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This comprehensive guide details the deployment and hardening of the Havoc C2 framework, a modern post-exploitation Command and Control system. Learn how to establish a production-grade infrastructure, including configuring Teamservers, setting up various listeners (HTTP/HTTPS/SMB), and integrating Nginx redirectors. It provides OPSEC-hardened techniques for authorized red team adversary emulation engagements.

This methodology systematically deobfuscates multi-layered PowerShell malware. It utilizes Abstract Syntax Tree (AST) analysis, dynamic execution tracing, and specialized tools (like PSDecode) to recover hidden payloads, original commands, and C2 infrastructure from scripts obfuscated with Base64, string concatenation, or complex invocation tricks. Essential for incident response and deep malware analysis.

Build automated pipelines to respond to AWS GuardDuty findings. This solution uses EventBridge to detect high-severity threats and triggers a Lambda function. The function automatically quarantines compromised resources (e.g., EC2 instances), creates forensic EBS snapshots, and sends detailed notifications via SNS, drastically reducing Mean Time To Respond (MTTR). Ideal for proactive cloud security posture management.

This script performs statistical analysis on Zeek connection logs (conn.log) to detect Command and Control (C2) beaconing patterns. It leverages the ZAT library to load data into Pandas DataFrames, calculates inter-arrival time statistics, and flags connections with low standard deviation relative to the mean. This technique is crucial for network threat hunting and security incident investigation when identifying malicious, periodic callbacks.

A comprehensive guide for deploying and operationalizing Amazon GuardDuty. It provides continuous, intelligent threat detection across core AWS services including S3, EKS, and EC2 runtime monitoring. Use this skill to investigate suspicious activity, detect compromised credentials, or build automated incident response playbooks using EventBridge and Lambda for proactive security.

A comprehensive guide for security teams on detecting and responding to unauthorized crypto mining operations in cloud environments (AWS, Azure). It details a multi-layered approach, utilizing cost anomaly detection, compute utilization monitoring, GuardDuty findings, and network flow log analysis (VPC/KQL) to identify resource hijacking attempts and suspicious activity across EC2, ECS, and EKS workloads.

This skill detects DNS-based data exfiltration by analyzing Zeek dns.log files. It identifies indicators such as high Shannon entropy subdomains, oversized TXT/NULL records, and abnormal query volumes. Use it when investigating suspected DNS tunneling or covert C2 channels to enhance threat detection capabilities.

A comprehensive skill designed for advanced security analysis, detecting malicious behaviors across mobile applications (Android/iOS). It performs multi-layered analysis, including static indicator checks (permissions, manifest), dynamic instrumentation via Frida, network traffic monitoring (C2 communication, exfiltration), and automated scanning (MobSF). Use this when investigating suspicious apps, detecting trojans, or performing malware triage.

A comprehensive skill for detecting early-stage ransomware indicators before data encryption occurs. It utilizes advanced network detection tools such as Zeek and Suricata, combined with SIEM correlation rules and threat intelligence feeds. This method monitors the entire pre-encryption kill chain, identifying precursor behaviors like initial access broker activity, Cobalt Strike C2 beaconing, credential harvesting (e.g., Mimikatz signatures), and data staging attempts, enabling timely incident response and containment.

This tool automates the extraction of embedded configuration details from Agent Tesla Remote Access Trojan (RAT) samples. It is designed to recover crucial exfiltration credentials (SMTP, FTP, Telegram), keylogger settings, and Command and Control (C2) endpoints by analyzing and deobfuscating the .NET assembly structure. Essential for threat intelligence, incident response, and malware reverse engineering.

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 provides comprehensive methods to detect Cobalt Strike beacon command-and-control (C2) traffic. It uses advanced network forensics techniques, including analyzing default TLS certificates (e.g., serial 8BB00EE), JA3/JA3S fingerprints, HTTP malleable profiles, and beacon interval jitter, leveraging Zeek logs, Suricata rules, and Python PCAP analysis. It is essential for threat hunters and SOC analysts investigating sophisticated C2 communications.