Skill UI

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 PowerShell toolset performs advanced post-exploitation, reconnaissance, persistence, and data exfiltration against Microsoft 365/Entra ID tenants using the Microsoft Graph API. It operationalizes stolen Graph tokens to enumerate users, dump policies, escalate privileges, and search sensitive data across mailboxes, SharePoint, and Teams. Essential for authorized red teaming engagements.

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.

This specialized skill reviews user interface animations, motion patterns, and interactive code (CSS, Framer Motion, etc.) against a strict, high-craft standard. It evaluates not only functionality but also performance, accessibility, physical correctness, and adherence to motion design principles. Use it when reviewing diffs related to transitions, keyframes, or gestures to ensure the motion feels right, not just that it runs.

Trivy is an open-source, comprehensive scanner used to find vulnerabilities (CVEs), misconfigurations, secrets, and license issues across multiple targets. It is essential for implementing 'shift-left' security gates in CI/CD pipelines, scanning container images, Infrastructure-as-Code (IaC) like Terraform/Kubernetes, and generating/re-scanning SBOMs for supply chain transparency.

A specialized tool for generating sophisticated, strategic HTML presentations. It integrates data visualization using Chart.js, adheres to design tokens for consistency, ensures responsive layouts, and incorporates proven copywriting formulas and slide strategies, making your pitch decks highly impactful for marketing and business needs.

This guide provides a structured approach to red-teaming Large Language Models (LLMs) to detect sensitive data leakage from system prompts. It simulates advanced attacks—including prompt injection, instruction override, and encoding tricks—to identify embedded secrets, API keys, and proprietary business logic. Essential for validating adherence to OWASP LLM07 and securing AI applications against data exfiltration.

A comprehensive red-teaming skill for assessing the security posture of Retrieval-Augmented Generation (RAG) pipelines. It systematically probes two critical injection surfaces: poisoned retrieved context (indirect prompt injection) and embedding manipulation. Use this skill to validate retrieval guardrails, ensure data leak prevention, and demonstrate vulnerabilities in LLM-powered knowledge assistants.

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.