Skill UI

This skill provides deep technical expertise regarding the DWARF debugging format (v3-v5) and the DWARF standard. It assists in analyzing, parsing, verifying, and generating debug information from compiled binaries. Use cases include answering questions about the DWARF specification, writing code that interacts with DWARF data, and utilizing tools like `dwarfdump` or `readelf` for structural validation and quality metric extraction.

Use this skill to perform read-only API calls for exploring, previewing, searching, and filtering structured datasets hosted on Hugging Face. It allows users to validate dataset availability, list splits, paginate large datasets, and retrieve comprehensive metadata and statistics, making it ideal for data validation and content extraction workflows.

Xquik unlocks Twitter data via REST APIs, MCP tools, and webhooks, covering tweet/user lookups, follower extraction, giveaway draws, trending topics, and accurate account monitoring for real-time automation.

This skill provides methods for reliably extracting typed, validated, and structured data from Large Language Models (LLMs), moving beyond simple text parsing. It covers best practices across major APIs (OpenAI's response_format, Anthropic's tool_use, Google's responseSchema) and local models. Key workflows include defining schemas (Pydantic/Zod), implementing constrained decoding, and building robust retry loops for production-grade data pipelines.

Examines packet captures, Zeek logs, and NetFlow data to uncover C2 channels, lateral movement, and exfiltration during security incidents, guiding analysts through capture, filtering, and IOC extraction workflows.

A comprehensive tool and guide for detecting and exploiting NoSQL injection vulnerabilities in MongoDB, CouchDB, and similar databases. It simulates advanced attacks such as authentication bypass, blind data extraction using regex, and JavaScript execution via the $where operator. Ideal for penetration testers and security researchers assessing APIs and web applications backed by NoSQL backends.

A comprehensive guide detailing the process of identifying and exploiting SQL injection vulnerabilities in web applications. The content covers manual and automated techniques, including error-based, boolean, and time-based blind injections. Users learn to fingerprint major database engines (MySQL, MSSQL, Oracle) and utilize tools like sqlmap to demonstrate data extraction and security risks during authorized penetration tests.

This guide outlines the process for forensically acquiring digital evidence from major cloud storage services, including Google Drive, OneDrive, Dropbox, and Box. The method combines API-based remote data extraction (such as audit logs and revision histories) with the collection of local endpoint sync-client artifacts. It is essential for conducting thorough incident response, security assessments, and e-discovery investigations involving cloud-synced data.

Zeek is a powerful, open-source network analysis framework that functions as a passive security monitor. It generates highly detailed, structured logs (e.g., HTTP, DNS, TLS) from raw network traffic, allowing for deep metadata extraction. This skill guides users through deploying Zeek, writing custom detection scripts, and integrating the resulting rich security logs with SIEM platforms for advanced threat detection and forensic investigations.

bdistill transforms AI interactions into a structured, queryable knowledge base. It extracts, structures, and quality-scores domain knowledge from both closed-source AI models (in-session) and local open-source models (via Ollama). Users can build comprehensive reference datasets, Q&A pairs, or generate structured training data for traditional machine learning, ensuring validated and exportable domain expertise.

This skill provides comprehensive analysis and structured data extraction for academic research papers hosted on Hugging Face and arXiv. It can read paper content in markdown format, retrieve key metadata (authors, abstracts, GitHub repos), and identify linked assets such as associated models, datasets, and Spaces. Use this when the user provides a Hugging Face or arXiv URL, or explicitly requests a summary or explanation of an AI research topic.

A comprehensive guide detailing the workflow for firmware reverse engineering. It uses tools like binwalk to identify embedded filesystems (e.g., SquashFS, CramFS), perform entropy analysis to locate hidden data, and extract components. The process covers deep inspection, credential discovery, and reporting for IoT and embedded security assessments.