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Acacian/aegis

v0.6.0 Security

This release includes 1 security fix for security teams reviewing exposed deployments.

Published 2mo MCP Security & Auth
✓ No known CVEs patched
Read the diff → Tool health → What is this tool? →
This release patches 1 known CVE

Topics

agent-security ai-agent-security ai-agents ai-governance ai-safety ai-security
+14 more
audit-trail compliance guardrails langchain llm-security mcp mcp-security model-context-protocol pii-detection policy-as-code policy-engine policy-testing prompt-injection selection-governance

Affected surfaces

auth rce_ssrf

Summary

AI summary

Added eight new MCP security modules and fixed eighteen vulnerability issues.

Full changelog

MCP Security Modules & Security Hardening

New Features

  • 8 MCP security modules: response scanning, escalation detection, shadow detection, rate limiting, consent protocol, transport validation, security reports, audit dashboard
  • LangChain indirect prompt injection PoC demo
  • MCP security positioning pivot + retention mechanisms

Security

  • 18 vulnerability fixes: fail-closed defaults, API auth enforcement, data sanitization, SSRF/ReDoS/TOCTOU protection
  • URL sanitization + Streamlit CVE fix

Testing & Quality

  • Test coverage 87% → 91%+ (audit backends, instrument modules, pydantic_ai, patch_openai all at 100%)
  • Pre-commit framework integration (ruff lint + format + suspicious file blocker)

CI/DX

  • Upgraded ruff pre-commit hook (v0.3.0 → v0.11.2)
  • Claude Code hooks: auto-format on edit, pre-commit lint gate, pre-push CI gate
  • Skip MCP-dependent tests gracefully when MCP not installed

Full Changelog: https://github.com/Acacian/aegis/compare/v0.5.0...v0.6.0

Security Fixes

  • 18 vulnerability fixes including fail‑closed defaults, API auth enforcement, data sanitization, SSRF/ReDoS/TOCTOU protection and URL sanitization for Streamlit CVE

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About Acacian/aegis

Policy-based governance for AI agent tool calls. YAML policies, approval gates, risk assessment, and audit logging. Cross-platform: LangChain, OpenAI, Anthropic, MCP.

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Beta — feedback welcome: [email protected]