Skill UI

Analyzes behavioral reports from security sandboxes (Cuckoo, AnyRun) to detect advanced anti-analysis and evasion techniques. It specifically identifies indicators such as timing checks, hypervisor artifact queries, user interaction patterns, and environment fingerprinting. This tool is essential for threat hunting, enhancing detection rules, and conducting deep malware triage.

A comprehensive skill for detecting advanced malware techniques, including DLL injection, process hollowing, APC injection, and thread hijacking. Utilizes memory forensics (Volatility), API monitoring (Sysmon), and behavioral analysis to identify malicious code artifacts and suspicious process activities in a deep defense context.

A guide and implementation pattern for deploying Nozomi Networks Guardian sensors. This solution enables passive, non-disruptive monitoring of Operational Technology (OT) and Industrial Control Systems (ICS). It provides critical asset visibility, behavioral anomaly detection, protocol-aware monitoring, and vulnerability assessment, making it essential for building robust OT Security Operations Centers (SOCs) and ensuring compliance without risking live operations.

CAPE is an open-source sandbox derived from Cuckoo, designed for automated dynamic malware analysis. It features advanced behavioral instrumentation, capturing system changes, network traffic (PCAP), and specialized parsers to extract malware configurations (e.g., Emotet, Cobalt Strike). Use this skill for incident response, security assessments, and validating security controls against complex payloads and evasion techniques.

This skill provides a comprehensive workflow for analyzing malicious software to extract actionable Indicators of Compromise (IOCs). It covers static analysis (PE parsing, hashing, string extraction) and dynamic analysis techniques. Users learn how to identify file hashes, network indicators (C2 IPs, domains), registry modifications, and behavioral artifacts, ultimately formatting the findings into standard STIX 2.1 formats for sharing and incident response.

This system detects ransomware by combining multiple advanced techniques: real-time entropy analysis, file system I/O monitoring, and behavioral heuristics. It identifies abnormal mass file modification patterns, sudden spikes in data entropy (indicating encryption), and suspicious process activities like shadow copy deletion. Ideal for building advanced EDR detection layers to catch zero-day and unknown ransomware variants.

This skill is designed for deep forensic analysis of asynchronous processing chains, specifically focusing on 'drift'—behavioral or configuration differences between a synchronous request path and subsequent worker-executed tasks. Use it to trace payloads, inspect worker-only state, follow retry mechanisms, handle dead-letter queues, or connect enqueued items to eventual side effects (e.g., file writes, cache updates, emails). It is a specialized downstream tool, requiring prior orchestration context.

Comprehensive workflow for analyzing suspected malware via static, dynamic, and behavioral techniques. Covers IOC extraction, YARA/Sigma rule generation, sandbox automation, and anti-analysis bypassing.