openclaw - 💡(How to fix) Fix Integration: Adding prompt injection protection and audit logging to OpenClaw with Ombre[Feature]: [1 comments, 2 participants]

Summary

Add Ombre as an official security and audit integration for OpenClaw

Problem to solve

OpenClaw has documented prompt injection vulnerabilities and 469 open security issues. SECURITY.md lists prompt injection as out of scope. With 5,700+ community skills, every skill install is a potential attack surface. There is currently no built-in security layer protecting LLM calls.

Proposed solution

Integrate Ombre — an open source security and audit layer — to wrap OpenClaw's LLM calls automatically.

Adds:

• Prompt injection blocking (20+ attack patterns)
• PII redaction before data hits the model
• Tamper-proof audit trail of every agent decision
• Hallucination detection on every response
• EU AI Act compliance exports
• 40-60% cost reduction via semantic caching

pip install git+https://github.com/pypl0/Ombre.git

github.com/pypl0/Ombre

Alternatives considered

Manual prompt sanitization is inconsistent and misses sophisticated injection attacks. No existing OpenClaw integration addresses the full security and compliance stack.

Impact

Affected: All OpenClaw users running community skills Severity: High — prompt injection can cause real damage Frequency: Every LLM call is a potential attack surface Consequence: Data leaks, unauthorized actions, compliance violations

Evidence/examples

Palo Alto Networks called OpenClaw a "security nightmare" 469 open security issues on this repo SECURITY.md explicitly lists prompt injection as out of scope Ombre demo: github.com/pypl0/Ombre

Additional information

Ombre runs locally — zero data transmission. BUSL 1.1 licensed — free for internal use. Built by a solo developer in Kenya from an Android phone.