Skill UI

This skill provides a structured methodology and Python implementation for monitoring and analyzing data leak sites (DLS) associated with ransomware groups. It helps security analysts track victim postings, extract threat intelligence on group tactics, assess sector-specific risks, and understand evolving ransomware threat landscapes for proactive defense.

This skill automates the process of parsing Cyber Threat Intelligence (CTI) reports to extract adversary behaviors. It maps these behaviors to MITRE ATT&CK techniques and structures them as STIX 2.1 Attack Pattern objects. The resulting library supports detection engineering by generating rule templates (Sigma, YARA) for proactive defense and threat-informed security control implementation.

A multi-layered defense system designed to detect sophisticated prompt injection attacks targeting LLM-powered applications. It combines regex pattern matching for known signatures, heuristic scoring for structural anomalies, and advanced DeBERTa-based classification. Ideal for building robust input validation layers, securing RAG pipelines, and performing proactive AI security scanning.

A comprehensive, pre-deployment, defense-in-depth security audit tool for Solidity smart contracts built with Foundry. It combines static analysis (Slither, Aderyn), symbolic execution (Mythril), property-based fuzz testing, and key hygiene checks to proactively detect critical vulnerabilities like reentrancy, access control flaws, and arithmetic bugs before deployment to any EVM chain.

This skill provides a structured approach to monitoring and analyzing data leak sites (DLS) maintained by ransomware groups. By extracting structured data on victim postings, threat group tactics, and sector-specific details, users can assess current ransomware risk, track attack trends, and proactively build robust defense strategies.