Skill UI

Detects goal hijacking vulnerabilities where malicious instructions are hidden within external content sources processed by the agent, such as retrieved documents (RAG), uploaded files, or web page content. This skill simulates these attack vectors to ensure the agent only uses the provided context for the stated task and does not execute embedded hidden commands.

This tool provides comprehensive AI security scanning using the Tencent AI-Infra-Guard framework. It systematically audits AI infrastructure, scans tools and skills, checks agent security, and performs advanced LLM jailbreak evaluations to identify vulnerabilities and ensure the robustness and reliability of AI systems.

A comprehensive security tool designed for AI environments (OpenClaw). It functions as an 'antivirus' for AI skills, performing deep audits, scanning skills before installation, and running full security health checks. Its primary goal is to detect vulnerabilities, prevent data leaks, and mitigate privacy risks, ensuring the integrity and safety of the AI workspace.

A comprehensive tool designed to scan any agent skill for potential security risks and vulnerabilities before implementation or use. Powered by local static analysis (A.I.G.), it ensures that no file contents, credentials, or personal data ever leave your device, providing maximum privacy and safety for integrating new AI capabilities across various agent platforms.

This comprehensive guide provides essential security best practices for deploying applications on Fly.io. It covers critical areas such as secrets management, private networking using WireGuard, securing TLS certificates, and properly scoping deploy tokens. The included functions demonstrate how to validate API tokens, verify webhook signatures, and validate deployment configurations to mitigate common cloud and application-level vulnerabilities.

A comprehensive offensive checklist for assessing the security and robustness of AI and Large Language Model (LLM) applications. It covers advanced adversarial techniques such as prompt injection, jailbreaking, model extraction, data poisoning, and analyzing system vulnerabilities across components. Essential for red-teaming and security assessment.

A comprehensive methodology for discovering potential software vulnerabilities. It outlines advanced techniques including static analysis, dynamic analysis, fuzzing, taint tracking, and modern attack surface mapping (e.g., kernel, drivers). Ideal for professional code audits, bug bounty hunting, and building robust vulnerability research pipelines.

This is a detailed offensive checklist for identifying and exploiting insecure deserialization vulnerabilities across multiple programming languages (Java, Python, PHP, .NET, Node.js, etc.). It covers techniques like gadget chain generation, magic method abuse, type confusion, and modern attack vectors, providing a deep methodology for penetration testing and vulnerability research.

A speed-optimized, comprehensive checklist for rapid security assessments. This guide covers full-cycle penetration testing methodologies, including deep reconnaissance (WAF bypass, CDN mapping), access control testing (MFA, JWT, API keys), and session management vulnerabilities. Ideal for time-boxed engagements, CTF competition, or initial service triage.

A comprehensive checklist and methodology for penetration testing file upload endpoints. Covers critical vulnerabilities such as MIME type bypass, extension bypass, magic byte manipulation, path traversal, and stored XSS. Essential for web application security assessment and bug bounty hunting, guiding testers through basic testing to advanced exploitation techniques like Null Byte injection and double extensions.

This comprehensive guide covers advanced fuzzing methodology, a core technique in exploit development. Learn how to use coverage-guided fuzzing with powerful tools like AFL++ and libFuzzer to automatically discover critical security vulnerabilities, such as memory corruption bugs. Ideal for setting up robust fuzz campaigns, optimizing corpus generation, and triaging complex vulnerability outputs.

A comprehensive checklist designed for assessing the security posture of GraphQL endpoints. It covers advanced vulnerabilities such as introspection abuse, IDOR, query depth/complexity DoS, injection attacks (SQLi/NoSQLi), and authorization bypass mechanisms. Essential for professional penetration testing and bug bounty hunting.