrations, and content is a key buyer concern. ISOC systems promise complexity reduction through single vendor reliance to solve this issue.
- Buyers demand better quality and consistent performance from managed security services providers. Many ISOC systems vendors offer native service offerings for their products, potentially leading to more predictable service results.
- The high cost of classic SIEM platforms remains a top concern. ISOC systems’ consolidated approach to TDIR can offer cost advantages by bundling multiple products and/or services and reducing the number of vendors to manage.
- Currently, many organizations fail to meet basic TDIR goals because security information and event management (SIEM) operations are complex, which results in inefficient or underperforming operations. ISOC systems offer the hope of simplifying operations to improve TDIR outcomes.
Obstacles
- A major concern for buyers evaluating ISOC systems is vendor lock-in. Terminating a vendor relationship with an ISOC systems provider could lead to having to migrate several tools at a single point in time, which presents a significant obstacle.
- The shift from a traditional SIEM to an ISOC system necessitates a comprehensive project plan aimed at replacing various technologies within a condensed time frame. Consolidating multiple vendors and solutions into a single technology stack over a short duration can pose a significant challenge.
- Moving to an ISOC system involves switching out multiple best-of-breed solutions in favor of a single vendor solution. Moving from a best-of-breed mindset to a single vendor solution across multiple technologies is likely to have internal cultural pushback.
- Buyers who heavily rely on advanced features within their existing SIEM may view the limited features of ISOC systems as a significant challenge.
User Recommendations
- Consider ISOC systems as a SIEM migration candidate if complexity of operations is your top concern.
- Evaluate gained operations efficiency to justify the cost savings; ISOC systems can drive down costs, but the cost savings are usually measured as a combination of product and labor cost reduction.
- Consider ISOC systems with integrated native service offerings when prioritizing predictable managed security services. Vendors managing their proprietary technology stacks often have advantages in delivery quality and scale.
- Shift focus from measuring the performance of individual components to measuring the performance and output of the system as a whole when evaluating ISOC systems.
- Plan to use all core components provided by the chosen vendor when selecting ISOC systems. Mixing and matching components, while technically possible, diminishes the value of complexity reduction that the platform is intended to provide.
Sample Vendors
CrowdStrike; Microsoft; Palo Alto Networks; Rapid7; SentinelOne; Sophos; Stellar Cyber; Trend Micro
Threat Exposure Management
Analysis By: Pete Shoard, Jeremy D'Hoinne, Mitchell Schneider
Benefit Rating: Transformational
Market Penetration: 20% to 50% of target audience
Maturity: Early mainstream
Definition:
Threat exposure management encompasses processes and technologies that allow enterprises to continually and consistently assess the visibility and validate the accessibility and exploitability of their digital assets. It must be governed by an effective continuous threat exposure management (CTEM) program.
Why This Is Important
The diversity of modern infrastructure affects organizations’ ability to accurately assess cyber risks. Security teams often struggle to identify modern exposure types, leaving security gaps due to accelerated AI usage and lack of Identity oversight, SaaS and cyber-physical systems security. Threat exposure management addresses these challenges by enabling identification, prioritization and validation of issues across diverse attack surfaces and ensuring comprehensive visibility and mitigation.
Business Impact
Threat exposure management governs and prioritizes risk reduction for the modern enterprise. It requires assessment of all business-related systems, applications and subscriptions, broadening risk understanding for today’s digital landscape. CTEM programs factor in business importance, likelihood of attack, visibility of vulnerability and validation of the existence of an attack path, enabling businesses to mobilize responses to genuine, impactful risks.
Drivers
- Organizations seek to upgrade vulnerability management programs to demonstrate to the business that cyber risk is more pervasive than simply traditional IT assets that require patching. For instance, there are new threats and increased exposure from rapid technology development in areas such as AI. Threat exposure management provides business alignment through the scoping process and helps reduce volumes of irrelevant or nonbusiness-critical issues.
- Exposure is a factor of not only where vulnerabilities exist, but also where impacts to normal business processes can be most greatly felt. Threat exposure management aims to allow reprioritization of treatments as environments shift in a rapidly changing and expanding IT landscape.
- Organizations commonly silo exposure activities, such as penetration testing, threat intelligence management and vulnerability scanning. Siloed views provide little or no awareness of the complete picture of cyber risk.
- Modern technologies, application development and innovation efforts with AI, as well as the increasingly pervasive use of third-party SaaS applications, is making organizations susceptible to invisible and high-impact exposures. Vulnerability management approaches have focused too much on systems and software-based exposures, where a much wider set of visibility and new remedial responses are required to reduce the exposure to new threats.
- Vendor offerings to identify threat exposures have consolidated into exposure assessment platforms (EAP), offering broader visibility into exposures as standard. End users now frequently consider nonpatchable technology issues as potential threats and are planning response actions for new scenarios.
Obstacles
- The increased scope of CTEM programs over traditional VM introduces many new complexities often not previously considered or budgeted for.
- While evaluating new exposures is necessary, building effective response processes and the ability to mobilize a gradient of countermeasures, such as threat monitoring and control configuration, is lacking. Many organizations are not prepared to respond to modern threat scenarios.
- Processes to manage end-to-end awareness (from visibility of attack vectors to response to breaches) are virtually nonexistent in most organizations, which often simply scan their networks for compliance reasons. Regulations rarely factor in the exploitability of exposures.
- Assessing the complexity of attacks requires new skill sets. Market areas, such as adversarial exposure validation (AEV), make it simple to test the out-of-the-box scenarios using simulation tools. But users need new skills to be effective at using these capabilities and customizing scenarios.
User Recommendations
- Evolve vulnerability management programs with CTEM to manage a wider set of exposures. Focus on business importance when building target scopes. Don’t scan for or try to find every possible exposure, but drive toward reducing risk in areas of significant business importance.
- Preagree routes to mobilize responses to exposures with a variety of stakeholders, as success depends on it. Automated remediation of gaps in security posture remains unlikely to have a significant impact due to end-user trust in solutions and the complexity of resolution paths.
- Communicate exposure risk to the board. Executives must be made aware of changes to exposure and be encouraged to allocate adequate resources to proactive security.
- Validate that exposures genuinely exist and that security controls are functioning as expected with automated testing tools such as AEV.
- Include assets that your organization doesn’t directly own, such as social media accounts, SaaS and data held by supply chain partners.
Gartner Recommended Reading
Sliding into the Trough
Penetration Testing as a Service
Analysis By: Mitchell Schneider, William Dupre, Carlos De Sola Caraballo
Benefit Rating: High
Market Penetration: 20% to 50% of target audience
Maturity: Adolescent
Definition:
Penetration testing as a service (PTaaS) delivers automated and human‑led testing through a SaaS platform to support point‑in‑time, continuous and change‑driven assessments. It uses automation, validation workflows and human expertise to improve consistency and efficiency, and increasingly incorporates external attack surface discovery to expand coverage.
Why This Is Important
PTaaS modernizes pentesting by providing faster scheduling, real‑time collaboration and continuous visibility into findings. It supports continuous threat exposure management (CTEM) by enabling dynamic scoping, adaptive retesting and quicker mobilization of results. Automation‑first delivery improves consistency, accelerates remediation and integrates with DevOps and ticketing workflows to demonstrate progress to stakeholders.
Business Impact
PTaaS complements exposure assessments and traditional application security testing while improving cost efficiency and the quality of pentesting output. It enhances security posture by enabling continuous or change‑based validation earlier in the software development life cycle and provides real‑time findings through a platform that accelerates remediation and collaboration.
Drivers
- Organizations are turning to PTaaS to address expanding attack surfaces driven by public cloud adoption and the growth of internet‑facing digital assets. PTaaS enables developers to collaborate directly with pentesters instead of relying solely on DAST/SAST scanners, improving issue resolution and reducing dependence on traditional tool‑based workflows.
- Organizations with limited in‑house expertise continue to adopt PTaaS to meet compliance and risk‑management objectives while strengthening their overall security posture. To support rapid release cycles, security‑aware teams are integrating more agile pentesting approaches into CI/CD pipelines as part of DevSecOps practices.
- Gartner clients are testing more frequently to support CTEM, but manual pentesting remains too costly for modern cloud‑centric environments. PTaaS delivers automated workflows, faster mobilization and on‑demand or continuous testing through subscription models that better align with evolving infrastructure.
- Organizations increasingly adopt PTaaS to support broader exposure management programs as providers integrate external attack surface discovery and automated validation to align testing with CTEM workflows.
- Most organizations maintain dedicated pentesting budgets and increasingly seek higher value for the same spend. Automation‑first, technology‑led PTaaS models can improve both testing frequency and deliverable quality without requiring significantly greater investment.
- Engaging external researchers can introduce legal and operational complexity. PTaaS platforms reduce this complexity by offering standardized engagement models, vetted testers and integrated workflow support, lowering the time spent on coordination, authorization and payment management.
- Security teams adopt PTaaS to validate and mature SOC capabilities. Real‑world findings from continuous or on‑demand testing help refine detection logic, strengthen response playbooks and improve operational resilience.
