clawdefender

Scan AI agent skills and inputs for injection and exfiltration threats.

2|Updated Mar 10, 2026
One-click install
npx skills add https://github.com/gula00/autoclaw-skills --skill clawdefender-gula00
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: clawdefender
Source: https://github.com/gula00/autoclaw-skills/tree/main/clawdefender-1
Command: npx skills add https://github.com/gula00/autoclaw-skills --skill clawdefender-gula00

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill acts as a robust security layer for AI agents, proactively identifying and mitigating risks associated with malicious code, prompt injection, and data exfiltration.

Core Features & Use Cases

  • Security Auditing: Scans installed skills and scripts for known vulnerabilities and malicious patterns.
  • Input Sanitization: Cleans external input (like API responses or user-provided text) to prevent prompt injection and command execution.
  • URL Validation: Checks URLs before fetching to prevent SSRF and data exfiltration attacks.
  • Use Case: Before processing an email received by your AI agent, use ClawDefender to sanitize its content, ensuring no malicious commands or injection attempts are present.

Quick Start

Scan all installed skills for security issues using the command: ./scripts/clawdefender.sh --audit

Frequently Asked Questions about clawdefender

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I protect my AI agent from prompt injection and command injection attacks?

To protect against prompt injection and command injection, you need a security layer that sanitizes external inputs and scans skill code for malicious patterns. This prevents attackers from executing unauthorized commands through external text or API responses.

What is SSRF prevention and how does URL validation stop data exfiltration?

SSRF prevention blocks unauthorized server requests by validating URLs before fetching. Checking URLs prevents data exfiltration attacks by ensuring your AI agent does not access internal network resources or send sensitive data to malicious external endpoints.

How do I audit installed AI agent skills for security vulnerabilities?

You can audit installed skills for security vulnerabilities by running a script that analyzes skill code for malicious patterns. This security auditing process detects known threats and mitigates risks associated with malicious code before execution.

Can I sanitize external API responses before my AI agent processes them?

Yes, you can sanitize external API responses by running them through an input sanitization service. This cleans the input to prevent prompt injection and command execution, ensuring no malicious commands are present before processing.

Does path traversal detection work when scanning skill code for malicious patterns?

Path traversal detection works during security scanning by utilizing pattern matching to identify attempts to access unauthorized files. The scanner analyzes skill code and external inputs to mitigate these attacks and secure your AI agent.