Skill UI

A specialized threat hunting skill designed to detect remnants of the PowerShell Empire post-exploitation framework. It analyzes Windows event logs (specifically Script Block and Module Logging) for key Indicators of Compromise (IOCs), such as default launcher strings, Base64 encoded payloads, known module signatures (e.g., Mimikatz), and staging URL patterns. The output provides a detailed JSON report, comprehensive timeline, and MITRE ATT&CK mapping for incident response and security validation.

Timesketch is a collaborative, open-source platform for security teams to analyze and reconstruct complex forensic timelines. It ingests and normalizes multi-source security data (logs, artifacts) using methods like Plaso, CSV, and JSONL. Users can visualize event chronology, track attack chains, and utilize advanced built-in analyzers (e.g., Sigma, Chain of Events) for comprehensive incident investigation and documentation.

A comprehensive guide to deploying and configuring Suricata, a high-performance IDS/IPS. This skill covers setting up multi-threaded packet capture, integrating Emerging Threats rulesets, generating structured EVE JSON logs, and enabling deep protocol inspection (HTTP, TLS, DNS). It enables real-time threat detection and seamless SIEM integration for centralized security monitoring.

This skill analyzes AWS CloudTrail logs to detect suspicious API call patterns, such as new event sources, geographic anomalies, or high-frequency usage. It establishes a statistical baseline of normal activity and flags deviations indicative of compromised credentials, privilege escalation, or insider threats, providing a detailed JSON report for security investigation and threat hunting.

A comprehensive skill for detecting and exploiting JavaScript prototype pollution vulnerabilities in both client-side and server-side applications. It demonstrates advanced property injection techniques to achieve critical security outcomes, including Cross-Site Scripting (XSS), Remote Code Execution (RCE), and authentication/authorization bypass, especially in Node.js environments and JSON merging scenarios.

This skill focuses on identifying and exploiting type juggling vulnerabilities in PHP web applications. It demonstrates techniques such as loose comparison bypass (==), type coercion using JSON/serialized input, and leveraging magic hash collisions to circumvent authentication mechanisms, password verification, and general application logic checks in a controlled security testing environment.

This guide details how to implement robust API schema validation using OpenAPI Specification (OAS) and JSON Schema. It enforces strict input/output contracts, preventing critical vulnerabilities such as injection attacks (SQLi, XSS), data leakage, and mass assignment by validating data types and structure at the API gateway or development level.

This guide details how to implement multi-layered API threat protection using Google Apigee. It covers critical security policies including JSON/XML content validation, OAuth 2.0 enforcement, SpikeArrest rate limiting, and advanced regex patterns to defend against OWASP Top 10 threats. Ideal for establishing robust API security controls and meeting compliance requirements.

This skill provides comprehensive knowledge on using JSON Web Tokens (JWT) for secure authentication and authorization. It covers implementing various cryptographic signing algorithms (such as HS256, RS256, ES256, and EdDSA), validating signatures, enforcing claim constraints (like expiration time), and implementing robust defenses against common JWT vulnerabilities, including algorithm confusion and the 'none' algorithm attack. Ideal for building secure, scalable web APIs.

Automate comprehensive vulnerability management by deploying and operating Greenbone/OpenVAS. This skill guides the use of the python-gvm library to programmatically manage the entire scanning lifecycle: creating scan targets, executing complex vulnerability scans via the Greenbone Management Protocol (GMP), monitoring progress, and parsing detailed XML reports into actionable JSON findings. Ideal for security assessments and compliance checks.

This comprehensive skill guides the user through monitoring various running experiments across different platforms (SSH, Vast.ai, Modal). It provides structured steps to check running processes, collect logs, extract structured JSON results, and pull detailed metrics from Weights & Biases (W&B). Finally, it summarizes findings, compares against baselines, and suggests next steps.

This skill automates the generation of high-quality, publication-ready figures and comparison tables from raw experimental data (CSV, JSON, etc.). It supports various plot types, including line plots, bar charts, scatter plots, heatmaps, and box plots, ensuring consistent style (DPI 300, PDF format) suitable for academic submissions. Users provide a figure plan and raw data, and the system generates the necessary code to visualize results.