Skill UI

This comprehensive guide implements External Attack Surface Management (EASM). It integrates leading industry tools like Shodan, Censys, subfinder, httpx, and nuclei for deep reconnaissance. Users can systematically discover assets, enumerate subdomains, fingerprint services, scan for vulnerabilities, and calculate weighted exposure scores based on professional OWASP methodology. Ideal for continuous security monitoring and deep penetration testing.

This comprehensive skill provides a systematic framework for performing deep security assessments on iOS applications. It covers static analysis of IPA packages, dynamic instrumentation using Frida and Objection, SSL pinning bypass for traffic interception, extraction and auditing of sensitive data from the Keychain, and runtime method hooking. Use this for authorized penetration testing against standards like OWASP MASTG.

This advanced code review skill forces genuine perspective shifts by employing three hostile reviewer personas: the Saboteur (production breaks), the New Hire (maintainability), and the Security Auditor (OWASP-informed). It ensures that all code reviews are critically rigorous, eliminating superficial "Looks Good To Me" approvals and catching blind spots missed by the original author or general AI models. Use it before merging a PR for maximum confidence.

Checks AI agent implementations against the OWASP Agentic Security Initiative Top 10 risks, producing findings on controls, vulnerabilities, and recommendations for prompt injection, tool governance, escalation, logging, identity, policy, supply chain, and behavioral monitoring before production or audit.

This framework implements the OWASP Top 10 standards, specifically tailored for Agentic Applications. It provides a standardized methodology to classify and map diverse security findings—such as prompt injection, tool misuse, and privilege abuse—to ten core risk categories (ASI01-ASI10). It is essential for security teams to systematically assess, prioritize, and remediate vulnerabilities inherent in complex AI agent systems.

A comprehensive methodology for identifying critical vulnerabilities in transactional applications (e-commerce, fintech, SaaS). This goes beyond standard OWASP Top 10 checks, focusing on flaws like workflow bypass, state machine violations, price manipulation, and role boundary abuse. It guides testers to map application flows, identify hidden endpoints, and quantify the potential financial impact of logic failures.

A comprehensive CI/CD pipeline for Quarkus applications, designed to verify code quality and deployment readiness. It covers all phases: build, static code analysis (SonarQube, Checkstyle), rigorous functional testing (Unit, Integration, API), security scanning (OWASP, dependency checks), native image compatibility testing, performance load testing (K6), and container image validation (Trivy, Grype).

This tool provides a comprehensive security assessment framework for Retrieval-Augmented Generation (RAG) systems and vector databases. It tests critical vulnerabilities such as embedding inversion, cross-tenant data leakage, knowledge-base poisoning, and retrieval manipulation, aligning with OWASP LLM08:2025 standards. It is essential for validating the security posture of multi-tenant and vector-search applications.

Automate security regression testing for Large Language Model (LLM) applications by integrating Promptfoo and DeepTeam into CI/CD pipelines. This skill enforces a critical security gate, automatically testing endpoints against OWASP LLM Top 10, OWASP Agentic threats, and common jailbreaks/prompt injections. It ensures that security patches do not regress over time due to prompt or model changes, providing continuous risk monitoring.

This guide provides a structured approach to red-teaming Large Language Models (LLMs) to detect sensitive data leakage from system prompts. It simulates advanced attacks—including prompt injection, instruction override, and encoding tricks—to identify embedded secrets, API keys, and proprietary business logic. Essential for validating adherence to OWASP LLM07 and securing AI applications against data exfiltration.

This comprehensive guide outlines a multi-stage verification pipeline for Quarkus applications. It covers build artifacts, static analysis (Checkstyle, SonarQube, PMD), comprehensive testing (Unit, Integration, API), security scanning (OWASP, dependency checks), native compilation, and performance testing (K6). Use this before PRs or deployments to ensure code quality and stability.

A comprehensive CI/CD quality gate checklist for Spring Boot projects. It guides developers through mandatory steps including building, static analysis (SpotBugs, PMD), running unit/integration tests, measuring code coverage, performing security scans (OWASP), and reviewing diffs before merging or deploying.