When your AI agent needs a chaperone, a bouncer, and a snitch
ClawKeeper wraps OpenClaw agents in three independent security layers—policy injection, runtime enforcement, and external oversight—because autonomous tools should not police themselves.

What it does ClawKeeper hardens OpenClaw autonomous agents through three concurrent mechanisms. Skills inject security policies directly into the agent context; a plugin audits configurations and monitors behavior at runtime; and a decoupled watcher process oversees state evolution, ready to halt high-risk actions or demand human confirmation without coupling to the agent’s internal logic.
The interesting bit The project treats safety as a separation-of-powers exercise. By keeping the watcher independent and system-agnostic, it attempts to guarantee that a rogue or misdirected agent cannot disable its own chaperone. The README bills it as “The Norton for OpenClaw,” which is either a warning or a promise depending on your nostalgia for 1990s antivirus pop-ups.
Key highlights
- Three complementary layers: instruction-level skills, runtime plugin enforcement, and independent watcher middleware.
- v1.1 ships concrete guards:
exec-gateblocks destructive shell commands via regex,path-guardlocks sensitive files,budget-guardenforces token limits, and a permission store with HMAC-SHA256 integrity protection tracks allow/deny decisions. - The watcher runs locally or in the cloud and is described as deployable across personal, enterprise, and intranet environments.
- A self-constructed benchmark of seven adversarial categories is cited, though the README offers no specific metrics—only a chart and the claim of “optimal defense performance.”
Caveats
- Benchmark claims are unquantified in the README; no scores, margins, or statistical detail accompany the “optimal” assertion.
- Despite the watcher’s advertised system-agnostic design, every integration example and command reference targets OpenClaw exclusively.
Verdict Worth evaluating if you are running OpenClaw agents in production and want defense-in-depth without betting everything on a single gate. If you are not in the OpenClaw ecosystem, treat this as architecture inspiration rather than a drop-in solution.
Frequently asked
- What is SafeAI-Lab-X/ClawKeeper?
- ClawKeeper wraps OpenClaw agents in three independent security layers—policy injection, runtime enforcement, and external oversight—because autonomous tools should not police themselves.
- Is ClawKeeper open source?
- Yes — SafeAI-Lab-X/ClawKeeper is an open-source project tracked on heatdrop.
- What language is ClawKeeper written in?
- SafeAI-Lab-X/ClawKeeper is primarily written in TypeScript.
- How popular is ClawKeeper?
- SafeAI-Lab-X/ClawKeeper has 1k stars on GitHub.
- Where can I find ClawKeeper?
- SafeAI-Lab-X/ClawKeeper is on GitHub at https://github.com/SafeAI-Lab-X/ClawKeeper.