Skill UI

A comprehensive guide to writing reliable and maintainable tests for Kotlin projects. This skill covers modern testing patterns using Kotest for various spec styles (FunSpec, BehaviorSpec), MockK for dependency mocking, and enforces TDD principles (RED/GREEN/REFACTOR). Learn how to implement unit tests, property-based testing, and ensure high code coverage with Kover.

This skill details the process of reverse engineering Go-compiled malware using Ghidra. It involves parsing Go-specific metadata structures like buildinfo and pclntab to recover stripped or obfuscated function names. Users can also extract embedded module paths and dependency strings, providing critical insight into the malware's capabilities and third-party dependencies.

A comprehensive guide detailing how to integrate DevSecOps best practices into a GitLab CI/CD pipeline. It automates multiple security checks, including Static Analysis (SAST), Dynamic Analysis (DAST), container scanning, dependency scanning, and secret detection. This approach enforces 'shift-left' security, finding and fixing vulnerabilities early in the development lifecycle to ensure compliance and robust security.

A robust framework for orchestrating complex, multi-step coding tasks using multiple AI agents. It functions by first planning the entire project into a mission dependency graph (DAG), then dispatching specialized agents to isolated Git worktrees for parallel development. The system automatically monitors progress, handles merges, and generates structured, comprehensive reports detailing changes, completed tasks, and next steps.

A robust security auditing tool designed to scan CI/CD pipeline configurations, such as GitHub Actions YAML, for critical supply chain vulnerabilities. It automatically detects issues like unpinned dependencies, script injection risks, secrets exposure, and dependency confusion, helping teams harden their build systems and maintain secure software development lifecycles.

A comprehensive guide to building production-grade Laravel applications. It details architectural patterns for achieving scalability and maintainability, covering service/action separation, advanced Eloquent usage (casts, scopes), dependency injection via service containers, and robust API routing patterns.

Implements a robust, multi-factor model to calculate the criticality score of IT assets. The scoring incorporates data sensitivity, business function dependency, regulatory scope, and network exposure, moving beyond simple CVSS scores. The resulting 1-5 criticality tier directly modifies vulnerability remediation Service Level Agreements (SLAs), ensuring security resources are focused on the organization's most valuable and risky systems.

This skill details implementing Software Composition Analysis (SCA) using Snyk. It helps security teams detect known vulnerabilities, check license compliance, and automate dependency remediation within CI/CD pipelines. Learn to integrate scanning into GitHub, GitLab, and Jenkins workflows, generate automated fix PRs, and continuously monitor deployed applications to safeguard the software supply chain.

A comprehensive security tool designed to simulate and detect critical software supply chain attacks. It identifies risks such as typosquatting via Levenshtein distance, dependency confusion against private registries, package integrity failures through SHA-256 hash verification, and known vulnerabilities using pip-audit. Essential for security auditing and assessing project dependency risk.

A comprehensive, NIST/CISA-aligned workflow for structured recovery following a ransomware incident. It covers critical steps including environment isolation, forensic evidence preservation, Active Directory restoration (DSRM, krbtgt reset), backup integrity validation, and phased, dependency-based system rebuild. Essential for post-incident disaster recovery planning.

This comprehensive tool manages the complete lifecycle of ML experiments, providing robust deployment capabilities across diverse environments. It supports running training jobs on local GPUs, dedicated remote servers, Vast.ai, and serverless platforms like Modal. The workflow handles environment detection, code synchronization (rsync/git), dependency pinning, and integrates advanced logging tools (e.g., W&B), ensuring reliable, scalable, and reproducible ML training runs.

Integrates Aqua Security's Trivy scanner into CI/CD pipelines to perform automated vulnerability scanning on Docker images and related artifacts. It detects OS package CVEs, application dependency issues, and Dockerfile misconfigurations. This ensures that only secure, compliant images can proceed to registry push or production deployment by enforcing strict quality gates.