Obstacles
- Many providers still focus on internet‑facing assets such as web and mobile applications, which may not address broader testing needs. PTaaS platforms can also struggle in complex environments that require deep domain expertise.
- PTaaS offerings’ depth and extensibility remain less flexible than statement‑of‑work‑driven engagements, limiting specialized or highly customized testing requests.
- PTaaS overlaps with adversarial exposure validation (AEV), creating use-case confusion, although AEV focuses on continuous attack simulations while PTaaS emphasizes human expertise and structured validation.
- Variability in tester continuity, limited business‑impact context and inconsistent compliance acceptance continue to hinder adoption, requiring organizations to verify provider capabilities and regulatory alignment.
- Emerging “agentic pentesting” claims create confusion, as AI‑driven autonomous testing is often positioned similarly to PTaaS despite wide variation in maturity, reliability and scope.
User Recommendations
- Determine which mix of penetration testing approaches — compliance‑driven engagements, PTaaS, in‑house red teams or bug bounty — best fits your needs.
- Confirm the scope PTaaS vendors can deliver, as not all support internal infrastructure, wireless, social engineering or physical testing. Favor hybrid models that combine automation with human expertise for more effective and efficient results.
- Select PTaaS vendors that align with applicable compliance requirements and provide broader coverage than only internet‑facing assets. Evaluate whether providers deliver adjacent capabilities, either natively or through integrations with solutions such as exposure assessment platforms (EAP) to support CTEM workflows.
- Seek vendors that deliver tailored guidance and integrate with DevOps, CI/CD and ticketing systems to streamline workflows and reduce skills‑gap pressures.
Sample Vendors
Astra Security, BreachLock, Bugcrowd, Cobalt, Ethiack, HackerOne, NetSPI, Siemba, Synack, Sprocket Security
Gartner Recommended Reading
Cyber Range
Analysis By: Dhivya Poole, Eric Ahlm
Benefit Rating: Moderate
Market Penetration: 5% to 20% of target audience
Maturity: Emerging
Definition:
A cyber range constitutes a technology-enabled virtual simulation environment that closely replicates information technology (IT)/operational technology (OT) networks, systems, identities, and traffic. It integrates a learning management system with orchestration capabilities and specialized tools to establish a secure sandbox suitable for live-fire cybersecurity training, comprehensive skills assessment, and rigorous testing of technologies and incident response playbooks.
Why This Is Important
Cyber range represents a fundamental shift in cybersecurity education and operational readiness, moving beyond traditional, theoretical-only training models. Relying solely on abstract knowledge and classroom learning is insufficient to prepare security teams for the dynamic, high-stakes realities of real-world threats. Advanced, targeted attacks, such as sophisticated ransomware campaigns, supply chain compromises, and zero-day exploits, demand a practical, hands-on understanding.
Business Impact
- Risk reduction: Prepares teams to safely execute attack scenarios to detect and respond to attacks, thereby lowering breach risk and reducing mean time to respond (MTTR).
- Operational resilience: Tests incident response, business continuity, disaster recovery plans, in realistic scenarios, strengthening resilience and validating processes.
- Talent management: Provides hands-on adversary-aligned training, improves hiring and retention through practical skills assessments and ongoing upskilling.
Drivers
- Escalating threats: Ransomware, AI-driven attacks and rapidly evolving adversary techniques require dynamic and safe environments where teams can rehearse realistic attack scenarios. Cyber ranges enable dynamic, high-fidelity simulation that static labs cannot match, helping organizations prepare for complex, multistage attacks.
- Cloud adoption: Cloud delivery reduces costs and deployment complexity, making advanced attack-scenario simulation and emulation accessible to more organizations. This approach accelerates training, experimentation, and scenario development without requiring dedicated infrastructure.
- IT/OT convergence: As threats increasingly target OT and critical infrastructure, organizations need hybrid environments that can safely run IT and OT attack scenarios. Cyber ranges allow realistic testing of adversary behaviors across ICS and SCADA to identify pathways without risking production outages.
- AI adoption: As organizations increasingly adopt autonomous agents and copilots to enhance operational efficiency, cyber ranges provide secure, controlled environments for safe experimentation and scenario development. Teams can validate and stress-test emerging AI security capabilities against realistic threats, train models, ensure human oversight, and provide reliability to deploy AI without risking production systems.
- Skills gap: The shortage of qualified professionals increases the need for scalable, hands-on training platforms where teams can practice realistic and complex attack scenarios. Cyber ranges help build practical red, blue, and purple teaming capabilities, strengthening readiness to detect, respond, and contain threats.
- Tabletop maturity: For organizations advancing beyond tabletop exercises, cyber ranges provide the subsequent phase: offering a realistic, controlled attack simulation environment for high-fidelity technical validation of the assumptions and outcomes derived from those initial exercises.
Obstacles
- Resource intensity: Building and maintaining in-house ranges incurs substantial costs and complexity, and it demands specialized proficiency.
- Content development: The scarcity of experts capable of crafting current, high-fidelity attack scenarios introduces a risk to the relevance of training.
- Complexity: The simulation of specialized or legacy environments (e.g., SCADA, banking mainframes) presents significant technical difficulties and is expensive.
- Interoperability: Proprietary platforms may limit seamless integration with external third-party tools or the exchange of scenario content.
User Recommendations
- Prioritize SaaS/cloud delivery: Opt for cloud-based solutions to benefit from lower costs and access to up-to-date content.
- Align with use cases: Clearly define objectives, such as skills development, recruitment, or technology validation, to ensure platform compatibility with existing technologies and organizational requirements.
- Evaluate content freshness: Select providers that offer regularly refreshed scenarios informed by current cyberthreat intelligence.
- Integrate with existing security stack: Ensure the platform facilitates integration with your operational security tools (e.g., SIEM, EDR, etc.) to enable realistic training simulations.
Sample Vendors
Cloud Range; Cyberbit(RangeForce); CybExer; CYBER RANGES; Hack The Box; IBM X-Force; Immersive Labs; Keysight (IXIA); SANS Cyber Ranges; SimSpace
Gartner Recommended Reading
Bug Bounty as a Service
Analysis By: Dhivya Poole, Craig Lawson, Mitchell Schneider
Benefit Rating: Moderate
Market Penetration: 5% to 20% of target audience
Maturity: Adolescent
Definition:
Bug bounty as a service (BBaaS) delivers crowdsourced exposure discovery through a SaaS platform combining vetted, global ethical hackers with managed triage and payment handling service. BBaaS combines automation and managed oversight to streamline scope, engagement, triage, rewards and reporting. It extends traditional bug bounty programs by providing continuous, on-demand testing at scale, helping organizations identify real-world vulnerabilities while reducing program overhead.
Why This Is Important
BBaaS offers continuous, diverse and scalable real-world testing of applications and assets, moving beyond point-in-time assessments. It uses global crowdsourced expertise to find logic flaws, hidden assets and emerging issues that automated tools such as vulnerability scanners miss. By rewarding impactful findings, not hours billed, BBaaS helps speed risk reduction and supports “always on” assurance aligned with agile and DevOps delivery.
Business Impact
BBaaS helps prevent breaches by finding exploitable vulnerabilities early, especially in complex, public applications. Integrated with DevSecOps, it accelerates fixing via real‑time researcher collaboration. Though cost‑efficient compared with large consulting contracts, its true value relies on timely remediation and managing validated findings. It complements, rather than replaces, other offensive security methods like penetration testing.
Drivers
- Expanding attack surface: Rapid digital transformation, cloud and AI proliferation create an ever-expanding attack surface that outpaces point-in-time assessments. BBaaS complements penetration testing and other offensive security methods by providing continuous, diverse testing across distributed assets, uncovering exposures that static or periodic methods miss.
- Talent shortage: The expanding cybersecurity skills gap drives organizations to seek external expertise or to augment internal resources. BBaaS provides access to specialized researchers, with deep knowledge of niche technologies, reducing dependence on limited internal teams.
- Continuous delivery: Agile and DevOps models demand security testing that matches rapid deployment cycles. Continuous submission of vulnerabilities through bug bounty programs ensures critical issues are discovered at the speed of code changes, outpacing periodic assessments.
- Threat complexity and diversity: Modern attacks exploit subtle logic flaws, chained misconfigurations, and edge-case behaviors. A diverse global researcher base increases the likelihood of uncovering these nuanced issues that scanners and traditional tests often miss.
- Cost efficiency: The bounty-based compensation model means that the organizations pay primarily for verified vulnerabilities, improving budget predictability and aligning spend with measurable risk reduction.
- Vulnerability disclosure program (VDP) enablement: Vendors increasingly offer integrated VDP features like submission portals, coordinated disclosure, safe‑harbor terms and triage support, giving researchers a safe reporting channel. This lowers legal risk, prevents unmanaged disclosures and broadens visibility beyond planned testing.
Obstacles
- Trust and privacy concerns: Allowing external researchers to test sensitive systems can raise fears about unauthorized access and data privacy even when rigorously vetted.
- Budget variability: Unpredictable bounty payouts make it hard to forecast costs; challenging organizations used to fixed budgets.
