Skill UI

A comprehensive guide to deploying decoy artifacts, such as fake credentials, URLs, and files, called honeytokens or canarytokens. These tokens have no legitimate operational use; therefore, any interaction with them provides a high-fidelity, low-false-positive signal of an intrusion, data theft, or insider threat. Use this technique to enhance detection in low-telemetry areas like file shares or credential stores.

A comprehensive skill for triaging npm packages and dependency lockfiles against supply-chain threats. It utilizes heuristic scanning (GuardDog), manual tarball inspection, and dynamic detonation in isolated environments to detect malicious behavior such as credential exfiltration, reverse shell execution, and self-propagation. Essential for secure code review and CI/CD pipeline gating.

A critical security tool for detecting typosquatted, brandjacked, or misspelled packages across major registries (npm, PyPI, crates.io). It uses advanced techniques like edit-distance and corpus matching to proactively screen dependency names before installation. Ideal for implementing CI/CD gates, auditing lockfile diffs, or reviewing dependency lists sourced from AI models to mitigate supply chain attacks.

This comprehensive guide covers the process of creating, analyzing, and securing Software Bills of Materials (SBOMs). It utilizes Syft to generate standards-compliant SBOMs (CycloneDX or SPDX) from container images and filesystems. The workflow details correlating these SBOMs with known CVEs using Grype for vulnerability analysis, and subsequently signing the artifacts with Cosign. This process is crucial for establishing supply chain trust, ensuring dependency visibility, and integrating vulnerability gating into CI/CD pipelines.

Chainsaw is a fast, Rust-based forensic tool designed for first-response threat hunting. It analyzes collected Windows EVTX files using the comprehensive Sigma rule corpus, built-in detection rules, and high-speed keyword/regex searching. Furthermore, it uniquely analyzes critical artifacts such as shimcache, SRUM, and event-log gaps, providing robust, offline detection capabilities without needing a SIEM pipeline. It is essential for digital forensic triage and hypothesis confirmation.

This skill provides a comprehensive guide to the full lifecycle operation of the Havoc Command and Control (C2) framework. It covers setting up the team server, writing Yaotl profiles, and generating highly evasive Demon agents using sophisticated techniques like indirect syscalls and sleep obfuscation. It is critical for authorized red-team engagements, adversary emulation, and validating EDR detection capabilities.

This guide details the process of parsing core Windows forensic artifacts, including MFT, Prefetch, Registry hives, ShellBags, and Amcache. Utilizing Eric Zimmerman's specialized EZ Tools, raw evidence is converted into standardized CSV/JSON formats. This process is crucial for Digital Forensics and Incident Response (DFIR) investigations, enabling analysts to reconstruct program execution, file access history, and persistence mechanisms, which can then be loaded into Timeline Explorer for unified analysis.

Trivy is an open-source, comprehensive security scanner designed for DevSecOps. It assesses container images, Infrastructure-as-Code (Terraform, K8s), filesystems, and SBOMs for vulnerabilities (CVEs), misconfigurations, hardcoded secrets, and license compliance. It is essential for implementing 'shift-left' security gates in CI/CD pipelines, ensuring that code and infrastructure are secure before deployment.

This advanced protocol forces the AI to conduct a thorough context audit before attempting any complex task. It mandates reading every relevant file, identifying architectural gaps, and providing a detailed orientation statement. It is essential for multi-file modifications, system design, and debugging to prevent acting on assumptions and maintain high code accuracy. The AI cannot proceed until all unknown variables are resolved.

This skill guides developers through the complex process of integrating an iOS App Clip target into an existing Expo project. It covers setting up the necessary bundle identifiers, configuring associated domains (AASA file), and deploying the required metadata to allow the lightweight clip to be invoked directly from a URL alongside the parent application.

This skill assists in generating robust Behavior Driven Development (BDD) tests. It supports writing feature files using Gherkin syntax (Given/When/Then) and automatically generates corresponding step definitions in multiple languages, including Java, JavaScript, and Ruby. Ideal for structuring and automating end-to-end functional tests.

This skill helps developers achieve maximum AI readiness by automatically detecting the project stack and seeding context using a single, precise goal sentence. It systematically fills the essential project context (the 6 Ws), requiring the user only to answer the few remaining knowledge gaps (like the 'why' or 'when'). This creates a portable, structured context file, ensuring AI models have a complete understanding of the project before coding, minimizing guesswork and maximizing efficiency.