CiscoCiscoDefenseClaw

Overview

DefenseClaw is the Cisco governance layer for AI coding agents — scan capabilities before they run, inspect runtime traffic, and export durable audit evidence across nine first-class connectors.

DefenseClaw is the Cisco governance layer for AI coding agents. It enforces one rule: untrusted agent capabilities are scanned, governed, logged, and blocked when policy says they are unsafe.

Three jobs, one runtime

GovernInspectProve
Skills, MCP servers, plugins, and generated code before they runPrompts, completions, tool calls, and sandbox activity at runtimeSQLite audit history, JSONL, OTLP, Splunk, webhooks, and TUI views

DefenseClaw combines a Python operator CLI, a Go gateway sidecar, and an OpenClaw TypeScript plugin. The CLI configures and inspects; the gateway runs the data path; the plugin wires the loop closed inside OpenClaw.

Architecture

setup · approve · audit
Agent runtimeClaude · Codex ·OpenClaw · ...
Connectorproxy or hooks
defenseclaw-gatewayGo sidecar
Policy + Scanners+ optional LLM Judge
SQLite + JSONL
OTLP · Splunk · Webhooks
OperatorCLI · TUI · HITL
DefenseClaw spans three runtimes — Python CLI, Go gateway sidecar, OpenClaw plugin — and exposes one enforcement contract per connector.

What's in the box

Scope and limitations

DefenseClaw improves safety by combining scanner results, runtime inspection, policy decisions, sandbox controls, and audit trails. It does not prove that an agent, skill, plugin, or model interaction is risk-free.

High-risk deployments should pair DefenseClaw with human review, least-privilege credentials, sandboxing, CI gates, and production monitoring. In observe mode, findings are logged without blocking. In action mode, configured HIGH and CRITICAL findings can block prompts, tool calls, or component admission.