- Report noise without managed triage: Without managed triage, high volumes of low-quality or duplicate reports can overwhelm internal teams.
- Regulatory constraints: Some compliance requirements mandate certified testers or approved methodologies, limiting the use of global crowdsourcing models.
User Recommendations
- Start private: Launch with a private, invitation-only program using vetted ethical hackers to control submission volume and evaluate internal triage and remediation procedures. Move to public programs as your ability to handle findings matures.
- Define scope and rules: Set clear boundaries, exclusions and rules of engagement (ROEs) to protect both your organization and ethical hackers. Specify what is off-limits (e.g., social engineering, physical attacks) to avoid rule misinterpretation or unauthorized testing.
- Leverage managed triage: Utilize the managed triage services to filter out duplicates and false positives, so teams focus only on valid findings.
- Integrate workflows: Ensure development teams have the capacity and workflows (e.g., Jira integration) to fix findings promptly, as unresolved backlogs undermine the program value and adoption.
Sample Vendors
Bugcrowd; HackerOne; HackenProof; Intigriti; LRQA; Synack; YesWeHack; Yogosha
Gartner Recommended Reading
Cybersecurity AI Assistants
Analysis By: Jeremy D'Hoinne
Benefit Rating: Moderate
Market Penetration: 20% to 50% of target audience
Maturity: Adolescent
Definition:
Cybersecurity AI assistants leverage generative AI (GenAI) techniques to discover existing knowledge available from cybersecurity tools, generate content or code and assist security teams in their daily tasks. Cybersecurity AI assistants are mostly available as companion features in existing products, but can also take the form of a dedicated front end and can integrate software agents to take action.
Why This Is Important
Most cybersecurity technology providers are now embedding a GenAI assistant into their existing products. These cybersecurity AI assistants promise improved productivity but primarily reduce friction to use complex cybersecurity tools. They are evolving to be agentic, integrating further through the use of existing APIs in the tools they support. Many GenAI features presented as “AI agents” by cybersecurity providers today fall under the cybersecurity AI assistant category.
Business Impact
- Organizations use cybersecurity AI assistants as part of their existing tools to augment existing workflows.
- Cybersecurity can improve operator accuracy, resulting in lower business downtime and potentially less data loss due to security incidents.
- Organizations with high cybersecurity administrative turnover have shorter training periods due to the advantages of these assistants.
- Cybersecurity AI assistants help surface key alerts, configuration issues and suggest recommended next actions.
Drivers
- The biggest driver of adoption is that these assistants are automatically added to existing cybersecurity tools.
- Cybersecurity teams, pressured to cut costs and automate repetitive tasks, are seeing a surge in interest for the promises of AI agents, despite concerns over “agent washing.”
- Cybersecurity AI assistants help teams to quickly create general best-practice guidance, synthesize and analyze threat intelligence, automate the first steps in incident response and generate remediation suggestions for application security.
- Organizations continue to experience skill shortages and look for opportunities to automate resource-intensive cybersecurity tasks.
- Cyber risk analysts need to speed up cyber risk assessments and be more agile and adaptable through increased automation and prepopulation of risk data in context.
- More broadly, GenAI augments existing cybersecurity programs by better aggregating, analyzing and prioritizing inputs. These assistants then offer a guided response within the scope of the tool it supports.
Obstacles
- Assistants’ pricing is the biggest factor for the pace of adoption. Providers want to monetize investments, but buyers don’t see enough value to justify a paid option.
- Cybersecurity is plagued with false positives. One inaccurate GenAI response will cause caution about adoption and usage.
- Automated actions require accountability and lower false positive tolerance. Most assistants lack features to implement human in the loop (HITL) and convincing proofs of low false positive rates.
- Many organizations lack the process maturity and structured data flows for AI assistants’ benefits.
- Best practices and tooling to implement responsible AI, privacy, trust, security and safety don’t fully exist yet. Security teams might be reluctant to enable GenAI features without guarantees regarding data security and privacy.
- Cybersecurity AI assistants’ scope is often limited to the product they’re part of, creating fragmented insights and limited value.
User Recommendations
- Build AI literacy and develop metrics to measure the success of the pilot program.
- Be sure to have a control group to validate improvements attributed to AI against previously implemented processes
- Monitor the addition of GenAI assistants from your existing providers and beware of “agent washing.” Don’t pay a premium before obtaining measurable results.
- Evaluate privacy features and the model architecture to ensure the security of data shared with the GenAI assistant.
- Implement a documented approval workflow for allowing new generative cybersecurity AI experiments to avoid the unmanaged sharing of sensitive data.
- Implement a policy requiring that any content (that is, configuration or code) generated by an AI is fully documented, peer-reviewed by humans and tested before it is implemented. Otherwise, consider any AI-generated content as “draft only” when used for critical use cases.
Gartner Recommended Reading
Cybersecurity Incident Response Retainer Services
Analysis By: William Candrick, Wayne Hankins
Benefit Rating: High
Market Penetration: More than 50% of target audience
Maturity: Mature mainstream
Definition:
Cybersecurity incident response retainer (CIRR) services provide proactive and reactive services. The core reactive service provides incident response capabilities, including investigation, containment and eradication. Some services also provide full recovery. CIRR proactive services support cyber resilience before incidents occur, and often include maturity assessments, tabletops and pen tests. These professional services are sold as a retainer.
Why This Is Important
Incident response is a foundational cyber resilience capability. Yet most cybersecurity functions lack the full scope of tools, skills or capacity to handle complex incidents. CISOs adopt CIRR services to boost pre- and post-incident preparedness, and access specialized skills, such as ransom negotiation, expert witness, chain of custody and evidence retention.
Business Impact
Across all industries, cyber risk is now a top boardroom concern and a top business threat. In fact, 98% of board directors predict cyberthreats will grow over the next two years, and 93% view cyber risk as a threat to shareholder value (see Gartner Board of Directors Survey: Risk & Tech Spark M&A Activity Paradox).
Boards increasingly accept that cyber prevention isn’t possible, and instead demand that CISOs deliver robust cyber resilience. To succeed, CISOs must augment incident response capabilities with CIRR services to boost pre- and post-incident preparedness.
Drivers
- Cyber insurers often require or strongly prefer clients to have a CIRR in place. Some cyber insurers even offer CIRR services as part of their policies.
- Laws and regulations such as DORA and NIS2 require cyber resilience and shorter incident reporting timelines, necessitating a CIRR to improve compliance.
- Cybersecurity functions often lack the experience or bandwidth to handle all types or volumes of incidents. CIRR services augment existing cybersecurity capabilities and capacity.
- CEOs, CFOs, the board and PR firms often view employing a reputable CIRR service as a useful talking point to improve public relations and defend the brand during an incident.
- CPS and OT environments require specialized incident response capabilities — and even legacy techniques — offered by some CIRR services.
- Companies often lack the expertise to conduct digital forensics, maintain chain of custody and retain evidence during complex cyber crises.
- Many organizations procure a portfolio of external providers for major cyber incidents, such as breach coaches (external counsel), ransom negotiators, ransom payment facilitators, PR firms and credit monitoring services (for impacted customers and employees). A CIRR has experience coordinating across multiple external and internal stakeholders.
Obstacles
- Cybersecurity incident response is increasingly a team exercise spanning IT, legal, finance, operations, public relations, compliance and cybersecurity. CIRR services face growing complexity and higher expectations in how they navigate a crisscross of stakeholders during incidents.
- The proactive services offered by CIRR retainers don’t scale well across client bases. CISOs cite varied experiences, including citing “cookie cutter” tabletops, generic incident playbooks, and surface-level pen tests.
- General counsel and internal legal increasingly take a lead in procuring CIRR retainers, creating complexity in the sales cycle and forcing CISOs to coordinate, rather than lead, the procurement process.
- CIRR retainers are sometimes asked to work and communicate via external counsel. This is due to client-attorney privilege considerations, which can delay and complicate response actions and coordination with the client.
User Recommendations
- Consider a multiretainer sourcing strategy. This approach counters CIRR capacity and prioritization issues during global incidents, and enables flexible pricing strategies across prepaid and zero-hour retainers.
- Coordinate procurement with the General Counsel. Increasingly, organizations elect to structure retainers to strengthen client-attorney privilege, and integrate with breach coaches.
- Engage C-suite leaders to review and endorse your CIRR retainer. C-suite leaders may prioritize factors such as vendor brand perception or experience working with specific law firms.
- Evaluate bundling a CIRR retainer with other services and solutions. Many EPP, MDR and consulting providers also sell add-on retainers. Consider trade offs between cost and convenience, with the risks of placing faith in a single vendor to deliver both detection and response services.
Gartner Recommended Reading
Predictive Modeling for Cybersecurity
Analysis By: Yogesh Bhatt, Akif Khan, Jonathan Nunez
Benefit Rating: Moderate
Market Penetration: 20% to 50% of target audience
Maturity: Adolescent
Definition:
Predictive modeling is a forward-thinking approach that uses data analysis and supervised machine learning to forecast events or outcomes before they materialize. By analyzing extensive cybersecurity data, predictive modeling helps cybersecurity teams assess the likelihood of adversarial actions targeting an organization. In cybersecurity, it has traditionally supported fraud detection and vulnerability assessment and has recently expanded into threat intelligence and risk management.
