
ClawPatrol
https://github.com/denoland/clawpatrol- Category
- Cybersecurity
- Rank
- No. 624Tools index
- Pricing
- Open Source
- Type
- TOOL
- Builder
- denoland
- GitHub
- 1.0k stars
- Latest release
- v0.5.9
- Date
About
Security firewall for AI agents — guardrails against prompt injection and dangerous tool calls. By Deno.
What it does
ClawPatrol is a programmable checkpoint between an agent and the services it contacts. It inspects network traffic, extracts protocol facts, then applies HCL rules before forwarding each action. Policies can deny requests or pause them for human approval. Operators can wrap one process, route an entire host, or run the central gateway.
Why it's ranked here
The project addresses agent access at the network boundary with unusually concrete controls. Rules can reason about SQL operations, Kubernetes resources, and HTTP request details instead of merely matching destinations. Its three deployment shapes make the same policy model useful for local workers and shared infrastructure, though setup complexity is substantial.
What's good
Protocol-aware facts make policies precise. A rule can distinguish SQL verbs and tables, Kubernetes verbs and namespaces, or HTTP methods and paths. WireGuard works without a separate gateway kernel module, while Tailscale mode avoids public inbound ports and adds user identity. Human approval can stop a request before it reaches the target.
Tradeoffs
This is infrastructure, not a lightweight agent library. The release-shaped Go binary is roughly 59 MB before the real dashboard bundle. Building requires the dashboard toolchain, and exercising per-process interception on macOS requires a signed system extension. WireGuard deployments also face NAT hairpin limits, while Tailscale mode depends on its hosted control plane.
How to use it well
Use it when platform engineers need enforceable controls around agents that access databases, Kubernetes, or HTTP services. Start with the annotated HCL example, test deny and approval paths, then choose per-process routing for isolated workers or host-wide routing for managed machines. It does not govern actions that never traverse the gateway, so retain host and application controls.
Technical notes+
README.md defines the gateway, join, and process-wrapping CLI surfaces. go.mod targets Go 1.26.3 and includes CEL, HCL, WireGuard, Tailscale, gVisor, SQLite, protocol parsers, and OpenTelemetry dependencies. Makefile builds the dashboard before compiling one binary and runs tests with go test ./.... internal/tools/docgen/main.go derives configuration documentation from registered Go schemas and supports a drift-check mode. doc/dev-setup.md says the Vite dashboard SPA is embedded at build time. doc/wireguard.md documents an embedded wireguard-go endpoint with a gVisor netstack, while doc/tailscale.md describes an embedded tsnet exit node. doc/wg-go-heap-buffers.md records an inherited unbounded buffer-pool risk under sustained traffic or high peer counts.
Observed
- License
- MIT
- Primary language
- Go
- Packaging
- Single statically linked Go binary with an embedded dashboard SPA
- Install surface
- Shell installer or source build with Make
- Interface
- CLI with gateway, join, and per-process run modes
- Platform support
- Per-process tunnels on Linux and macOS
- Configuration
- HCL policies with CEL conditions
- Network modes
- WireGuard and Tailscale
Read from README.md, go.mod, Makefile, internal/tools/docgen/main.go, doc/README.md, doc/dev-setup.md, doc/tailscale.md, doc/telemetry.md, doc/wireguard.md, doc/binary-size.md, doc/code-vocabulary.md, doc/claude-code-oauth.md, doc/multi-file-config.md, doc/wg-go-heap-buffers.md, doc/tailscale-oauth-credential.md.
What it can do
Block prompt injection attacks
User prompts and AI agent inputs → Filtered and sanitized prompts
Monitor AI agent tool calls
AI agent function calls and API requests → Security assessment and approval/denial decisions
Filter dangerous tool executions
Tool call requests from AI agents → Blocked or allowed tool execution commands
Detect malicious prompt patterns
Text prompts and conversation data → Security threat classification and alerts
Enforce AI agent security policies
Security rules and AI agent behavior data → Policy compliance reports and enforcement actions
Log security incidents
Security events and threat detections → Security incident logs and reports
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