Skill UI

This guide serves as the core entry point for comprehensive security testing of identity and access control mechanisms. It is designed to help testers systematically identify vulnerabilities across login flows, session management, object authorization (IDOR), and modern protocols like JWT, OAuth, CORS, and SAML. Use this when planning security audits for any web application with user accounts.

An expert playbook for systematically testing Insecure Direct Object References (IDOR) and Broken Object/Function Level Authorization (BOLA/BFLA). This guide covers finding object identifiers across all request vectors (URL, body, headers, cookies), implementing A-B testing methodologies, identifying various ID patterns, and executing horizontal or vertical privilege escalation attacks. Essential for deep API security auditing.

A comprehensive playbook for testing security flaws in OAuth 2.0 and OpenID Connect (OIDC) implementations. Use this guide to systematically check for misconfigurations in redirect URI handling, state and nonce validation, PKCE enforcement, token audience/issuer checks, and account binding vulnerabilities. Essential for reviewing applications linked to external identity providers.

This tool simulates a Chief Technology Officer's comprehensive review, stress-testing any major technical plan. It systematically interrogates critical areas including scaling limits (scaling cliffs), accumulated technical debt, team capacity planning, build-vs-buy economics, system reliability (SLOs), and security compliance. Use it before committing to core architecture changes or making high-stakes engineering decisions.

A comprehensive red-teaming skill for assessing the security posture of Retrieval-Augmented Generation (RAG) pipelines. It systematically probes two critical injection surfaces: poisoned retrieved context (indirect prompt injection) and embedding manipulation. Use this skill to validate retrieval guardrails, ensure data leak prevention, and demonstrate vulnerabilities in LLM-powered knowledge assistants.

A comprehensive, four-phase methodology for debugging complex software issues. It guides users through root cause investigation, pattern analysis, hypothesis testing, and controlled implementation. The core principle emphasizes finding the underlying cause rather than applying quick, symptomatic fixes, ensuring robust and reliable code improvements across various failure scenarios.

This model provides an engineering operational framework for teams that leverage AI agents to generate large volumes of code. It shifts the focus from simple syntax to process quality, robust architecture design, rigorous testing, and systematic risk control, ensuring the development of highly stable and reliable systems in AI-assisted environments.

A comprehensive strategy for regression testing in AI-assisted development. It focuses on identifying systematic blind spots, such as schema inconsistencies between sandbox and production paths, and integrating automated bug checks into the development workflow. This guide teaches how to build robust, database-free API tests to ensure code quality when AI models contribute to the codebase.

A comprehensive pipeline designed for Laravel projects to ensure code quality and stability before deployment. It systematically executes environment checks, linting, static analysis, full testing with coverage, security audits, migration validation, and cache preparation. Essential for robust CI/CD pipelines and pre-Pull Request validation.

This guide assists developers in creating a systematic QA plan for RevenueCat integration. It provides a structured approach to verifying the entire subscription lifecycle, including initial purchases, renewal, upgrades, and cancellations. The core principle is linking tests to specific, verifiable dashboard signals, ensuring robust and reliable in-app monetization setups.