Why This Is Important
Predictive modeling helps organizations prioritize security by focusing on vulnerabilities most likely to be exploited. When combined with threat intelligence, it enables automated actions such as blocking malicious activity. By aggregating data from multiple sources, it identifies patterns, improves early threat detection and enhances contextual accuracy.
Business Impact
In today’s digital ecosystem, cyberthreats are becoming more sophisticated, persistent and disruptive, while traditional security approaches remain largely reactive. Predictive modeling helps organizations shift from reactive to adaptive security by using real‑time data and AI. It enables teams to identify, score and mitigate risks proactively, reducing exposure and strengthening resilience against emerging threats, including those targeting cloud and hybrid environments.
Drivers
- Predicting cyberattacks and addressing exposures most likely to be exploited can reduce the costs associated with data breaches, including financial losses, reputational damage and regulatory penalties. The average cost of an enterprise breach is several million dollars.
- Traditional cybersecurity measures have been reactive in nature, responding to threats only after they occur.
- Cybersecurity leaders seek a proactive, data-driven approach that uses predictive modeling to gain foresight. This enables them to defend against existing threats and anticipate and remediate potential vulnerabilities before they are likely to be exploited, helping maintain a proactive security posture.
- Predictive modeling enables organizations to stay ahead of emerging threats by continuously learning from new data, internal context and signals to adapt their security programs.
Obstacles
- Data quality: High‑quality, comprehensive data is essential for predictive modeling but often difficult to obtain due to silos, incomplete datasets or limited access.
- Implementation: Developing and integrating predictive models into cybersecurity programs is complex, resource‑intensive and requires specialized expertise.
- Limitation: Predictive models can generate false positives or false negatives, creating unnecessary alerts or missed threats, especially without robust testing and validation.
- Threat landscape: Organizations see only a subset of threats, which limits model effectiveness against new or unknown attacks.
- Privacy and ethics: Large datasets introduce privacy and ethical concerns, particularly when they contain sensitive information.
- Cost: Building and maintaining predictive models requires significant investment, which can challenge organizations with constrained budgets.
- Integration: Ensuring models work with current cybersecurity tools is difficult and needs coordination.
User Recommendations
- Invest in quality data: Use high-quality, diverse data to boost predictive model accuracy.
- Establish AI literacy: Build or hire data science and cybersecurity expertise to support effective implementation.
- Prioritize buying: Buy predictive modeling solutions if lacking internal AI skills and resources.
- Start small and scale: Launch pilot projects, benchmark results and expand based on success.
- Focus on integration: Ensure models integrate seamlessly with existing cybersecurity tools and infrastructure.
- Update models: Regularly fine‑tune and refresh models to address evolving threats and new data.
- Manage alerts: Refine parameters and use supplementary tools to reduce false positives and false negatives.
- Evaluate cost-benefit: Assess financial impact and expected benefits to align investments with organizational goals.
- Monitor impact: Track performance and outcomes to ensure predictive modeling objectives are met.
Gartner Recommended Reading
XDR
Analysis By: Eric Ahlm, Franz Hinner, Thomas Lintemuth
Benefit Rating: Moderate
Market Penetration: 20% to 50% of target audience
Maturity: Early mainstream
Definition:
Extended detection and response (XDR) delivers unified security incident detection and response capabilities. XDRs integrate threat intelligence, security events and telemetry data from multiple sources, with security analytics to provide contextualization and correlation of security alerts. XDR must include native sensors. XDR can be delivered as a SaaS offering, and is typically deployed by organizations with relatively lower security maturity.
Why This Is Important
XDR will cease to exist in its current form as vendor TDIR capabilities expand and buyers prefer a more integrated set of cybersecurity technologies that support both native and third-party solutions.
Cybersecurity leaders should seek to migrate XDR solutions to workspace cybersecurity capabilities to better meet the requirements of endpoint and workspace security operations, or ISOC solutions if the primary objective is more aligned to TDIR operations.
Business Impact
XDR products in their current forms will cease to maintain relevance in the detection and response market. Large security players are co-opting the XDR concept and integrating it as a feature layer within their broader platforms. Organizations must reassess their investments to maintain functionality and value.
Drivers
- XDRs appeal to organizations with modest maturity needs, due to the detection logic, mostly vendor-provided, that generally requires less customization and maintenance.
- XDRs appeal to organizations looking for improved collaboration across the security stack components, as well as those looking to lower the administration requirements of more complex TDIR solutions.
- Overall operations reduction drives buyers to XDR solutions, since the vendor takes on many responsibilities involving managing stack dependencies, scaling workflows and providing detection content.
- Purchasing a platform product like XDR simplifies the vendor acquisition and integration challenges associated with best-of-breed strategies.
Obstacles
- The XDR market movement toward obsolete before plateau should be considered a major obstacle for buyers seeking a new XDR solution acquisition.
- XDR’s limited extensibility creates obstacles for clients who wish to build highly customized detection and monitoring use cases using solutions outside of the XDR vendor’s preferred open ecosystem.
- Expanding an XDR detection stack’s capabilities through the addition or replacement of security controls will be limited by the vendor.
- XDR may be a poor choice for high maturity security operations centers (SOCs) that require role-based dashboards, advanced workflows and large-scale enterprise architectural capabilities.
User Recommendations
- Carefully evaluate your needs to see if your current XDR solution or potential new purchase aligns to either enhancing workplace security or simplifying security operations for TDIR functions instead of a SIEM solution.
- Migrate from XDR to a workplace security product if your goals of usage are more aligned to better security posture and policy management between endpoints, applications, data and end-user identities.
- Migrate from XDR to an ISOC solution if your goals for XDR usage are more aligned to supporting TDIR objectives on a centralized platform.
Sample Vendors
Cisco; CrowdStrike; Fortinet; Microsoft; Palo Alto Networks; SentinelOne; Sophos; Stellar Cyber; Trellix; Trend Micro
Gartner Recommended Reading
Identity Threat Detection and Response
Analysis By: Mary Ruddy
Benefit Rating: High
Market Penetration: More than 50% of target audience
Maturity: Adolescent
Definition:
Identity threat detection and response (ITDR) is a discipline that leverages advanced tools and best practices to secure the entire identity and access management (IAM) environment — including IAM controls, configurations and related assets — from sophisticated attacks. ITDR solutions focus on proactive detection capabilities, responses to diverse attack vectors and restoration back to normal operations as necessary.
Why This Is Important
Identity is foundational for security (identity-first security). Therefore, IAM must be operated with a security mindset as threat actors are targeting the identity systems themselves. Credential abuse is a top attack vector, according to the 2025 Data Breach Investigations Report by Verizon Business. Organizations must increase the maturity of their process for protecting their IAM infrastructure. ITDR adds additional layers of security to IAM and cybersecurity deployments.
Business Impact
Securing IAM is mission-critical for identity and security operations. If accounts or the IAM infrastructure itself are compromised, attackers can take control of systems and disrupt operations. Protecting IAM is a top priority. “Business-as-usual” processes that seemed adequate before attackers targeted IAM directly are no longer sufficient. This can require multiple ITDR-enabling tools, which may include tools already in the organization’s portfolio.
Drivers
- Sophisticated attackers actively target IAM. Administrator credential misuse is now a primary vector for attacks against IAM tools. Attackers can use administrative permissions to gain access to a global administrator account or a trusted token-signing certificate to forge tokens for lateral movement.
- Modern attacks prove conventional identity hygiene is only part of the solution. There is no such thing as perfect prevention. Multifactor authentication and entitlement management processes can be circumvented.
- ITDR is needed as an additional layer beyond access management (AM), identity governance and administration, privileged access management, security information and event management, and identity posture management.
- IAM and infrastructure security controls have major detection gaps. IAM is traditionally used as a preventive control, whereas infrastructure security often has limited depth when detecting identity-specific threats. ITDR demands more specific capabilities that operate with lower latency than general-purpose detection and response tools.
- Ensuring the integrity of IAM infrastructure requires deploying a more granular govern, identify, protect, detect, respond and recover loop. This includes combining foundational practices with ITDR. Govern to ensure that ITDR activities are effective and evolve with your organization. Identify resources and threats in your environment to ensure your ITDR program meets current requirements. Protect root IAM administrator account posture to anchor ITDR. Detect indications of abnormal activity quickly and accurately before material damage is done. The state of the art is sub second. Respond to incidents with playbooks and appropriate levels of automation, both to block the activity and to adjust policies and configuration posture to avoid recurrences. Recover quickly in the rare circumstances when this is necessary.
Obstacles
- ITDR requires coordination between IAM and security functions, which can be challenging for both.
- ITDR effectiveness is dependent on the integration architecture, data and signals ingested.
- IAM hygiene, detection and response best practices are often immature. Organizations tend to operate identity tools in silos, which prevents them from sharing risk signals and prioritizing overall hygiene activities.
