ClawShield is an open-source firewall that sits between AI agents and inspects every communication, blocking prompt injection, PII leaks, and secrets before they reach the model or leave the network.

How does ClawShield protect OpenClaw agents?

It uses 3-layer defense-in-depth: application-level content scanning, iptables network egress rules, and eBPF kernel-level syscall monitoring with behavioral anomaly detection.

Why was ClawShield built?

The creator built it after discovering 40,214 OpenClaw instances exposed with critical CVE-2026-25253, realizing there was no firewall between agents that could block compromised agent communication.

Is ClawShield open source?

Yes. There are two implementations: DEFNOISE-AI/ClawShield and SleuthCo/clawshield-public, both available on GitHub under open-source licenses.

Does ClawShield work with other AI agents besides OpenClaw?

Yes. ClawShield is built to protect OpenClaw instances but works with any agent-to-agent protocol, making it applicable to broader AI agent security.

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ClawShield: Open-Source Firewall for Agent-to-Agent AI — Defense-in-Depth with eBPF Kernel Monitoring

ClawShield inspects every agent communication — blocking prompt injection, PII leaks, and secrets. Built after discovering 40K+ exposed OpenClaw instances. 3-layer defense: application scanning, iptables network rules, and eBPF kernel monitoring. Ships with 5 AI agents and YAML policy engine.

Product Idea from this Signal

An observability platform that traces every OpenClaw agent action across sessions and providers with full replay

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When an OpenClaw agent breaks something or produces a wrong result, developers have no way to replay what happened. Session logs are text blobs with no structure, there is no trace linking a chain of tool calls to a final output, and multi-agent setups produce interleaved logs that are impossible to untangle. ClawShield (500 GitHub stars) tackles the security angle with eBPF monitoring but does not help with debugging or performance analysis. This tool captures every agent action as a structured trace, links them into causal chains, and provides a replay UI where you can step through exactly what the agent did and why.

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