Skill UI

A comprehensive guide to deploying cloud-native deception across AWS, Azure, and GCP. This skill utilizes decoy resources—such as canary IAM keys, honey object storage buckets, and decoy secrets—whose sole purpose is to generate high-fidelity alerts the instant they are interacted with by an attacker. It detects cloud reconnaissance, credential theft, and lateral movement by wiring detection through native logging services (CloudTrail, Sentinel, Cloud Audit Logs), ensuring near-zero false positives for the SOC.

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 details the process of building and maintaining a comprehensive anti-phishing training program. It covers establishing baseline susceptibility assessments, deploying regular, progressive simulations, and providing interactive, role-based learning modules (using platforms like KnowBe4 or Proofpoint). The focus is on measuring and improving the human layer of defense against social engineering and sophisticated phishing attempts, thereby fostering a continuous security culture.

This skill automates the entire phishing incident response workflow using the Splunk SOAR REST API. It parses suspicious email headers and bodies to extract artifacts (URLs, IPs, sender details), creates a structured incident container, triggers a comprehensive automated investigation playbook, and compiles a final verdict report for security teams.

Implements HashiCorp Vault's dynamic secrets engine to automatically generate, lease, and rotate short-lived credentials for databases (e.g., Postgres, MySQL), AWS IAM keys, and PKI certificates. This eliminates the risk associated with storing static secrets, ensuring compliance with zero-trust principles and automating the entire secret lifecycle.

A comprehensive guide for conducting authorized vishing (voice phishing) pretext calls. This technique, utilized in red-teaming, simulates an attacker impersonating a trusted authority (e.g., IT support, vendor) to test an organization's human security controls. It measures employee adherence to verification protocols and highlights vulnerabilities in staff security awareness.

Provides a comprehensive guide to implementing Zero Trust Network Architecture on Google Cloud Platform (GCP) using Identity-Aware Proxy (IAP). It enforces rigorous, per-request identity verification and context-aware authorization for services like Compute Engine, App Engine, and Cloud Run. This ensures that only authenticated users who meet specific criteria (e.g., device posture, corporate location, time window) can access protected resources, eliminating reliance on public IPs or VPNs.

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 specialized tool for scientific data visualization, acting as a visualization advisor to analyze data, recommend chart types, prevent common errors, and generate publication-grade figures.

Stratus Red Team is an open-source tool designed for detection engineering and purple teaming. It programmatically detonates granular, documented offensive techniques across major cloud platforms (AWS, Azure, GCP, and Kubernetes). It validates existing security detections (like CloudTrail/GuardDuty) by simulating real attacker activity in a controlled, reversible environment. The tool ensures deterministic lifecycles, guaranteeing that all created resources are cleaned up after testing.

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.

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.