- Multiple capabilities are required to fully protect IAM. These include closely monitoring configuration changes to root IAM administrator accounts, detecting when IAM tools are compromised, enabling rapid investigations and efficient remediation and reverting quickly to a known good state. This can require multiple vendors.
- There are many different tools with ITDR capabilities that vary widely in their strengths. Therefore, organizations may need to choose multiple tools to achieve full coverage.
User Recommendations
- Include ITDR in your formal SecOps and IAM programs. Prioritize securing IAM with tools to discover and monitor identity attack techniques, detect when attacks are occurring and remediate quickly.
- Look for capabilities to provide visibility across your IAM ecosystem, prioritize remediation efforts and demonstrate (over time) a reduction in the attack surface. Use multiple tools to provide all needed ITDR capabilities.
- Use emerging IAM standards to enable your IAM infrastructure to operate as an identity fabric that shares risk signals. Direct ITDR alerts to a security operations center or identity alert response team, or use a managed service.
- Mature organizations can use the MITRE ATT&CK framework to correlate ITDR techniques with attack scenarios to ensure that at least well-known attack vectors are addressed.
- To achieve your desired security risk posture, assess your entire set of IAM controls and implement complementary controls to IDTR as needed.
Sample Vendors
Cisco; CrowdStrike; Delinea (Authomize); Gurucul; Microsoft; Netwrix; Proofpoint; Semperis; SentinelOne; Silverfort
Gartner Recommended Reading
Climbing the Slope
Offensive Security Programs
Analysis By: Dhivya Poole, Mitchell Schneider, Jonathan Nunez
Benefit Rating: Moderate
Market Penetration: 20% to 50% of target audience
Maturity: Mature mainstream
Definition:
Offensive security programs are a proactive cybersecurity practice that use repeatable and consistent processes to simulate cyberattack techniques and identify security weaknesses. This approach uses the same tools and techniques as cybercriminals to boost security resilience by validating threat exposure and stress-testing systems and processes. Key methods include penetration testing, red teaming and bug bounties, all designed to reveal potential security gaps comprehensively.
Why This Is Important
To stay ahead of evolving threats, cybersecurity leaders must adopt an attacker’s view. Offensive security is crucial for simulating cyberattacks, identifying weaknesses and proactively evaluating defenses. These programs provide the “how” by outlining actionable steps to assess exploitability before threat actors cause financial loss or reputational damage. This approach enables organizations to fix weaknesses, enhance security, build trust and refine incident response.
Business Impact
Running an offensive security program can significantly benefit businesses by improving their overall cybersecurity posture, reducing severity risk and enhancing their ability to respond to cyberthreats. Offensive security raises awareness across the organization, fosters a robust security culture and delivers actionable reports with remediation recommendations, helping enterprises safeguard their environments more effectively.
Drivers
The demand for offensive security is driven by several key factors:
- Proactive identification and validation of threat exposures to prevent costly breaches and minimize financial, reputational and operational losses.
- Strategic investment that offers clear insights into high-risk and high-impact threat exposures, improves operational efficiency and demonstrates the ROI of proactive measures.
- Visibility into the business impact of cyber risk, enabling informed decision making and prioritization of initiatives that reduce impactful threats.
- Routine security testing to maintain compliance with regulations such as HIPAA and PCI DSS, helping organizations avoid penalties and strengthen consumer trust and brand reputation.
- Demonstrated commitment to resilience that supports strategic decision making and helps leadership prioritize resources and align efforts with regulatory expectations such as DORA and NIS2.
- Support for growth and operational excellence by embedding resilience into organizational culture and enabling secure business objectives.
Obstacles
- Testers face an expanding attack surface driven by cloud computing, IoT and emerging areas such as AI, making it harder to identify and secure all potential entry points.
- Offensive security teams must be proficient in a broad range of assessments, each requiring specific skills, techniques and knowledge, making it difficult to maintain expertise across all domains.
- Communicating technical findings in an actionable manner can be challenging, especially when knowledge gaps exist between testers and their audiences.
- Testers must comply with an increasing number of strict security standards, regulations and ethical guidelines, which can be resource-intensive and time-consuming.
- Assessments often take place in dynamic environments where target systems, security controls and configurations change rapidly, requiring testers to remain agile and adapt in real time.
- Rapidly advancing adversarial tactics make it difficult for offensive security practitioners to keep pace.
User Recommendations
An offensive security program should:
- Define scope: Prioritize resources on critical testing and attack surfaces.
- Balance teams: Use internal teams for routine tests (e.g., penetration testing) and external experts for specialized tasks (e.g., red teaming) to manage costs and ensure unbiased compliance.
- Implement use-case-based testing: Use penetration tests for broad coverage, bug bounties for in-depth vulnerability discovery and red teaming to simulate advanced threats and strengthen incident response.
- Develop reporting processes: Use tested and governed methods to convert technical findings into actionable insights, increasing organizational value and accelerating risk‑reduction approvals.
- Utilize frameworks and tools: Employ frameworks and tools such as the Cyber Kill Chain, MITRE ATT&CK and AEV with regular updates and audits to maintain efficient compliance.
- Integrate threat intelligence: Invest in capabilities that anticipate advanced adversary techniques.
Gartner Recommended Reading
Co-Managed Threat Detection Services
Analysis By: Pete Shoard
Benefit Rating: Moderate
Market Penetration: 20% to 50% of target audience
Maturity: Mature mainstream
Definition:
Co-managed threat detection services are delivered remotely. These services can manage an individual or an ecosystem of client-owned SIEM, EDR, identity threat detection and response (ITDR) or other threat detection, investigation and response (TDIR)-capable products. These products provide an operational platform for the delivery of threat identification and incident investigations by both the provider and the end-user SOC team overseeing mitigating response actions to security incidents.
Why This Is Important
Co-management offers buyers the opportunity to increase their internal security skill sets while still having the support of an experienced service provider. This approach increases the speed at which cybersecurity maturity can be improved and offers flexibility to build capabilities and mature internal staff in ways not available via a more “fully managed” approach. This approach helps to create a distinction between outcome-driven services and technology-driven detection and response services.
Business Impact
Organizations make purchases of TDIR-capable products such as SIEM, but often struggle to operate them effectively. Detection and response is critical to the success of any security strategy. Midsecurity and midmaturity buyers recognize broader threat detection needs and are adopting more tools. Co-managed services provide security operations center (SOC) maturity in areas like creation/tuning of detection content and lightweight investigation.
Drivers
- Buyers require the ability to continuously build and update detection content and reporting within their TDIR-capable technologies because they have non-security-related use cases that require them to own the infrastructure. These use cases include being able to access reports, create custom rules or dashboards, and conduct HR or legal investigations. Using these technologies requires expert knowledge of the threat landscape and other data manipulation skills, which are hard to acquire and retain.
- Specifically, the complexity of TDIR-capable technologies and content development requirements means that many buyers do not have the in-house expertise to build, maintain and evolve in line with their threat visibility objectives.
- Compared to turnkey services, such as managed detection and response (MDR), co-managed threat detection provides buyers greater flexibility and access to configure a dedicated detection and response capability. As an organization’s security maturity increases and internal skill sets grow, co-managed service options often become the preferred follow-up pathway or an add-on capability to grow beyond MDR limitations.
- Buyers may already have a service provider or system integrator; co-managed threat detection services often coexist with IT outsourcing and cybersecurity consulting providers operationally supporting the maintenance, health and software updates for TDIR-capable technologies.
- Many buyers have adopted, or plan to adopt, SaaS-related TDIR offerings as part of a bundle of capabilities with broader infrastructure investments and will be migrating from legacy on-premises technologies or alternative SaaS providers because of this. The associated threat detection requirements of these migrations can be complex and may benefit from the support of experienced managed providers.
Obstacles
- Aligning long-term SOC team development goals with a co-managed service is difficult. While co-management provides easy acquisition of SOC skills, long-term planning for internal development of staff requires forethought and a defined roadmap.
- Co-managed threat detection services typically offer only a first line of triage and investigation and not the full process of managing security incidents. No matter how much incident management support a provider offers, there is always some level of response that is the responsibility of the customer.
- Owning your TDIR-capable solution may be a preference, but can take a significant amount of time to deploy and get operational. Co-managed services rarely provide a fast turnaround related to deployment and value realization.
- The complexity of adopting an already deployed solution can increase cost. Planning for the process of changing providers or asking providers to adopt existing technology is essential to avoid wasting time and budget.
User Recommendations
- Identify details of use cases early to establish requirements for log data, TDIR and any compliance reporting needs to ensure the project costs are well-controlled.
- Consider the impact on, and plan to sustain, long-term SOC skills and training requirements when using co-managed services.
- Outline your requirements aligned to the maintenance and design of detection and reporting content specifically. TDIR-capable platforms can be health monitored and the underlying system maintenance carried out by noncybersecurity providers. Explore other, more cost-effective technology management services if this is the primary goal of the procurement.
- Build a RACI when using infrastructure and co-managed threat detection providers, specifying clear and appropriate escalation paths and responsibility definitions. Include details to resolve potential conflicts in incident resolution responsibilities.
