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A dedicated tool for forensic analysis of Windows PowerShell Script Block Logs (Event ID 4104) captured in EVTX files. It reconstructs multi-block scripts, applying advanced detection heuristics such as entropy analysis and pattern matching to identify obfuscated commands, encoded payloads (Base64), download cradles, and AMSI bypass attempts, crucial for threat hunting and incident response.

A comprehensive toolkit designed for cybersecurity professionals to deobfuscate malicious JavaScript code. It reverses complex encoding layers (Base64, Hex, Unicode), eval chains, and control flow obfuscation techniques found in phishing pages, web skimmers, and dropper scripts, revealing the original malicious logic for thorough forensic analysis and threat intelligence gathering.

This skill provides systematic methods and advanced techniques to deobfuscate multi-layered PowerShell malware. It utilizes Abstract Syntax Tree (AST) analysis, dynamic execution tracing, and specialized tools to reveal hidden payloads, C2 infrastructure, and the original malicious logic. It is essential for security analysts, red teamers, and incident response teams performing deep malware analysis.

A comprehensive guide and framework for detecting attacker lateral movement within enterprise networks. It details the use of network flow analysis (Zeek), authentication log review (Windows Event Logs, Kerberos), and dedicated SIEM correlation rules (Splunk, Elastic) to identify techniques like Pass-the-Hash and RDP hopping. Ideal for threat hunters and security engineers building detection pipelines.

This skill provides a systematic methodology for detecting Command and Control (C2) beaconing patterns in network traffic. It utilizes advanced statistical techniques, including Coefficient of Variation (CV) and jitter analysis, applied to network flow logs (Zeek, proxy, firewall). It is crucial for proactive threat hunting and incident response to identify compromised endpoints communicating periodically with malicious infrastructure.

This skill detects anti-forensic timestomping by analyzing NTFS Master File Table (MFT) entries. It compares timestamps from the $STANDARD_INFORMATION attribute (user-modifiable) against the $FILE_NAME attribute (kernel-protected). Discrepancies, such as SI Created < FN Created, strongly indicate malicious manipulation and defense evasion. This methodology is crucial for advanced threat hunting and digital forensic investigations.

A comprehensive guide for cybersecurity professionals detailing the process of collecting, parsing, and correlating system, application, and security logs (Windows EVTX, Linux syslog, web logs). It helps reconstruct event timelines, identify breach activity, and establish evidence for forensic reports.

Zeek is a powerful, open-source network security monitoring framework that generates high-fidelity structured logs and metadata from raw network traffic. This skill covers deploying Zeek, analyzing various protocol logs (HTTP, DNS, TLS, etc.), writing custom detection scripts to identify anomalies, and integrating resulting security insights with SIEM platforms for comprehensive threat detection and forensic investigation.

This skill detects malicious Command and Control (C2) communications tunneled through the DNS protocol. It analyzes DNS query logs for indicators such as DNS tunneling tools (Iodine, dnscat2), Domain Generation Algorithms (DGA), and encoded payloads within TXT/CNAME records. Techniques include Shannon entropy analysis of subdomains, statistical anomaly detection, and machine learning classification. Ideal for network security analysts conducting deep threat hunting and forensic investigations.

A comprehensive guide on implementing Firebase Analytics in Flutter applications. Covers setup, automatic screen view tracking, logging custom and predefined events, setting user properties, and adhering to data privacy best practices for accurate user flow analysis and conversion funnel tracking.

A systematic guide for debugging complex issues in Go applications, including crashes, deadlocks, concurrency errors, and performance bottlenecks. This skill teaches the 'Golden Rules' of debugging: reproducing bugs, isolating variables, and finding the true root cause rather than applying symptom fixes. It covers advanced techniques using pprof for profiling, the Delve debugger (dlv), and Go's built-in race detector, providing a structured methodology for professional software development.

Guides learners through reconnaissance, scanning, vulnerability analysis, exploitation, and reporting phases of authorized penetration testing, pairing command examples with tool choices and professional deliverables.