{"repo":"quantifylabs/aegis-memory","free":true,"listed":false,"github":"https://github.com/quantifylabs/aegis-memory","clone":"git clone https://github.com/quantifylabs/aegis-memory.git","description":"Secure context engineering for AI agents. Content security · integrity verification · trust hierarchy · ACE patterns. Self-hosted, Apache 2.0.","language":"Python","stars":27,"topics":["agent-security","agents","ai","ai-agents","audit-trail","compliance","content-security","context-engineering","mcp","memory"],"license":"Apache-2.0","category":"ai-agents","readme_excerpt":"Secure memory & context for AI agents. Every write is screened for prompt injection, secrets, and tampering before it can persist or reach another agent. aegis inspect finds the unsafe memory writes in your agent  →  aegis memory.guard gates every one of them. Website • Docs • Blog • Quickstart • Security Guide --- Contents - What is Aegis? — the 60-second overview + architecture - Why it matters — agents are being compromised through memory - Quickstart (2 minutes) — server, SDK, first multi-agent example - Guard every write — the write boundary, in code - Threat model — what Aegis defends, and what it doesn't - Security capabilities — the six built-in protections - The Context Hub — prompts + memory + skills + subagents in one call - Memory Depth — hybrid retrieval, contradictions, consolidation - Context that improves itself (ACE) — agents that learn - How Aegis compares — vs mem0, Zep, Letta - What's shipped vs roadmap — no marketing ahead of code - Security benchmark — does the detector actually work? - Memory benchmark — LongMemEval, and what poisoning does to it - Performance — latency and throughput numbers - Deployment and configuration - Documentation · Contributing · License --- What is Aegis? Aegis Memory is a secure memory and context layer for AI agents. It does what a memory library does — store, search, rank, and share what your agents know — but it treats every piece of content as untrusted until it's screened. A single gate sits in front of mem","default_branch":null,"files":null,"tree":[],"storefront":"/r/quantifylabs","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/quantifylabs/aegis-memory/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}