Sample Vendors
AT&T; BlueVoyant; Bridewell; IBM; Kroll; NCC Group; Optiv; Stratejm (Bell Canada)
Gartner Recommended Reading
NDR
Analysis By: Thomas Lintemuth
Benefit Rating: High
Market Penetration: 20% to 50% of target audience
Maturity: Early mainstream
Definition:
Network detection and response (NDR) products continuously monitor network traffic to detect anomalies and threats using behavioral analytics. NDR products include automated responses via integration with third-party cybersecurity products and, less commonly, directly. NDR is offered with hardware and software sensors. Management and orchestration consoles can be software or SaaS.
Why This Is Important
NDR identifies all devices communicating on the network as well as network activity to/from these devices, baselines typical activity, and detects abnormal activity, all without the need for signature-based controls or agents. NDR detects lateral movement of attackers, command and control activity, and data exfiltration. Its placement on the network means NDR catches what other controls miss. It becomes the source of truth for the network.
Business Impact
NDR delivers business value by proactively mitigating risk through visibility into the network attack surface. AI-based machine learning algorithms detect incidents missed by signature-based detection techniques. Automated response capabilities make incident responders more effective. NDR facilitates faster, more thorough incident investigations, combining threat hunting and alert contextualization with drill-down capabilities to enhance organizational resilience and safeguard critical assets.
Drivers
- Detect breach activity: NDR complements traditional preventative controls by detecting incidents based on deviations from baseline. This enables security teams to investigate breaches without relying on manual controls.
- Contextualize alerts: Security operations center (SOC) analysts are inundated with high volumes of events to the security information and event management (SIEM) platform. NDR provides contextual detail for devices that are involved in an incident.
- Low risk, high reward: Deploying NDR products is a low-risk project, because the sensors are deployed out of band. They don’t inject a point of failure or a “speed bump” for network traffic. Enterprises that implement NDR products as a proof of concept (POC) often report high degrees of satisfaction, because the tools provide much-needed visibility into network traffic and enable even small teams to spot anomalies.
- Monitor hybrid, CPS, and cloud traffic: A key functionality for NDR is the ability to monitor network traffic wherever it may be, including in on-premises, IaaS, SaaS, and cyber-physical system (CPS) networks. Organizations use NDR to avoid creating gaps in their ability to monitor interactions among all their systems, wherever those interactions may be.
- Eliminate visibility gaps: NDR records every network packet that crosses its sensors. Properly deployed and scoped NDR generates a list of all assets that are communicating on the network.
- Passive detection: NDR is deployed out of band so attackers have little ability to know they are being observed. This also makes it nearly impossible, unlike endpoint detection and response (EDR), to disable their monitoring.
- Crypto agility and post-quantum readiness: The transition toward post-quantum cryptography has demonstrated that organizations have limited records of the presence and location of algorithms used in their systems. NDR is a powerful tool in assisting organizations building a cryptography inventory.
Obstacles
- NDR must demonstrate value outside of tracking the number of incidents that prompt alerts, as it will lose that metric every time to EDR. NDR must clearly contribute to improved posture improvement, compliance, and operational efficiency.
- NDR has not developed a solid reputation for automated response. Response capabilities should be optimized so analysts have “1-click” actioning of enforcements across EDR, network access control (NAC), secure access service edge (SASE) and firewall platforms.
- NDR products will become irrelevant if they do not adapt to identify, risk score and control AI-driven applications, automation, and infrastructure.
- NDR products require tuning to the environment in which they are deployed. This necessitates ongoing human resources to achieve maximum benefit.
- NDR faces commoditization unless it can demonstrate value beyond integrated platform offerings that may claim NDR-like capabilities.
User Recommendations
- Develop a strong understanding of the overall traffic patterns to support proper implementation and gain maximum value from NDR.
- Plan sensor types and deployment locations so that the most relevant network traffic can be analyzed. Proper positioning of the NDR sensors is critically important to achieve complete visibility and control the cost of the deployment.
- Tune out false positives in the implementation phase — false positives may be triggered by vulnerability scanners, shadow IT applications and other factors that may be specific to your environment.
- Ensure dedicated resources are identified and allocated for getting the optimum value from NDR investments
- Plan for ongoing tuning as new detection models are deployed from the vendor.
- Select network sensors with the appropriate throughput capacity to negate overloaded ports or dropped packets.
Sample Vendors
Arista Networks, Corelight; Darktrace; ExtraHop; Gatewatcher; NetWitness; Stamus Networks; Trellix; Vectra AI
Gartner Recommended Reading
MDR Services
Analysis By: Andrew Davies
Benefit Rating: High
Market Penetration: More than 50% of target audience
Maturity: Mature mainstream
Definition:
Managed detection and response (MDR) services provide customers with remotely delivered, human-led, modern security operations center (SOC) functions. These allow organizations to rapidly detect, analyze, investigate and actively respond through threat disruption and containment. MDR providers offer a turnkey experience using a technology stack that covers endpoint, network, logs and cloud. This telemetry is analyzed by the provider’s experts, skilled in threat hunting and incident management.
Why This Is Important
The cyberthreat landscape is in a constant state of change, and the complexity of attacks against organizations is escalating faster than ever before with the use of AI-driven attacks. Given the changes in the threat landscape, scaling your security operations practice is vital. MDR services provide an effective means of scaling your workforce for security operations. Most organizations lack the resources, budget or appetite to build and run their own 24/7 SOC function, required to help them protect and defend against attacks that increasingly impact and cause more damage to operations. MDR services enable organizations to mature their threat detection and response coverage.
Business Impact
MDR services combine people, process and technology, translating security issues into business-focused risks, impacts and outcomes, reducing complexity and allowing increased security maturity through turnkey adoption. Organizations that have not invested in threat detection and response capabilities are at greater risk from the impact of cyberincidents. The challenge of finding, acquiring and retaining the necessary expertise and threat detection, investigation, and response products makes building an adequate internal capability onerous.
Drivers
- Buyers require fast adoption of mature capabilities that take a long time to build or buy, or are prohibitively expensive to operate. MDR delivers a turnkey solution for those wishing to quickly build and maintain threat detection investigation and response (TDIR) capability.
- MDR services enable organizations to focus on outcome-driven responses as they provide the expertise to interpret and deliver against a set of requirements. Ultimately, this delivers relevant and actionable business outcomes.
- MDR providers can help you extend your TDIR capabilities quickly to a broader range of new environments than is typically possible with smaller internal-only teams.
- MDR providers allow for remotely delivered mitigative response actions, enabling buyers to respond and alleviate issues faster and with less impact to their business, although the level of autonomy granted to vendors varies according to the trust level. With the improved access to MDR service providers’ portals, clients can validate the response for some scenarios, and possibly execute it.
- Many MDR providers are expanding their offering beyond TDIR to include exposure management. This is a driver for MDR when buyers seek to better harmonize their TDIR practice with their exposure management practice.
Obstacles
- The vastly different approaches by providers to offer MDR services often cause buyers to question how to strategically engage a provider.
- Technology vendors with threat detection, investigation and response-capable solutions offer similarly named, but often more light-touch, overlay services, such as managed endpoint detection and response (EDR) and co-managed security information and event management (SIEM). This increases buyers’ confusion.
- Misaligned expectations and a lack of effective internal processes to consume MDR outputs lead to performance issues with MDR service providers and failed engagements.
- Not assigning staff as the point of contact to the service can cause challenges. If not defined effectively, segmentation of operational responsibilities and building effective response processes usually leads to dissatisfaction with services.
- New AI-driven solutions promising to initiate measures for active containment or disruption of a threat or an exposure are in direct competition with MDR providers
User Recommendations
- Focus on outcomes, not technologies. Organizations underinvested in technologies capable of TDIR, such as EDR, should favor contract vendors that provide the tools and deliver the desired outcomes.
- Ensure that your MDR provider supports additional security services as your security maturity improves and business-driven risks change, so you don’t need to add additional vendors at a later time. These services include exposure management and continuous threat exposure management (CTEM).
- Assess if the MDR service deliverables focus on completeness, actionability and options for service provider follow-up incident response and threat hunting activity.
- Examine co-managed security monitoring service offerings when adjacent capabilities are required to support the management and expansion of your own TDIR investments, such as EDR and SIEM.
- Buy MDR services that offer a migration path to more self-service in the future. Looking for vendors that have open communication channels with analysts and delivery teams can support that goal.
- Less mature organizations with lower security maturity can find quicker time to value with technology-driven MDR services.
Sample Vendors
Accenture; Arctic Wolf Networks; Critical Start; CrowdStrike; eSentire; Expel; Rapid7; ReliaQuest; Sophos
Gartner Recommended Reading
Cyberthreat Intelligence Data & Analytics
Analysis By: Jonathan Nunez
Benefit Rating: High
Market Penetration: More than 50% of target audience
Maturity: Mature mainstream
Definition:
Cyberthreat intelligence data and analytics (CTI D&A) solutions provide actionable insights and context on threats, threat actors, and related risks. They help organizations understand adversary identities, motives, behaviors, and TTPs to improve decision making and strengthen security. CTI D&A is a core data source that supports the broader unified cyber risk intelligence framework.
