AGENTIC RUNTIME SECURITY
Cloud, SaaS, Identity, and Al are where attackers operate now—and where endpoint tools go blind. Mitiga delivers Agentic Runtime Security that anticipates, interrupts, and stops active attacks before they reach the business.
Agentic Runtime Security across your modern infrastructure — Cloud, SaaS, Identity, AI, and Third-party Services.
Transforming the modern SOC
For well over a decade, security operations lived on the endpoint. But now the enterprise runs on cloud, SaaS, identity, third-party services, and AI — and four forces have reshaped what the SOC has to defend.
Driver 01
AI now finds vulnerabilities faster than the world can patch them, and exploitation often begins before a fix ships. When we can't close the window in time, we must pivot to detecting and disrupting what gets past defenses as a result.
Driver 02
The average enterprise runs hundreds of SaaS apps — sanctioned, unsanctioned, and entirely unknown. You can't defend what you can't see, and posture tools weren't built to surface active SaaS misuse.
Driver 03
Chatbots, copilots, and autonomous agents now act with their own credentials and permissions. The fastest-growing identity on your network isn't a person — and it operates entirely outside the endpoint's view.
Driver 04
Modern attacks cross Cloud, SaaS, Identity, AI, and third-party services in minutes. Defending against them means anticipating, detecting, interrupting, and stopping active attacks across the entire modern infrastructure — in runtime.
anticipate, disrupt, stop active attacks
The primary asset is no longer the server — it's third-party services, cloud, SaaS, identity providers, and AI. That world is now much more complicated than endpoints, not less.
On an endpoint, you can always fall back to the device for a disk image or memory dump. In a cloud and services world, there's no endpoint to fall back to — defense is 100% dependent on the logs. That's why a forensic-grade, distributed data lake is a structural necessity for Mitiga, not a feature.
Mitiga delivers behavioral detection that catches attacks in runtime, agentic AI triage that collapses noise into a prioritized attack story, and fast, reversible containment — before anything bad happens.
Mitiga AI Detection and Response
Agentic Runtime Security isn't AI bolted on. Every pillar runs on the same agentic, AI-native platform — built with AI, to defend with it, from it, and the AI itself.
Pillar 01
AI for Detection & Response
An automated SOC agent runs AI triage, agentic investigation and hunting, and agentic containment and remediation end-to-end — fully integrated into the agentic SOC over API and MCP.
Pillar 02
AIDR for AI-Centric & AI-Scaled Attacks
Purpose-built for AI-speed adversaries: runtime AI triage, investigation, and hunting paired with AI-attack detection, automated detection engineering, and fast, automated, reversible containment.
Pillar 03
AIDR for AI Resources & SaaS Apps
Detects and stops attacks across workforce AI like ChatGPT, Copilot, and Agentforce and AI infrastructure like Bedrock and Claude — shutting down AI abuse, compromised identities, and threats to AI SaaS apps and services.
detect and contain active attacks at machine speed
Endpoint detection and response only sees what crosses the device, and can't see cloud infrastructure and providers, SaaS, identity, AI, and third-party services. The most dangerous activity originates in the cloud and identity control plane. That's where Mitiga watches.
Proof 01
More shadow apps found than agent-based endpoint tools.
In recent customer deployments, Mitiga surfaced more unauthorized SaaS applications than agent-based endpoint security already in place. Shadow SaaS is identity-driven and cloud-native — it never generates a tell-tale endpoint signal.
Proof 02
A new and rapidly expanding threat class.
Unsanctioned SaaS no longer means a shared file. A meeting transcription tool like Otter.ai is a conversation recorder — one adoption exposes every participant in every meeting it touches, widening data exfiltration risk and opening the door to identity threats.
Proof 03
Real-time coverage for non-human identities.
The fastest-growing identity isn't a person. Mitiga extends IOA-based behavioral detection to chatbots, copilots, and autonomous agents — watching the calls they make and data they reach, and flagging compromise or abuse in real-time as it happens.
Key capabilities
One runtime defense layer that detects, decodes, and disrupts, built on a long-horizon forensic data lake.
Identity Threat Detection & Response
Continuous behavioral baselining across users, service accounts, OAuth apps, API tokens, and federated access — surfacing identity-driven attacks that posture tools and audit logs miss.
