Skill UI

A comprehensive read-only client for querying the Go package discovery API (pkg.go.dev). It provides detailed documentation, API signatures, usage examples, version history, dependency graphs, and known CVE vulnerabilities for any Go module or package. Ideal for understanding external library usage, reviewing API details, or checking dependency health without needing write access.

Chainsaw is a fast, Rust-based tool for digital forensics and threat hunting. It enables analysts to rapidly perform Sigma rule checks and keyword searches across collected Windows Event Logs (.evtx) and specialized artifacts (like shimcache and SRUM). Ideal for first-response and offline analysis, it provides detection capabilities without needing a SIEM ingestion pipeline, allowing quick hypothesis testing in the field or air-gapped environments.

A comprehensive guide for threat hunting and detection engineering focused on identifying SSO and OAuth token abuse. It detects 'pass-the-cookie' and session replay attacks where attackers use stolen tokens (like cookies or refresh tokens) to move laterally across federated SaaS platforms (Entra ID, Okta) without needing credentials. Essential for post-incident scope analysis and validating T1550.001 coverage.

This skill enables comprehensive security graph mapping by ingesting both on-premises Active Directory data (via SharpHound) and cloud Entra ID data (via AzureHound) into BloodHound CE. It analyzes complex, hybrid attack paths, allowing security teams to identify critical privilege escalation chains from low-privileged accounts to Tier-0 assets, mapping findings to MITRE ATT&CK.

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 skill guides the deployment and operation of the Havoc C2 framework, enabling advanced adversary emulation. It utilizes Yaotl profiles to generate highly evasive agents (Demon) that employ sophisticated techniques like indirect syscalls and sleep obfuscation. The scope covers the full red-teaming lifecycle, including C2 setup, payload generation, post-exploitation, and lateral movement, making it ideal for authorized security testing and validating EDR detection capabilities.

A comprehensive guide to setting up the open-source Sliver C2 framework. It covers deploying the server, generating cross-platform implants and beacons, establishing resilient multi-protocol listeners (mTLS, DNS, HTTPS), and executing advanced post-exploitation and pivoting techniques using the built-in armory for adversary emulation.

This skill guides the full lifecycle of threat intelligence processing, transforming raw indicators of compromise (IOCs) from MISP feeds into actionable security detections. It covers feed curation, false positive reduction using warninglists, and automating the generation of high-fidelity rules for Suricata, Sigma, and Wazuh. Use this to mature your MISP instance from a repository into a proactive detection engine.

PyRIT (Python Risk Identification Tool) is an open-source automation framework designed for advanced, multi-turn adversarial red-teaming of conversational LLMs. It simulates real-world attack scenarios by orchestrating an attacker model and a scorer model in a feedback loop. Features include Crescendo (gradual escalation) and Tree-of-Attacks with Pruning (TAP) techniques to detect complex vulnerabilities like prompt injection and jailbreaks in stateful dialogues.

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.

This skill utilizes NVIDIA's open-source garak framework to conduct comprehensive red-teaming assessments on Large Language Models (LLMs). It tests for critical vulnerabilities such as prompt injection, jailbreaks, data leakage, and toxic content generation by sending thousands of adversarial probes. Ideal for pre-deployment security validation, API guardrail testing, and generating defensible evidence for AI risk assessments.