Why This Is Important
Cybersecurity leaders must understand their organization’s threat landscape and ensure security controls are continuously updated with relevant, contextualized intelligence. CTI D&A enables ongoing visibility into emerging threats and delivers timely, accurate, and actionable insights that support risk‑informed decisions before, during, and after an attack.
Business Impact
- Reduces material business risk by enabling earlier detection of adversary activity, minimizing operational disruption, financial loss, and reputational damage.
- Strengthens decision making across security and executive teams through contextualized, timely insight into threats and exposures.
- Enhances enterprisewide resilience by turning intelligence into actionable outputs that drive security control validation and accelerate response.
Drivers
- External threat signal consolidation: Major security providers are integrating or acquiring TI, DRPS, and EASM capabilities to create unified platforms that correlate external exposures, adversary behavior and brand abuse to reduce fragmentation, strengthen attribution, and expand enterprisewide operational impact.
- Demand for deep curation and contextualization: Rising intelligence volumes, fragmented threat data, and globally distributed adversary activity are driving organizations to require curated, sector‑aware, and campaign‑level insights. Mature buyers now expect intelligence that distills massive telemetry into clear, decision‑ready outputs aligned to their industry, geography, and business priorities moving well beyond IOC‑level feeds toward contextual analysis tied to adversary intent, behaviors, and monetization patterns.
- Shift toward automated response: Organizations want actionable intelligence that directly fuels detection engineering, automates rule generation, powers enforcement actions, and executes domain and content takedowns, closing the loop between insight and defense. Intelligence is no longer judged by volume or breadth, but by the measurable impact it has on reducing exposure and accelerating response.
- AI productivity and insight: Multiagent and LLM‑driven workflows are transforming how intelligence is collected, correlated, summarized, and operationalized. AI enhances analyst throughput, accelerates investigation, reduces noise, and enables adaptive response patterns across large, heterogeneous environments, setting a new baseline expectation for automation, accuracy, and scalability in CTI programs.
Obstacles
- Inconsistent measurement and unclear ROI: Without operational metrics or program efficacy measures, CTI teams struggle to justify investment, leaving budgets vulnerable.
- Market saturation and indistinguishable offerings: With over 200 vendors marketing CTI-related capabilities, the market has become heavily saturated, leading to overlaps in features, positioning and claims. This creates confusion, slow evaluations, and causes buyers without rigorous requirements to over-, or under-, invest.
- Shortage of analyst capacity and specialized skills: Effective CTI requires both technology and human expertise; many organizations underresource analyst roles or lack the expertise to operationalize intelligence.
User Recommendations
- Establish and govern priority intelligence requirements (PIRs) to anchor use cases, reduce vendor noise, shape evaluation criteria, and prevent overpurchasing or misalignment with business needs.
- Adopt operational delivery metrics including detection coverage, false-positive reduction, response acceleration, control optimization and exposure prioritization to quantify CTI value and support defensible program maturity.
- Prioritize platforms that “close the loop”; choose CTI solutions that generate detection rules, automate enforcement actions, execute takedowns, validate efficacy, and continuously tune outputs.
- Leverage managed CTI or MDR providers to accelerate time to value, particularly for organizations lacking internal resources or skill sets.
- Integrate CTI into the wider security program to ensure that intelligence directly informs prioritization efforts and real-time decision making.
Sample Vendors
CrowdStrike; Duskrise; Filigran; Flashpoint; Google; Intel 471; Recorded Future (Mastercard); Silent Push; ThreatBook; VulnCheck
Gartner Recommended Reading
Cyberthreat Intelligence Management Systems
Analysis By: Jaime Anderson
Benefit Rating: High
Market Penetration: More than 50% of target audience
Maturity: Mature mainstream
Definition:
Cyberthreat intelligence management systems (CTIMS) are specialized systems designed to ingest, analyze, manage, and disseminate information about current and emerging cyberthreats. Their primary purpose is to help organizations proactively manage the identification, assessment, and response to potential cyber risks.
Why This Is Important
Cyberthreat intelligence management systems are vital for cybersecurity because they centralize and provide the tools to analyze threat data, automate detection and response, provide context for alerts, establish threat analysis workspaces and integrate with other tools (e.g., SIEM and EDR). This enables organizations to stay ahead of evolving threats, assess threat data sources, respond faster to incidents, track intelligence research and strengthen their overall security posture.
Business Impact
- Vital for any organization: Reduces breach risk by enabling faster detection, prioritization and response.
- Increase SOC efficiency: Streamlines threat data collection, manages requirements, reduces manual analysis, and speeds up response to support business resilience.
- Enhance regulatory compliance: Active monitoring aids in meeting regulations, improving audit readiness, and ensuring compliance.
Drivers
- Evolving threat landscape: The rise of sophisticated cyberattacks remains the strongest market accelerator. The increased activity from APTs, digital espionage campaigns, geopolitical tensions, nation-state activity and the growing complexity of attacks are key forces behind the shift for enterprises to adopt CTIMS.
- Threat data aggregation: Organizations are increasingly seeking solutions that can centralize threat intelligence data from multiple internal and external sources that analyze, score, and correlate indicators of compromise (IOCs), enabling a more comprehensive and actionable view of the threat landscape.
- Threat analysis and correlation: Organizations need investigation workbenches to track threats, document findings, and build a comprehensive understanding of adversary tactics, techniques, and procedures within CTIMS for more effective and sustained threat detection and coordinated defense.
- Integration and automation needs: The need for automation has increased demand for CTIMS capable of integrating with various internal security platforms and intelligence providers to make threat intelligence actionable for proactive detection and incident response.
- Reporting and dashboards: Organizations need systems that can deliver real-time visibility into threat landscape, trends, and response activities that can be curated specifically for their organization.
- Regulatory pressure and compliance mandates: Global frameworks like GDPR, HIPAA, and NIST increasingly require continuous monitoring, incident readiness, and demonstrable threat management capabilities which significantly influence CTIMS adoption, as organizations must prove resilience and auditability.
- Adoption of AI‑driven analytics, automation and predictive capabilities: Organizations are rapidly increasing adoption of AI‑based security analytics, behavioral monitoring, and automated threat detection. These technologies improve alert accuracy, reduce analyst workload, and accelerate response.
Obstacles
- Budget constraints: Economic downturns or budget cuts may slow adoption, as organizations prioritize core security tools.
- Integration complexity: If these systems fail to integrate smoothly with existing infrastructure, organizations may pause or reverse adoption.
- Overhyped expectations: If these systems fail to deliver promised results organizations may scale back investments.
- Skills shortage: Many organizations lack skilled threat intelligence analysts capable of interpreting and operationalizing intelligence effectively.
- AI and automation concerns: Organizations struggle with AI model transparency, bias, and governance challenges when implementing automated CTIMS workflows.
- Difficulty operationalizing intelligence: Many teams lack mature processes to turn raw intel into prioritized action, hindering full CTIMS value.
User Recommendations
- Deployment alignment: Select a deployment method that aligns with organizational objectives and security requirements to maintain intelligence standards and strengthen your security posture.
- Integration and automation: Prioritize systems with robust integration (native and API) and automation capabilities to connect seamlessly with existing tools and workflows, enhancing the efficiency of threat mitigation.
- Investigation workflows: Ensure the system provides investigation workflows and threat modeling so teams can track, document, and manage intelligence activities while proactively identifying and assessing risks.
- Metric development: Track return on investment using KPIs such as mean time to detect, actionable threats reported, reduction of false positives, and completion of priority intelligence requirements.
Sample Vendors
Analyst1; Anomali; Cyware; Dataminr; EclecticIQ; Filigran; Securonix
Gartner Recommended Reading
Entering the Plateau
Security Information and Event Management Platforms
Analysis By: Eric Ahlm, Andrew Davies
Benefit Rating: Moderate
Market Penetration: More than 50% of target audience
Maturity: Mature mainstream
Definition:
SIEM platforms allow security operations teams to perform threat detection and investigation, and to orchestrate response actions. They are extensible and offer a high degree of customization to organizations with unique requirements for organization-specific detections, operational dashboards and workflows, and reporting. The open nature of SIEM platforms makes them ideal for clients using a wide variety of third-party controls and data sources to perform TDIR functions.
Why This Is Important
Aggregating and normalizing data from various environments to centralize visibility is a core element of effective security programs. Security information and event management (SIEM) acts as a central tool supporting an organization’s ability to identify, prioritize and investigate security events of interest, execute response actions, and report on current and historical security events.
Business Impact
SIEM solutions can impact the business by:
- Allowing organizations to identify and respond to critical security events earlier in their life cycle, in order to reduce risk.
- Creating overall situational awareness for security issues and events, providing an efficient and trusted system of record, which can be used for operational security and compliance reporting.
- Creating advanced and highly extensible threat-monitoring objectives more commonly associated with business risks.
Drivers
- The SIEM market is undergoing redefinition to clarify its key applications, a change driven by evolving buyer demands for various threat detection and incident response (TDIR) approaches.
