quantifylabs/aegis-memory
Secure context engineering for AI agents. Content security · integrity verification · trust hierarchy · ACE patterns. Self-hosted, Apache 2.0.
Implements a 4-stage content security pipeline (injection detection, sensitive data scanning, integrity signing via HMAC-SHA256) and cryptographic agent binding to prevent context poisoning—a top attack vector in multi-agent systems. Built on an OWASP 4-tier trust hierarchy with immutable audit trails and ACE loop automation (generation→reflection→curation) that self-improves agent memory based on task outcomes. Provides Python SDK with cross-agent scoped access control and Docker-based self-hosted deployment.
Available on PyPI.
Stars
19
Forks
5
Language
Python
License
Apache-2.0
Category
Last pushed
Mar 02, 2026
Monthly downloads
100
Commits (30d)
0
Dependencies
7
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