Skill UI

A comprehensive guide detailing the systematic workflow for analyzing malicious Linux ELF binaries. It covers essential techniques including static analysis (using readelf, elftools), dynamic tracing (strace, ltrace), and deep reverse engineering (GDB) of various threats like botnets, cryptominers, and ransomware targeting Linux environments, containers, and cloud infrastructure.

Automate security regression testing for Large Language Model (LLM) applications by integrating Promptfoo and DeepTeam into CI/CD pipelines. This skill enforces a critical security gate, automatically testing endpoints against OWASP LLM Top 10, OWASP Agentic threats, and common jailbreaks/prompt injections. It ensures that security patches do not regress over time due to prompt or model changes, providing continuous risk monitoring.

This skill guides the deployment and strategic use of honeytokens and canarytokens (decoy credentials, files, URLs, etc.). These high-fidelity decoys are designed to detect unauthorized access, insider threats, or adversary reconnaissance by triggering alerts upon any interaction, providing early warning deep within the kill chain.

Falco is a powerful CNCF project for real-time runtime security monitoring. This guide teaches authors how to write and deploy custom detection rules using Falco's robust YAML rule engine and modern eBPF driver. It is designed to detect critical threats such as container escapes, namespace manipulation, privileged mounts, and anomalous syscalls in Kubernetes and Docker environments, significantly hardening the overall container security posture.

This skill provides a comprehensive, cross-platform workflow for auditing UEFI firmware security. It detects advanced threats like bootkits (e.g., BlackLotus, Bootkitty) and Secure Boot bypasses by verifying the integrity of the platform's trust chain. Key checks include confirming Secure Boot status, assessing the currency and application of DBX revocations, and examining the protection of critical EFI variables using specialized tools. Essential for hardware security assessments and forensic investigation.

This skill guides the end-to-end process of supply chain security by generating standards-compliant Software Bills of Materials (SBOMs) in CycloneDX and SPDX formats. It details using Syft to create inventories, correlating them with vulnerability intelligence via Grype, enforcing CI/CD gates based on severity, and establishing verifiable provenance using Cosign signing. Essential for modern DevSecOps practices.

This skill guides the secure migration from classical cryptography (RSA, ECC) to quantum-resistant algorithms (PQC). It covers building a Cryptographic Bill of Materials (CBOM), identifying data at risk (HNDL), and deploying hybrid key exchange protocols like X25519MLKEM768 to ensure long-term data security against quantum threats.

This guide demonstrates how to use the pycti Python client to model complex cyber threat intelligence within the OpenCTI platform. It structures threat actors, intrusion sets, campaigns, and TTPs into a unified STIX 2.1 knowledge graph. The skill is essential for correlating fragmented data from multiple sources (IOCs, reports) into a comprehensive, queryable adversary picture, supporting advanced threat hunting and detection engineering.

This comprehensive tool suite provides high-fidelity parsers for key Windows artifacts, including MFT, Registry hives, Prefetch files, and ShellBags. Designed for digital forensics and incident response, it converts raw system evidence into structured CSV/JSON formats. The output is optimized for feeding into Timeline Explorer, enabling analysts to build comprehensive, correlated timelines and establish a clear chain of events.

KAPE is a powerful, Windows-native triage tool used for Digital Forensics and Incident Response (DFIR). It executes in two phases: 'Targets' collect raw forensic artifacts (like registry hives, event logs, and prefetch files) from live systems, while 'Modules' parse this collected data into normalized, analyst-ready CSV/JSON formats. It enables fast, defensible, and scalable artifact collection, especially when full disk imaging is impractical.