Skill UI

This skill provides a comprehensive workflow to extract Indicators of Compromise (IOCs) from malware samples and analysis reports. It covers file hashes (SHA256, MD5), network artifacts (IPs, domains, URLs from strings and PCAPs), and host-based indicators (registry keys, file paths, mutexes) from sandbox reports. It is essential for threat intelligence sharing, building blocklists, and creating detection signatures (YARA, Snort).

A comprehensive guide and detection methodology for identifying covert communication channels utilizing DNS records. This technique analyzes Zeek dns.log for indicators such as high-entropy subdomains, excessive query volume, unusually long query lengths, and abnormal record type distributions, which suggest data exfiltration or Command and Control (C2) activity.

A comprehensive guide for deploying and managing network deception systems using industry-leading honeypot platforms like OpenCanary, T-Pot, and Cowrie. This skill helps security professionals detect unauthorized access attempts, trace lateral movement, and gather critical threat intelligence by simulating vulnerable services within a controlled environment. Ideal for enhancing network security architecture and creating early warning indicators for intrusions.

This skill guides the deployment and configuration of a TAXII 2.1 server using OpenTAXII. It enables automated, standardized exchange of STIX-formatted cyber threat intelligence (CTI) indicators between organizations. Use cases include establishing secure threat sharing pipelines, integrating with SIEM/SOAR platforms, and meeting stringent compliance requirements.

A comprehensive guide and workflow for digital forensic investigators to analyze ransomware artifacts. This process involves preserving volatile evidence (memory dumps), identifying the ransomware variant from file extensions and ransom notes, establishing the attack timeline using Prefetch and Event Logs, and extracting critical Indicators of Compromise (IoCs) such as Bitcoin addresses and Tor sites. Essential for incident response and recovery planning.

A comprehensive guide to detecting and mitigating advanced Adversary-in-the-Middle (AiTM) phishing attacks, which bypass Multi-Factor Authentication (MFA) using reverse proxies (e.g., Evilginx, EvilProxy). Learn defensive strategies including implementing FIDO2, configuring Conditional Access policies, and monitoring session hijacking indicators in SIEM/Web Proxies.

This guide details how to analyze comprehensive Zeek network logs (conn.log, smb_files.log, ntlm.log, dce_rpc.log, etc.) to detect advanced attacker techniques. It specifically targets indicators of compromise related to lateral movement, such as SMB admin share access, NTLM account spraying, and remote service execution (DCE/RPC patterns). It is a critical network forensics tool for post-incident investigation.

This skill provides a comprehensive framework for validating backup reliability. It automates processes like cryptographic hash verification, running simulated restores to isolated environments, detecting silent data corruption (bit rot), and scanning for ransomware indicators. Use it before relying on backups during a major incident or ransomware attack to ensure data recoverability and compliance.

This comprehensive guide details how to set up end-to-end observability for ClickHouse. It covers extracting key metrics using built-in system tables (e.g., query logs, merge status), integrating the metrics with Prometheus, and finally visualizing performance, throughput, and health indicators on Grafana dashboards. Essential for monitoring production-grade ClickHouse deployments and configuring reliable alerting.

This skill guides the creation of a comprehensive Service Level Objective (SLO) document. It helps define Service Level Indicators (SLIs) by identifying critical user journeys and measuring key metrics like success rate and latency. It calculates the allowed "error budget" and establishes a burn rate policy to maintain service reliability while enabling feature velocity and principled trade-offs.

This framework provides comprehensive detection capabilities for compromised cloud credentials across major platforms including AWS, Azure, and GCP. It analyzes critical threat indicators such as anomalous API activity, impossible travel patterns (impossible login locations), and unauthorized resource provisioning. Designed for incident response, security monitoring, and building robust detection rules to mitigate account takeover and credential abuse.