Cloud SecuritySecurity Operations
Mitiga Cloud Detection and Response Platform
Agentless cloud detection and response for cloud, SaaS, identity, and AI, with automated investigation, forensic data retention, and attack containment.
Mitiga Cloud Detection and Response Platform Overview
Mitiga's platform is an agentless Cloud Detection and Response (CDR) system for cloud, SaaS, identity, and AI environments, built to contain attacks that get past posture-based controls. Rather than scanning for misconfigurations, it monitors behavior across the full cloud estate and centers on a Cloud Security Data Lake that collects, normalizes, and enriches activity logs so every alert arrives with the forensic context needed to investigate it.
The platform connects telemetry from cloud providers, SaaS applications, identity systems, and AI infrastructure into a single view, then applies over 1,000 detection rules to surface compromised credentials, lateral movement, and data exfiltration. When a threat is detected, automated investigation paths reconstruct logs and actions into a unified attack timeline in the Cloud Investigation Workbench, and Cloud Investigation and Response Automation (CIRA) drives containment through cloud-native workflows. The Helios AIDR layer adds AI Triage and AI Insights to prioritize alerts and validate evidence, with forensic retention spanning more than 1,000 days.
Mitiga has been named an RSA Conference Innovation Sandbox finalist and a Global InfoSec Awards winner, and is listed among Dun's 100. It holds Advanced Technology Partner status in the AWS Partner Network and can be deployed alongside existing CNAPP tooling. The platform targets enterprise security operations teams, including Fortune 1000 companies, financial services institutions, and government agencies running cloud-first, SaaS-heavy environments.
Key Capabilities
mapped to solution categoriesAssembles chronological attack timelines from raw events across multiple data sources automatically, reducing the time to build an initial incident narrative.
Applies ML classification to incoming alerts to filter false positives, group related events, and route high-confidence detections to analysts, reducing L1 analyst workload.
Suggests the next investigative or containment steps for an alert or incident, with the supporting reasoning, so analysts can confirm and act rather than deciding from raw telemetry alone.
Inserts AI-generated analysis, triage decisions, and enrichment into existing SIEM and SOAR case management workflows rather than requiring analysts to use a separate interface.
Triggers automated response actions (session revocation, account suspension, OAuth grant removal), in SaaS platforms in response to confirmed detections via platform APIs.
Correlates SaaS activity with identity events (MFA changes, session token replay, impossible travel) to detect account takeover within cloud application environments.
Detects misuse of OAuth access tokens granted to connected applications, including tokens being used outside expected scope, geographic anomalies, and post-compromise app persistence.
Monitors user, admin, and OAuth app activity within SaaS platforms (M365, Google Workspace, Salesforce, GitHub), for anomalies and policy violations using API-based log ingestion.
Integrations
compatible toolsImplementation & support
Info last updated on June 27, 2026