Skill UI

This skill analyzes DNS query logs to detect sophisticated threats such as data exfiltration via DNS tunneling, Domain Generation Algorithm (DGA) usage, and covert Command and Control (C2) channels. It utilizes advanced techniques like entropy analysis, query volume anomaly detection, and subdomain length analysis within SIEM platforms, helping SOC teams identify threats that bypass traditional network security controls.

A comprehensive skill for performing deep security audits on Ethereum smart contracts. Utilizes both static analysis (Slither) and symbolic execution (Mythril) to detect critical vulnerabilities such as reentrancy, integer overflows, and access control issues. This process is crucial for ensuring the security and immutability of financial assets before mainnet deployment.

This skill analyzes Indicators of Compromise (IOCs)—such as IP addresses, domains, and file hashes—by querying multiple threat intelligence platforms (VirusTotal, AbuseIPDB, MISP). It determines maliciousness confidence, assigns blocking priorities, and attributes threats to campaigns, crucial for incident response, threat triage, and making informed security decisions.

A powerful toolkit utilizing Objection and Frida for authorized mobile penetration testing. It enables deep runtime analysis of iOS applications, allowing users to inspect sensitive data in the keychain, filesystem, and memory. Key capabilities include bypassing client-side protections such as SSL pinning and jailbreak detection without requiring source code access.

This tool parses Kubernetes API server audit logs (JSON lines) to detect critical security events. It specifically targets unauthorized access, secret enumeration, RBAC escalation, privileged pod creation, and shell access (exec/attach). Use it for incident response, threat hunting, or building SIEM detection rules.

This guide details the comprehensive process of using the Linux Audit framework (auditd) to detect advanced security threats. It covers deploying specific rules to monitor critical system files, detecting unauthorized privilege escalation, process injection, and suspicious system calls. Users can then leverage ausearch and aureport to efficiently query, reconstruct timelines, and summarize findings for forensic analysis and compliance auditing.

Comprehensive digital forensic analysis guide for Linux systems. It covers the collection and examination of critical artifacts such as authentication logs, shell histories, user configurations, system files (passwd, shadow), and persistence mechanisms to effectively detect security compromises, unauthorized access, and malicious activity.

A comprehensive cybersecurity tool designed to analyze malicious VBA and XLM macros embedded within Microsoft Office documents (Word, Excel, PowerPoint). It facilitates deep forensic investigation by extracting, deobfuscating, and tracing the full attack chain, including identifying auto-execution triggers, payload download URLs, and file writing techniques. Useful for malware analysts investigating phishing campaigns and maldocs.

This skill provides a comprehensive guide to using the Malpedia API for advanced malware intelligence analysis. Users can track malware family relationships, analyze variant evolution, extract associated YARA rules for detection, and map connections to specific threat actors. It is essential for security researchers and SOC analysts building robust threat models.

This skill provides a comprehensive workflow for detecting and analyzing malware persistence mechanisms on Windows systems. It automates the use of Sysinternals Autoruns via scripting to scan hundreds of Auto-Start Extensibility Points (ASEPs), including registry keys, services, scheduled tasks, and drivers. The process flags suspicious entries like unsigned binaries, suspicious paths, or dangerous command-line arguments, making it an essential tool for security incident response and threat hunting.

This skill analyzes behavioral reports (Cuckoo/AnyRun) to detect anti-analysis techniques used by malware, such as timing checks, VM artifact queries, user interaction monitoring, and environment fingerprinting. It provides a structured method for security researchers and SOC analysts to understand malware's true capabilities and detect evasion attempts.

This skill outlines the comprehensive process of memory forensics on compromised Linux systems. It guides users through acquiring volatile memory using the LiME kernel module and analyzing the resulting image with the Volatility 3 framework. Key artifacts extracted include process lists, network connections, bash history, and loaded kernel modules, making it an essential technique for incident response, threat hunting, and security investigations.