aegis-memory and aegis-lang
These are complementary tools where the memory/context security layer (A) would typically be implemented within or called by the security-by-construction language (B) to enforce trusted information flow in agent architectures.
About aegis-memory
quantifylabs/aegis-memory
Secure context engineering for AI agents. Content security · integrity verification · trust hierarchy · ACE patterns. Self-hosted, Apache 2.0.
This project helps operations engineers and security teams build AI agents that are protected against common vulnerabilities like data leaks and content manipulation. It takes the information your agents use and produce, ensuring its integrity and security, so you can confidently deploy AI agents in sensitive environments. It's designed for anyone deploying AI agents in a production setting where security and data protection are paramount.
About aegis-lang
RRFDunn/aegis-lang
A security-by-construction programming language for AI agents
Aegis provides a specialized programming language designed for building AI agents with security and compliance built-in. It takes your agent's code, written in a secure language, and produces Python code that automatically enforces runtime security policies like data tainting, capability restrictions, and audit trails. This is for developers and teams creating AI agents in regulated or high-stakes environments.
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