Entric leverages multi-stage AI reasoning to analyze architectural trust boundaries, uncover zero-day logic vulnerabilities, and auto-synthesize context-aware security fixes.
[19:42:01] INFO Mapping repository execution paths and auth boundaries...
[19:42:04] WARN Potential authorization bypass detected in /api/v2/user/roles.py:142
[19:42:07] CRITICAL Confirmed state race condition allowing parameter tampering.
[19:42:09] SUCCESS Synthesizing automated patch PR #148 with zero false positives.
Built for Next-Gen Security Researchers & Engineers
Evaluates entire repository structures, cross-file dependencies, and authentication logic to pinpoint multi-step exploit paths that static SAST tools completely miss.
Eliminates scanner fatigue by autonomously verifying exploitability. Filters out non-viable code paths and formats actionable threat reports with full telemetry.
Generates clean, production-ready bug fix pull requests that preserve existing code standards while patching vulnerabilities directly inside your CI/CD workflow.
From Ingestion to Patching in Minutes
Seamless GitHub/GitLab integration via secure webhooks or CLI runner.
AI constructs an AST and execution graph to model sensitive data flows.
Deep reasoning models evaluate complex logical attack vectors.
Generates validated code patches and opens secure pull requests.
Join our private beta for security researchers and enterprise security engineering teams.
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