Skill UI

A comprehensive design specification detailing 98 rules for building Command Line Interface (CLI) tools that are safe, reliable, and easily consumable by AI agents. It covers structured JSON output formats, standardized error handling (to stderr), robust input contracts, safety guardrails (e.g., preventing path traversal), and tiered compliance levels (Agent-Friendly, Agent-Ready, Agent-Native) for seamless integration into AI workflows.

A comprehensive strategy for regression testing in AI-assisted development. It focuses on identifying systematic blind spots, such as schema inconsistencies between sandbox and production paths, and integrating automated bug checks into the development workflow. This guide teaches how to build robust, database-free API tests to ensure code quality when AI models contribute to the codebase.

A comprehensive forensic workflow for detecting persistent, deep-seated malware, such as bootkits and advanced rootkits. The analysis covers multiple layers, including boot sectors (MBR/VBR), UEFI firmware modules, and kernel memory forensics. It is essential for investigating sophisticated, nation-state level threats that evade standard anti-malware and EDR solutions.

A comprehensive guide and workflow for digital forensics investigators to analyze raw email headers. This tool helps trace the true origin of suspicious emails, verify sender authenticity, and detect advanced spoofing techniques by validating crucial protocols like SPF, DKIM, and DMARC. It covers everything from header parsing to domain infrastructure analysis and IP reputation checks.

A comprehensive skill for performing deep security audits on Ethereum smart contracts. Utilizes both static analysis (Slither) and symbolic execution (Mythril) to detect critical vulnerabilities such as reentrancy, integer overflows, and access control issues. This process is crucial for ensuring the security and immutability of financial assets before mainnet deployment.

A comprehensive guide for digital forensics analysts to investigate compromised Linux systems. This workflow details the collection and analysis of critical system artifacts, including authentication logs, shell histories, SSH keys, and system configurations. Use this methodology during incident response to detect rootkits, unauthorized persistence mechanisms, and reconstruct full attacker activity.

A comprehensive workflow for performing static and dynamic analysis of malicious PDF documents. It utilizes tools like peepdf, pdfid, and pdf-parser to extract embedded JavaScript, shellcode, and suspicious objects. Ideal for triaging phishing attachments, analyzing exploit documents, and building threat signatures in a controlled forensic environment.

A comprehensive guide to utilizing Cuckoo Sandbox for deep dynamic analysis of suspicious malware samples. This workflow walks through sample submission, real-time monitoring, and programmatic extraction of behavioral indicators, including process activity, network communications (DNS, HTTP), file system changes, and registry modifications, essential for threat intelligence and IOC extraction.

This tool parses NetFlow v9 and IPFIX records to conduct deep network security analysis. It is crucial for investigating security incidents by building traffic baselines and applying statistical methods. Key detection capabilities include identifying port scanning, data exfiltration attempts, command and control (C2) beaconing patterns, and general volumetric anomalies in network traffic.

Examines packet captures, Zeek logs, and NetFlow data to uncover C2 channels, lateral movement, and exfiltration during security incidents, guiding analysts through capture, filtering, and IOC extraction workflows.

This comprehensive skill analyzes Zeek conn.log and NetFlow data to proactively detect advanced indicators of ransomware activity. It identifies critical threats such as Command and Control (C2) beaconing patterns, connections to TOR exit nodes, large-scale data exfiltration flows, and suspicious DNS anomalies. It is essential for threat hunting and complex security incident response.

This guide details a comprehensive workflow for digital forensic investigations focusing on Amcache.hve registry hive. It teaches how to use AmcacheParser to extract evidence of program execution, application installation, and driver loading, including correlating SHA-1 hashes with threat intelligence and reconstructing timelines. This is crucial for DFIR work to identify deleted executables and malicious activity.