Skill UI

This tool audits Kubernetes pod configurations to detect potential container escape misconfigurations. It checks for dangerous settings like privileged flags, excessive capabilities, host path mounts, shared namespaces, and cgroup abuses. Use it for comprehensive security assessments, compliance checking, or generating pre-enforcement security posture reports.

EvilGinx3 is an advanced Adversary-in-the-Middle (AiTM) framework designed for red teaming simulations. It goes beyond traditional credential harvesting by acting as a transparent proxy to intercept the entire authentication flow, including session cookies and Multi-Factor Authentication (MFA) tokens. This capability allows security professionals to assess the robustness of an organization's security posture against sophisticated account takeover attacks.

A comprehensive skill for Security Operations Center (SOC) teams and incident responders. It detects advanced lateral movement techniques, including Pass-the-Hash, PsExec, WMI, and RDP pivoting, by correlating Windows Security logs, Sysmon data, and network flow records within a SIEM. This capability is mapped to MITRE ATT&CK TA0008 and is essential for tracking an attacker's internal progression after initial compromise. Not intended for external attack detection.

This skill outlines the systematic process of integrating new data sources (e.g., Firewalls, EDR, Cloud, AD) into a SIEM platform. It covers planning, configuring collectors, building parsers, normalizing data fields (e.g., CIM), and validating data quality to enhance security monitoring and incident detection capabilities.

This skill automates red team operations using the Covenant C2 framework, providing comprehensive capabilities for authorized adversary simulation. It covers the full attack lifecycle, including listener setup, deploying agents (grunts), executing tasks on compromised hosts, and tracking lateral movement via the Covenant API. Ideal for professional penetration testing and security auditing.

This skill simulates security incidents using discussion-based tabletop exercises for Security Operations Center (SOC) teams. It is designed to test incident response procedures, evaluate cross-functional communication workflows (e.g., Legal, PR, Executive), and assess decision-making capabilities under pressure, all without touching production environments. Ideal for compliance validation, playbook refinement, and comprehensive team training.

This tool builds comprehensive forensic super-timelines by using Plaso to correlate events across diverse sources. It aggregates data from file system metadata, event logs, browser history, and registry artifacts into a unified chronological view. This capability is essential for complex digital forensic investigations requiring cross-source event correlation or detailed activity sequence reporting.

A comprehensive guide for performing systematic security assessments on web applications. Following the OWASP Web Security Testing Guide (WSTG), this process identifies critical vulnerabilities such as broken authentication, authorization flaws (IDOR), SQL injection, and Cross-Site Scripting (XSS). The workflow covers reconnaissance, mapping, and advanced testing techniques using tools like Burp Suite and sqlmap, ensuring deep coverage beyond automated scanner capabilities. Ideal for pre-production security validation and compliance audits.

This comprehensive guide covers the principles and implementation steps for building Progressive Web Apps (PWAs). Learn to integrate essential components like Web App Manifests and Service Workers to ensure your web application offers a reliable, fast, and truly offline-capable experience, mimicking the feel of a native mobile app. Ideal for enhancing web resilience and installability.

This comprehensive tool manages the complete lifecycle of ML experiments, providing robust deployment capabilities across diverse environments. It supports running training jobs on local GPUs, dedicated remote servers, Vast.ai, and serverless platforms like Modal. The workflow handles environment detection, code synchronization (rsync/git), dependency pinning, and integrates advanced logging tools (e.g., W&B), ensuring reliable, scalable, and reproducible ML training runs.

PydanticAI is a robust Python framework that integrates Pydantic's type-checking and validation capabilities into Large Language Models (LLMs). It allows developers to build production-ready AI agents that guarantee structured, validated outputs, moving beyond simple raw strings. Key features include supported tool calling, dependency injection for testability, and multi-model compatibility across major providers like OpenAI, Anthropic, and Gemini. Use this when reliability and correct data structure are paramount.

This skill systematically probes an AI model's core behavioral patterns across six critical dimensions, including reasoning, refusal, formatting, and grounding. It generates a comprehensive, styled HTML report with radar charts and actionable insights, allowing users to understand a model's true capabilities, compare different models, or perform compliance and red-team assessments without needing an external API key.