KAPE vs Sigma
GitHub Stats
About KAPE
KAPE (Kroll Artifact Parser and Extractor) is a triage tool that finds and parses forensic artifacts in minutes. Developed by Eric Zimmerman at Kroll, it operates in two phases: collection targets gather specific files and artifacts from a system, while module processors parse those artifacts into human-readable formats. KAPE ships with hundreds of pre-built targets covering browser history, event logs, registry hives, prefetch files, SRUM data, scheduled tasks, and virtually every forensic artifact type on Windows. Its module system integrates with Eric Zimmerman's tools (LECmd, PECmd, MFTECmd, etc.) and community parsers to process collected data automatically. KAPE is designed for speed - it can collect and parse a full forensic triage from a live system in under 10 minutes, making it the go-to tool for rapid incident response triage.
About Sigma
Sigma is a generic and open signature format for SIEM systems, analogous to what YARA is for files and Snort is for network traffic. Sigma rules describe log events in a YAML-based format that is independent of any specific SIEM product. Using the sigma-cli converter (pySigma), rules can be translated into native query languages for Splunk (SPL), Elasticsearch (Lucene/KQL), Microsoft Sentinel, QRadar, CrowdStrike, Carbon Black, Grep, and over 30 other backends. The Sigma rule repository contains thousands of community-contributed detection rules covering MITRE ATT&CK techniques, common malware behaviors, lateral movement, persistence mechanisms, and suspicious system activity. Security teams use Sigma to write detection logic once and deploy it across their entire detection infrastructure, regardless of which SIEM products they use. The format is maintained by the SigmaHQ project and has become the de facto standard for shareable detection rules.
Platform Support
Tags
KAPE only
Sigma only