KnightClaw: Local Security Extension for OpenClaw Agents
KnightClaw is a security extension designed to protect OpenClaw AI coding agents from adversarial prompts. The tool addresses a specific threat model where a single malicious message in the context window can cause an agent to follow attacker instructions instead of user commands.
Core Features
KnightClaw operates as a drop-in extension with no configuration required, no API keys, and no cloud dependency. It intercepts every message before it reaches the agent.
Detection System
The guard uses an 8-layer hybrid detection approach:
- Regex patterns
- Homoglyph detection
- Boundary token analysis
- Perplexity scoring
- Entropy analysis
- Heuristics
- Semantic embeddings (using a local, quantized BGE model)
Blocks occur in microseconds.
Additional Security Measures
- Egress redaction: Strips secrets from outbound responses before they leave the agent
- Hash-chained audit logs: Tamper-proof, append-only logs with full timeline of every block, allow, and config change
- Velocity circuit breaker: 10 blocks in 60 seconds triggers automatic lockdown with no manual intervention
- Kill switch: One command stops everything:
openclaw knight lockdown on
Technical Details
The extension runs entirely local with zero telemetry and is MIT licensed. The source is available for testing and contribution.
📖 Read the full source: r/openclaw
👀 See Also
AI Chatbots Leaking Real Phone Numbers: The PII Exposure Problem
Chatbots like Gemini, ChatGPT, and Claude are exposing real personal phone numbers due to PII in training data. DeleteMe reports a 400% increase in AI-related privacy requests in seven months.
Domain-Camouflaged Injection Attacks Evade Detectors in Multi-Agent LLM Systems
A new paper shows injection payloads tailored to domain vocabulary evade detection, dropping IDR from 93.8% to 9.7%. Multi-agent debate amplifies attacks. Llama Guard 3 detects zero payloads.
Zero-Trust OpenClaw Architecture Adds Pre-Execution Authorization and Post-Execution Verification
An open-source architecture for OpenClaw adds two security checkpoints: a Rust sidecar that intercepts tool calls before execution with sub-millisecond authorization overhead, and deterministic post-execution verification using assertions instead of LLM judgment. The system includes tracing with DOM snapshots and screenshots, plus a DOM compression skill that reduces token usage by 90-99%.
IronClaw's Security-First Approach to AI Agent Safety
IronClaw addresses AI agent security concerns by implementing constrained execution, encrypted environments, and explicit permissions instead of relying on LLM intelligence for safe behavior.