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Realtime pattern-based detection and sanitization for prompt and command injection, designed to screen GitHub issues, sanitize inputs, and stop dangerous comman
Agent Guard is a real-time security framework that detects and sanitizes prompt and command injection attempts aimed at AI agents. It applies pattern-based detectors for command execution (npm, curl|bash, rm -rf), prompt-injection phrases (ignore previous instructions, developer mode), social engineering cues, and specialized GitHub issue screening for Clinejection-style attacks. The tool can replace dangerous segments with safe placeholders and produce threat reports.
Use Agent Guard wherever untrusted text could influence agent behavior: screening GitHub issue titles/bodies, sanitizing user-supplied prompts, or pre-filtering web-scraped content before model consumption. It is appropriate in CI pipelines, moderation layers, or any agent pipeline that executes commands or generates actions based on external text.
agent_guard.py, mcp_server.py, and cli.py for local testing and integration.Built primarily for OpenClaw/Claude MCP deployments but usable as a standalone Python library. It integrates easily with agent runtimes that can call a local sanitize/analyze endpoint or run a CLI check before executing actions.
Quality assessment: substantive, actionable, and security-focused — suitable to save.
This skill has not been reviewed by our automated audit pipeline yet.
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