Skill UI

This skill simulates and detects critical software supply chain attacks, including typosquatting via Levenshtein distance, dependency confusion detection against private registries, and package integrity verification using SHA-256 hashing. It also performs comprehensive vulnerability scanning against known CVEs using pip-audit. It is essential for security assessments, compliance audits, and incident response when validating software component trustworthiness.

A comprehensive guide and Python tool for reverse engineering Rust-compiled malware. It addresses unique Rust binary challenges, such as non-null-terminated strings and monomorphization. The script extracts crate dependencies, identifies suspicious capabilities (like networking or encryption), and filters for malware-related strings, assisting security researchers in deep binary analysis.

A comprehensive guide to idiomatic Rust patterns and best practices for building safe, high-performance, and maintainable applications. Covers core concepts like ownership and borrowing, robust error handling using thiserror and anyhow, state modeling with enums, zero-cost abstraction via traits and generics, and safe concurrent programming practices.

A comprehensive guide to writing robust and maintainable tests in Rust. It covers various advanced testing patterns, including Unit, Integration, Async, and Property-Based testing. Learn how to apply the TDD (Test-Driven Development) cycle (RED-GREEN-REFACTOR) to enhance code reliability and ensure high code coverage.

Harbor is an open-source container registry designed for robust security and compliance. This guide details the comprehensive workflow for securing your container ecosystem by implementing advanced features such as vulnerability scanning (Trivy), image signing (Notary/Cosign), Role-Based Access Control (RBAC), and content trust policies. Learn how to enforce image provenance and maintain strict access control in Kubernetes environments.

This skill provides comprehensive guidance on hardening GitHub Actions CI/CD pipelines against modern supply chain attacks, credential theft, and privilege escalation. It teaches best practices such as pinning actions to immutable SHA digests, minimizing GITHUB_TOKEN permissions, preventing script injection from untrusted inputs, and implementing required approval gates for critical deployments.

This playbook guides Security Operations Center (SOC) analysts through a comprehensive, multi-step process for triaging and prioritizing security incidents. It covers receiving alerts from SIEM/EDR, enriching data using threat intelligence feeds (VirusTotal, AbuseIPDB), classifying the incident type (MITRE ATT&CK mapping), and calculating a severity score based on asset criticality and data sensitivity. The workflow culminates in automating ticket creation and triggering immediate response procedures via tools like PagerDuty.

A comprehensive guide for preparing SaaS and cloud infrastructure companies for SOC 2 Type I and Type II audits. Covers mapping Trust Service Criteria (TSC), generating control matrices, performing thorough gap analysis, collecting evidence, and assessing overall compliance readiness across Security, Availability, Confidentiality, and Privacy domains. Essential for demonstrating operational trustworthiness to enterprise clients.

AKF is the native metadata format specifically designed for tracking AI-generated or AI-modified content. It allows users to stamp files (including DOCX, PDF, images, and code) with detailed trust scores, source provenance, and compliance metadata. This tool is essential for professional workflows requiring strict auditing, compliance assurance, and verifiable data lineage, especially concerning regulations like the EU AI Act, HIPAA, and SOX.

Use Clarvia AEO (Agent Experience Optimization) to score any MCP server, API, or CLI tool for agent-readiness. It evaluates 15,400+ AI tools across four dimensions—API accessibility, data structuring, agent compatibility, and trust signals—ensuring the components are robust enough for advanced AI agent workflows and dynamic selection processes.

This guide outlines the implementation of Remote Browser Isolation (RBI) as a core component of a Zero Trust architecture. It details policies for URL risk classification, Data Loss Prevention (DLP) controls, and Content Disarm and Reconstruction (CDR). This is essential for hardening web access, protecting against zero-day exploits, phishing, and preventing data exfiltration from untrusted web content.

This framework implements robust input and output validation guardrails for LLM-powered applications. It prevents prompt injection, detects and redacts PII, filters toxic content, and validates model outputs against defined schemas. Use it when deploying AI agents that handle sensitive data or require strict adherence to corporate policies, ensuring a secure and trustworthy AI interaction layer.