Skill UI

This skill provides a comprehensive solution for monitoring brand impersonation attacks across multiple digital vectors. It systematically scans domains, social media platforms, mobile app stores, and the dark web to detect phishing campaigns, typosquatting, and unauthorized brand usage. It is essential for security teams conducting proactive threat intelligence gathering and vulnerability assessments to safeguard brand integrity.

This skill provides comprehensive functionality for monitoring and mapping adversary-controlled assets, such as C2 servers, phishing domains, and exploit kit hosts. By leveraging tools like Passive DNS, Certificate Transparency logs, and specialized scanners (Shodan/Censys), analysts can discover, track, and pivot through complex threat actor infrastructure over time, significantly enhancing security operations and threat intelligence maturity.

This skill analyzes ransomware cryptocurrency payment flows by utilizing major blockchain intelligence APIs (like Chainalysis and WalletExplorer). It identifies wallet clusters, tracks movements through obfuscation services (mixers, tumblers), and determines fund flows to exchanges, supporting forensic investigations and law enforcement attribution efforts.

This guide outlines a comprehensive workflow for detecting and preventing the exposure of sensitive AWS credentials (access keys, session tokens) within source code repositories, CI/CD pipelines, and configuration files. It utilizes TruffleHog for deep historical scanning and integrates git-secrets for robust pre-commit hooks, significantly reducing the risk of credential theft and unauthorized account access.

A comprehensive security auditing tool designed to identify over-permissive Role-Based Access Control (RBAC) roles and potential service-account token abuse paths within a Kubernetes cluster. It systematically reviews cluster bindings, effective permissions, and common escalation primitives using advanced tools like `kubectl auth can-i`, `rbac-police`, and `rakkess`, ensuring adherence to the principle of least privilege.

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.

A comprehensive security tool designed to detect and defend against subtle prompt injection attacks hidden within untrusted multi-modal content, such as web pages, PDFs, and images. It scans for obfuscated payloads (e.g., hidden CSS, metadata, zero-width characters) by combining content normalization, heuristic analysis, and dedicated ML detectors, ensuring that LLM agents only consume sanitized, trustworthy input.

This skill simulates high-impact container breakout techniques, demonstrating how to achieve root compromise on the underlying host operating system. It covers exploiting misconfigurations (e.g., privileged pods, hostPath mounts, exposed Docker sockets) and leveraging known vulnerabilities in runC/containerd, making it essential for authorized penetration testing and assessing the blast radius of a compromised microservice.

A powerful offensive security toolkit for red-teaming and penetration testing. It systematically enumerates and exploits various misconfigurations within Active Directory Certificate Services (AD CS) using Certipy. This allows attackers to forge privileged certificates, perform PKINIT authentication, and achieve domain compromise and privilege escalation, even without knowing user passwords. Ideal for validating security hardening.

Pacu is an open-source, modular AWS exploitation framework designed for authorized cloud penetration testing and red-teaming. It functions as a cloud-pentest analogue to Metasploit, enabling users to enumerate AWS resources, scan for privilege escalation paths, and automate the exploitation of IAM vulnerabilities, persistence mechanisms, and data exfiltration. Use this skill to assess the blast radius of compromised credentials in a controlled, authorized environment.

This skill is designed for proactive firmware forensics and advanced threat hunting. It analyzes the EFI System Partition (ESP) to detect sophisticated, pre-OS persistence mechanisms, such as UEFI bootkits (e.g., BlackLotus, ESPecter). Detection methods include verifying file hashes against a trusted golden baseline, checking Secure Boot signatures, scanning with YARA, and flagging structural anomalies within the ESP.

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.