ml-memory
Pass
Audited by Gen Agent Trust Hub on Sep 19, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill serves as a specialist guide for AI memory engineering. All analyzed components, including the implementation patterns and validation rules, focus on legitimate architectural and performance concerns without introducing security risks.
- [DATA_EXPOSURE]: The skill proactively addresses potential data leaks by including a validation rule (
memory-no-user-scope) inreferences/validations.mdthat requires all database queries to filter byuser_id, ensuring strict data isolation between users. - [COMMAND_EXECUTION]: The Python code snippets provided in the reference files are for logic such as exponential decay, salience learning, and entity resolution. These snippets use standard libraries and do not involve dangerous system calls, shell execution, or unsafe subprocess management.
- [PRIVILEGE_ESCALATION]: The skill includes patterns for 'Consolidation Conflicts' that recommend using distributed locks (e.g., Redis locks) and database-level locking (
SELECT FOR UPDATE). These are industry-standard practices for maintaining data integrity and do not represent a privilege escalation risk.
Audit Metadata