- The SIEM market (now called SIEM platforms) continues to mature classic SIEM capabilities for buyers that want extensible platforms for TDIR.
- Instead of continuing to use SIEM platforms, buyers may opt to migrate to competing TDIR solutions, such as security operations (SecOps) platforms or security data lakes (SDLs).
- Central monitoring of threats, as reported by multiple sources, is a primary driver for SIEM. Such platforms offer a central place to monitor and investigate security alerts, as well as to support contextual information required to make an alert actionable.
- A SIEM solution converts raw alert data into actionable intelligence by applying the most effective analysis method for the specific monitoring objective.
- Organizations need to expand detection workflow to include response activities, with capabilities such as security orchestration, automation and response.
- SaaS SIEM (cloud-based/native) solutions transfer the platform and infrastructure maintenance to the vendor and allow for more predictable linear budgeting for growth.
Obstacles
- Getting a SIEM solution to perform well against detecting attacks requires dedication and sufficient staffing. Undermanaged SIEM solutions continue to plague many organizations.
- SIEM budgets and resources are constrained; however, the types of threats the platform could potentially monitor are endless. As such, deciding what to monitor with the SIEM resources an organization has represents concession engineering at its best.
- The complexity of operating a SIEM solution and all the dependencies required for TDIR performance is an obstacle for smaller organizations, which may choose to consider alternative solutions.
- SIEM architecture at a large scale may require supplemental technologies that can add to the complexity and cost of the solution. This can cause increased buyer confusion or make justifying complete SIEM more challenging.
User Recommendations
- Based on your requirements for TDIR, evaluate whether alternate solutions such as SecOps platforms or SDLs can provide better value for your organization than SIEM platforms.
- Incorporate a learning period of alerting to determine how best to operationalize detection and response, as planning operational support for alert pipeline management without knowing how many alerts and how much work is required can be difficult.
- Ensure your cloud-based/native SIEM solution is aware of the underlying infrastructure it monitors. A SIEM solution must understand the nuances of its native environment, such as AWS, GCP or Microsoft Azure.
Sample Vendors
Cisco (Splunk); Elastic; Exabeam (LogRhythm); Google; Gurucul; Microsoft; Palo Alto Networks; Securonix; Sumo Logic
Gartner Recommended Reading
Endpoint Detection and Response
Analysis By: Franz Hinner, Eric Grenier, Satarupa Patnaik
Benefit Rating: High
Market Penetration: More than 50% of target audience
Maturity: Mature mainstream
Definition:
Endpoint detection and response (EDR) continuously monitors endpoints for unusual behavior to detect attacks that evade preventive controls, using high-fidelity behavioral heuristics and identity-aware telemetry analytics to enable rapid, manual or automated responses that reduce mean time to detect (MTTD) and strengthen defense-in-depth strategies.
Why This Is Important
Preventive controls miss many advanced and identity-linked threats; as hybrid work expands, EDR gives CISOs deep endpoint visibility and “black box” forensics to accelerate detection, automate containment, and meet tightening incident response and cyber insurance expectations.
Business Impact
- Protect AI assets: Cut GenAI data leakage and prompt-driven abuse detected on endpoints.
- Consolidate hybrid security: Shift to a workspace security platform (WSP) model that unifies protection for remote devices, apps and identities.
- Automate cyber resilience: Use AI-driven, self-healing playbooks to cut ransomware recovery costs and downtime.
- Ensure regulatory compliance: Monitor AI and workspace data to help meet GDPR, HIPAA and cyber insurance mandates.
Drivers
- Convergence into WSPs: Drive CISOs to favor EDR offerings that integrate cleanly into WSP roadmaps and expose endpoint telemetry as a core signal alongside device, app and identity controls.
- AI usage guardrailing: Increase demand for EDR tools that share endpoint and process telemetry with emerging AI security controls, enabling better GenAI acceptable-use enforcement and reduced data leakage risk.
- Adversarial AI attacks: Boost investment in EDR that can detect AI-driven automated exploits and suspicious process behavior and that can feed runtime AI defense mechanisms with high-fidelity endpoint context.
- Expansion of hybrid work: Accelerate adoption of cloud-native EDR architectures that provide continuous, real-time monitoring and response across remote and unmanaged endpoints used by hybrid workers.
- Identity-based attacks: Raise priority for EDR platforms that integrate tightly with identity threat detection and response (ITDR) to correlate endpoint and identity events, improve risk scoring and orchestrate joint remediation.
Obstacles
- EDR role in workspace defense: Limit EDR to one component of workspace defense, forcing CISOs to also invest in ITDR, CTEM and ASCA to cover identity, exposure and cloud-native attack paths.
- Competition from AI usage control: Expose EDR to encroachment from SSE and stand-alone AI usage control tools that promise simpler GenAI risk controls than evolving EDR platforms.
- Operational skills and complexity: Restrict EDR value when buyers lack staff to threat hunt, tune detections and run playbooks, pushing them toward EDR-lite options such as baseline endpoint protection plans.
User Recommendations
- Adopt a workspace-centric posture: Rationalize overlapping endpoint tools and favor EDR offerings that integrate cleanly into your broader WSP strategy for devices, applications and data.
- Integrate AI runtime guardrails: Pair EDR with dedicated AI security controls to monitor live AI interactions, using EDR telemetry to help detect prompt injection and unauthorized exposure of sensitive data.
- Formalize AI incident response: Extend incident response playbooks to cover AI-related misuse and model abuse, explicitly defining when and how EDR data and response actions support overall AI incident handling.
- Standardize on unified agents: Prioritize EDR and WSP-aligned solutions that use a unified agent and centralized console to reduce endpoint performance impact and maintain consistent protection for hybrid workers.
Sample Vendors
CrowdStrike; Microsoft; Palo Alto Networks; SentinelOne; Sophos; Trend Micro
Gartner Recommended Reading
Appendixes
See the previous Hype Cycle: Hype Cycle for Security Operations, 2025.
Hype Cycle Phases, Benefit Ratings and Maturity Levels
Hype Cycle Phases
Phase | Definition |
Innovation Trigger | A breakthrough, public demonstration, product launch or other event generates significant media and industry interest. |
Peak of Inflated Expectations | During this phase of overenthusiasm and unrealistic projections, a flurry of well-publicized activity by technology leaders results in some successes, but more failures, as the innovation is pushed to its limits. The only enterprises making money are conference organizers and content publishers. |
Trough of Disillusionment | Because the innovation does not live up to its overinflated expectations, it rapidly becomes unfashionable. Media interest wanes, except for a few cautionary tales. |
Slope of Enlightenment | Focused experimentation and solid hard work by an increasingly diverse range of organizations lead to a true understanding of the innovation’s applicability, risks and benefits. Commercial off-the-shelf methodologies and tools ease the development process. |
Plateau of Productivity | The real-world benefits of the innovation are demonstrated and accepted. Tools and methodologies are increasingly stable as they enter their second and third generations. Growing numbers of organizations feel comfortable with the reduced level of risk; the rapid growth phase of adoption begins. Approximately 20% of the technology’s target audience has adopted or is adopting the technology as it enters this phase. |
Years to Mainstream Adoption | The time required for the innovation to reach the Plateau of Productivity. |
Source: Gartner
Benefit Ratings
Benefit Rating | Definition |
Transformational | Enables new ways of doing business across industries that will result in major shifts in industry dynamics |
High | Enables new ways of performing horizontal or vertical processes that will result in significantly increased revenue or cost savings for an enterprise |
Moderate | Provides incremental improvements to established processes that will result in increased revenue or cost savings for an enterprise |
Low | Slightly improves processes (for example, improved user experience) that will be difficult to translate into increased revenue or cost savings |
Source: Gartner
Maturity Levels
Maturity Levels | Status | Products/Vendors |
Embryonic | In labs | None |
Emerging | Commercialization by vendors Pilots and deployments by industry leaders | First generation High price Much customization |
Adolescent | Maturing technology capabilities and process understanding Uptake beyond early adopters | Second generation Less customization |
Early mainstream | Proven technology Vendors, technology and adoption rapidly evolving | Third generation More out-of-box methodologies |
Mature mainstream | Robust technology Not much evolution in vendors or technology | Several dominant vendors |
Legacy | Not appropriate for new developments Cost of migration constrains replacement | Maintenance revenue focus |
Obsolete | Rarely used | Used/resale market only |
Source: Gartner
2025 Gartner Cybersecurity Innovations in AI Risk Management and Use Survey. This survey was conducted to understand how organizations are managing the cybersecurity risks of generative AI (GenAI) and AI techniques that support it. The research was conducted online from 21 March through 9 May 2025 among 302 cybersecurity leaders in the North America (n = 181), EMEA (n = 71) and Asia/Pacific (n = 50) regions. Qualifying organizations reported enterprisewide revenue of at least $250 million or equivalent for fiscal 2024 and were senior cybersecurity management involved in activities related to AI cybersecurity risk management within their organization. Disclaimer: The results of this survey do not represent global findings or the market as a whole, but reflect the sentiments of the respondents and companies surveyed.
1 Assessing Claude Mythos Preview’s Cybersecurity Capabilities, red.anthropic.com.