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What Is Agentic Runtime Security?

Reporting by Mitiga ResearchRead the original at mitiga.io

Executive Summary

Agentic Runtime Security shifts security focus from endpoint protection to the broader infrastructure by monitoring cloud, SaaS, identity, AI, and third-party services. This approach is necessitated because the primary assets have moved beyond traditional endpoints, which previously served as the center of gravity for security operations. Agentic Runtime Security differs fundamentally from Endpoint Detection and Response (EDR) by focusing on log-based detection across all platforms rather than relying on an agent within a workload. It addresses emerging threats posed by non-human identities, such as AI agents and chatbots, which use valid credentials to move laterally. The concept emphasizes that the necessary data foundation for defense is the long-horizon, forensic-grade data lake emitted by all services, not just endpoint telemetry.

Facts Only

* Agentic Runtime Security involves runtime detection and response across cloud, SaaS, identity, AI, and third-party services.
* Endpoint Detection and Response (EDR) protects endpoints, while Agentic Runtime Security protects everything else.
* The signal for Agentic Runtime Security comes from audit trails emitted by platforms, not an agent inside the workload.
* Agentic Runtime Security detects behavioral signals like compromised credentials and lateral movement as they happen.
* Response actions include revoking sessions or blocking API calls mid-attack.
* Median dwell time increased to 14 days, while average breach identification still takes 241 days.
* The modern attack surface includes SaaS, cloud services, identity providers, AI, and third-party connections.
* Non-human identities, such as chatbots and autonomous agents, are included in coverage.
* The three pillars of AI Detection and Response (AIDR) are Defend with AI, Defend from AI, and Defend the AI.
* Defense depends on a forensic-grade data layer across all domains.

Full Take

The narrative presents a clear structural shift: security must follow distributed services rather than endpoint reliance. The movement from EDR to Agentic Runtime Security reflects a necessary evolution driven by the speed of modern attack execution, where dwell time is measured in seconds but defense remains measured in months. The convergence of AI-enabled attacks with the proliferation of shadow SaaS and non-human identities highlights an architectural gap: existing tools are optimized for a centralized device model, creating blind spots across the cloud service fabric. The claim that visibility on paper is not defense in runtime forces a confrontation between posture management (knowing a door is unlocked) and runtime response (stopping entry), suggesting that true resilience requires bridging the gap between static posture assessment and dynamic, real-time control over distributed access and behavior. The implication for agency lies in recognizing that defending the system requires prioritizing data integrity across complex interactions rather than segmenting defense by location. What assumptions about centralized control and endpoint primacy are most vulnerable to being exploited in this new distributed reality?

From the original · Mitiga Research

Agentic Runtime Security is runtime detection and response across cloud, SaaS, identity, AI, and third-party services — the infrastructure endpoint tools can't see. It anticipates, detects, interrupts, and stops active attacks before they reach the business.

Read the full story at mitiga.io

Sentinel — Human

Confidence

The text reads like expert thought leadership synthesizing current security trends; it is highly opinionated in its framing but grounded in specific data points rather than pure fabrication.

Signals Detected

Sentence length variance and flow exhibit human variation, despite sophisticated terminology.

The text maintains a strong, focused argumentative thread consistent with expert opinion rather than neutral reporting.

Use of specific, varied statistics (Mandiant 2026, IBM 2025) points toward sourced synthesis rather than verbatim scraping.

The core concept is highly technical and specific, which generally resists easy, formulaic AI generation, though some structuring feels polished.

Human Indicators

Idiosyncratic emphasis on the necessity of the 'data foundation' being a structural necessity rather than a feature.

The specific framing of the problem—the gap between slow defenses and machine-speed attacks—demonstrates a synthesis of industry friction, typical of high-level analyst writing.