Skill UI

This guide outlines the methodology for conducting hardware security research on embedded systems. It covers physical interface analysis (UART, JTAG, SWD), debug pad triage, secure boot evaluation, and offline firmware extraction. It emphasizes systematic, non-destructive testing protocols and responsible handling of physical devices.

A comprehensive security assessment skill for identifying vulnerabilities in federated identity systems, including SAML, OIDC, and OAuth 2.0 flows. It covers common misconfigurations, such as signature tampering, PKCE failures, redirect URI issues, and token confusion, ensuring robust SSO implementation.

This tool tests your deep understanding of code you have recently written or reviewed. It generates structured, multi-level questions (Recall, Understanding, Application, Analysis, Synthesis) based on the provided code. Users can focus the quiz on specific areas like error handling, performance, or security, making it an excellent mechanism for continuous learning and solidifying technical knowledge.

A comprehensive framework for conducting authorized security assessments on Large Language Models (LLMs) and AI agents. It covers critical vulnerabilities including advanced prompt injection (OWASP Top 10), tool abuse, RAG data poisoning, memory manipulation, and system prompt extraction. Ideal for red teaming, security auditing, and ensuring the robustness of AI systems in production environments.

This comprehensive guide details the methodology for reverse engineering macOS and Mach-O binaries. It covers analyzing application bundles, deciphering Objective-C/Swift symbols, examining code signing and hardened runtime features, and performing both static (using tools like Ghidra, IDA) and dynamic analysis (using lldb, Frida) to aid in malware analysis and platform security research.

A comprehensive methodology for deep security testing of both Android (APK) and iOS (IPA) applications. This guide covers the entire workflow, from initial information gathering and static analysis (decompilation, code structure analysis) to advanced dynamic instrumentation, network interception, and bypassing modern security measures like SSL Pinning, Root/Jailbreak detection, and anti-debugging.

A comprehensive framework for authorized security assessments of Operational Technology (OT) and Industrial Control Systems (ICS). It emphasizes a 'passive-first' approach, covering Purdue model zoning, analyzing industrial protocols (Modbus, DNP3, etc.), and identifying exposure points on SCADA/DCS environments. The methodology strictly avoids disruptive write operations on PLCs, prioritizing read-only validation and safe network analysis for physical safety.

This skill parses standardized C-CDA/CCD XML clinical documents exported from EHRs. It extracts both human-readable section narrative text and coded entries, mapping them by LOINC codes and template IDs. It is essential for preparing clinical free-text data for subsequent NLP analysis and supports XML-aware de-identification while preserving document structure.

Guides users to select a local, on-device Personally Identifiable Information (PII) detection model from a committed registry. It filters models based on language, required runtime environment (e.g., PyTorch, MLX), and size constraints. The process emphasizes building an offline shortlist and mandates rigorous pre-deployment recall validation and performance benchmarking to ensure secure, privacy-preserving deployment.

Performs comprehensive, two-layer validation on generated plans. Layer 1 executes instant structural checks (format, dependencies, compliance) while Layer 2 triggers specialist agents (e.g., security, DB, performance) based on plan content. The system forces resolution of all identified issues before allowing execution, supporting auto-fixes and guided human input.

A comprehensive, multi-phase workflow guide for authorized reverse engineering of complex network protocols. Ideal for analyzing proprietary formats such as custom TCP/UDP binary protocols, Protobuf, gRPC, WebSocket frames, and reconstructing state machines from raw PCAP data. This guide covers data collection, field layout restoration, serialization recovery, and secure replaying.

Implements GDPR-compliant pseudonymization for sensitive personal or clinical data from EU residents. Unlike full anonymization, this method creates a reversible mapping key, which must be stored separately and securely. This process allows for controlled re-linkage (e.g., for Subject Access Requests or longitudinal care) while maintaining GDPR Article 4(5) compliance by ensuring the linkage key is kept separate from the working data.