AI-Powered Detection & Triage
Automated analysis evaluates impossible travel, token misuse, abnormal permission changes, and atypical admin actions in context — filtering benign mistakes, elevating true attacks. Fewer alerts, faster clarity.
Comprehensive AI Threat Coverage
IOA-based detection across LLMs, AI SaaS (ChatGPT, Gemini, Copilot), embedded chatbots, and AI agents — catching compromised credentials, lateral movement, and exfiltration in real time.
Shadow SaaS and AI Discovery
Continuous visibility into sanctioned, unsanctioned, shadow SaaS, and embedded AI — the apps, identities, tokens, and integrations already active — turning hidden risk into investigation-ready context.
Attack Timeline Reconstruction
Full-fidelity forensic data, retained across SaaS, identity, cloud, and AI, reconstructs attacker activity into one chronological timeline — tracing attacks back days, weeks, or months without gaps.
Cross-Domain Correlation
Links SaaS and identity activity to cloud API actions, AI usage, and downstream integrations — revealing the full blast radius so containment is never partial.
The Modern SOC
Mitiga gives SecOps teams what they need to transform a legacy, reactive SOC into an AI-native operating model — built to anticipate and stop attacks instead of chasing them after the fact.
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Capability
Agentic Runtime Security
The Modern SOC with Mitiga
Legacy Reactive SOC + SIEM
Runtime attack & drift protection
Spot early signals of attacks across cloud, SaaS, identity, AI, and third-party services and autonomously respond and stop in runtime. Identify and respond to risky Cloud & SaaS configuration drift and compliance violations in real time, and fix before the exploit.
Configuration and compliance drift surfaces in a posture scan days or weeks later — if at all. Detection stops at the alert; response is manual, and attacks materialize before anyone acts.
Agentic Detection Factory
Benefit from a comprehensive and rapidly growing repository of over 2,500 detections, growing with hundreds of new detections monthly, plus automated and pre-tested custom detections across your entire modern infrastructure.
A static rule library that begins aging the moment it ships. New detections mean professional services, custom engineering, and weeks of tuning per use case.
AI-driven threat hunting
Preemptive, continuous, and automated hunting across SaaS, Cloud, AI, and Identity. Finds hidden, dwelling attackers before they strike.
Hunting is manual, periodic, and analyst bound — gated by who's available and what they think to look for. Dwelling attackers sit undiscovered between hunts.
AI Triage
Evidence gathering, attack timeline reconstruction, verdict, and recommended response actions, all handled before a human opens the alert. From alert flood to actionable verdict, without analyst intervention.
Every alert lands cold in a queue. Analysts gather evidence, pivot across consoles, and rebuild the timeline by hand — hours of work before a verdict.
Distributed data lake
A distributed data lake architecture provides an investigation-grade context layer across Cloud, SaaS, Identity, and AI — leveraging both existing and collected, enriched data that feeds the Agentic SOC.
Data is siloed per tool with short retention. Investigations stall on missing logs, and there's no unified context layer to feed an agentic SOC.
AI SOC analyst
A personal, autonomous AI SOC analyst that runs deep investigations, threat hunts, detections, and triage. Cover every alert with 90% faster detection & response speed, 70% fewer false positives needing review, and 67% faster time to close out alerts — while scaling without adding headcount.
Headcount is the only way to scale. Alerts go uninvestigated, MTTR climbs, and coverage is capped by the size of the team.
What runtime defense delivers
01
Anticipate attacks across cloud, SaaS, identity, AI, and third-party services.
02
Detect active attacks the moment behavior turns malicious.
03
Interrupt attacks before data access or exfiltration.
04
Stop the threat, eliminate attacker persistence, and prevent impact.
Why posture-based security falls short
Posture and prevention tools reduce exposure — but end where compromise begins. They find misconfigurations, not active attackers. They see in silos and are limited by not providing broad context.
Alerting tools are noisy and disconnected from real behavior, drowning the signal that actually matters.
Traditional incident response starts after the damage is done — reconstructing an attack instead of disrupting and stopping it.
You don't close the gap by watching the device harder. You close it by defending the cloud, SaaS, identity, third-party services, and AI surfaces at runtime.
Across cloud, SaaS, identity, third-party services, and AI — stopping attacks before they reach the business.
