Skill UI

A comprehensive guide for analyzing binary exploitation techniques, covering buffer overflows, ROP chains, and memory corruption vulnerabilities. It details the use of specialized tools like pwntools, checksec, and ROPgadget for identifying and developing exploits in ELF binaries during authorized security assessments and CTF challenges. Focuses on advanced offensive security practices.

This skill guides comprehensive digital forensics investigations on compromised endpoints. It covers evidence collection (memory acquisition, disk imaging) and deep artifact analysis, including volatile data, MFT records, and prefetch files. Use it for incident response, legal evidence collection, and determining the scope of a breach by reconstructing attacker timelines.

This tool performs comprehensive security testing on GraphQL APIs by generating deeply nested, recursive, or highly repetitive queries. It specifically aims to identify Denial-of-Service (DoS) vulnerabilities and resource exhaustion issues by overwhelming the server's CPU, memory, or database connections. Essential for security auditors and penetration testers.

A comprehensive guide for digital forensics professionals on analyzing volatile memory dumps using Volatility 3. Learn to extract critical evidence, including running processes, network connections, loaded DLLs, system credentials, and detecting advanced threats like process hollowing and rootkits. Essential for incident response and malware analysis.

This automated toolkit streamlines memory forensics using the Volatility3 framework. It is designed to analyze raw memory dumps from Windows, Linux, and macOS, revealing complex threats such as process injection, hidden rootkits, malicious code artifacts, and illicit network connections that traditional disk-based methods cannot detect. Essential for real-time incident response and deep security auditing.

A comprehensive tool designed for assessing the security posture of Programmable Logic Controller (PLC) firmware. It specializes in detecting critical vulnerabilities such as hardcoded credentials, undocumented debug interfaces, backdoor functions, and memory corruption flaws. The tool supports analyzing major industrial platforms (Siemens, Allen-Bradley) by performing static and dynamic analysis, and verifying firmware integrity against known-good baselines, adhering to standards like IEC 62443. Use only in authorized lab environments.

A comprehensive guide to conducting security assessments on thick client (desktop) applications. This skill details techniques ranging from static analysis (using tools like dnSpy, IDA Pro) to dynamic analysis (process monitoring with Procmon, network interception via Burp Suite). It covers finding hardcoded credentials, identifying insecure local storage, mitigating DLL hijacking, and analyzing memory manipulation within local applications.

A comprehensive guide and workflow demonstrating how to use YARA rules for proactive threat hunting. This method helps detect unknown malware, suspicious patterns, and Indicators of Compromise (IOCs) across filesystems, memory dumps, and network artifacts, making it essential for incident response and security analysis.

A deep dive into advanced malware reverse engineering techniques. Learn how to utilize Ghidra's powerful disassembler and decompiler to analyze complex malware binaries. This guide covers identifying C2 communication protocols, extracting cryptographic routines, understanding memory injection, and analyzing low-level assembly code for core logic and evasion techniques. Essential for professional cybersecurity analysts.

An advanced debugging skill designed for AI agents. It utilizes gdb-cli to provide intelligent assistance for C/C++ programs, enabling the analysis of core dumps, debugging live processes, and investigating complex issues like crashes, deadlocks, and memory corruption. It correlates runtime state inspection with source code context for deeper insights.

A professional-grade 'Living Pipeline' that integrates advanced AI reasoning into the SDLC. It provides autonomous guardrails for system security, cloud cost management (FinOps), and Kubernetes compliance. It audits Linux Kernel patches for memory vulnerabilities, detects cost drifts in Terraform plans, and generates hardened K8s manifests from natural language policies.

This skill systematically audits a given project by analyzing its historical memory, rollout summaries, and local skill definitions. It identifies repeated complex workflows, recurring operational patterns, or areas where existing skills are stale. The audit process guides the user to recommend the highest-value skills to either add (if a new pattern emerges) or update (if current skills are outdated or incomplete), ensuring the AI agent operates with the most accurate and context-specific knowledge base for optimal project execution.