Caveat verdict

memory-lifecycle

agent-memory-lifecycle

88
🟢 Trusted
No high-risk patterns surfaced by the deep scan — automated capability review, not behavioral proof.

The skill provides a systematic memory management approach for AI agents, using legitimate capabilities like file and network operations to implement a five-tier lifecycle for memory management.

⚠ Flagged for review — coarse, uncorroborated signal, not a confirmed exploit. Review the config yourself before installing.

Automated static analysis — not a human review. Caveat flags capabilities, not confirmed intent, and can produce false positives. Disagree with this verdict? Use Dispute below.

68
security
80
transparency
70
maintenance

Permission integrity

Accesses agent memory/configuration files

agent_memory

Findings (4)

Pattern match medium

References agent memory files

SKILL.md · frontmatter · MEMORY.md

Pattern match medium

subprocess execution — runs system commands from Python

scripts/setup.py · prose · downgraded · subprocess.run(

Pattern match medium

subprocess with shell=True — command injection vector

scripts/setup.py · prose · downgraded · subprocess.run(cmd, shell=True

Pattern match low

Popular HTTP library — network access

references/weekly-prompt.md · prose · downgraded · got

Why the tier is capped

Execution sink present in raw bytes (Hard Floor: class D). Final tier capped at Caution — cannot be lifted by any downgrade, example-payload opt-in, or allowlist.

Permissions & capabilities

No declared permissions — minimal attack surface.

network_inagent_memory

Is this flag fair?

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