detecting-living-off-the-land-with-lolbas

name	detecting-living-off-the-land-with-lolbas
description	Detect Living Off the Land Binaries (LOLBins/LOLBAS) abuse including certutil, regsvr32, mshta, and rundll32 via process telemetry, Sigma rules, and parent-child process analysis
domain	cybersecurity
subdomain	threat-detection
tags	["lolbas","lolbins","sigma-rules","process-monitoring","sysmon","endpoint-detection","threat-hunting"]
version	1.0
author	mahipal
license	Apache-2.0

Detecting Living Off the Land with LOLBAS

Overview

Living Off the Land Binaries, Scripts, and Libraries (LOLBAS) are legitimate system utilities abused by attackers to execute malicious actions while evading detection. This skill covers detecting abuse of certutil.exe, regsvr32.exe, mshta.exe, rundll32.exe, msbuild.exe, and other LOLBins using process telemetry from Sysmon and Windows Event Logs, combined with Sigma rule-based detection.

Prerequisites

• Sysmon or Windows Security Event Log (Event ID 4688) with command-line logging enabled
• Sigma rule conversion tool (sigmac or sigma-cli)
• SIEM platform (Splunk, Elastic, or similar) for log ingestion
• Python 3.8+ with pySigma library
• LOLBAS project reference database

Steps

1. Establish LOLBin Watchlist — Build a prioritized list of monitored binaries (certutil, mshta, regsvr32, rundll32, msbuild, installutil, cmstp, wmic, bitsadmin)
2. Collect Process Telemetry — Ingest Sysmon Event ID 1 (Process Create) and Windows 4688 events with full command-line capture
3. Build Sigma Detection Rules — Create Sigma rules matching suspicious command-line arguments, network activity, and parent-child process anomalies for each LOLBin
4. Analyze Parent-Child Relationships — Flag unexpected parent processes spawning LOLBins (e.g., Excel spawning certutil, Word spawning mshta)
5. Score and Prioritize Alerts — Apply risk scoring based on argument anomaly, parent process, execution path, and network indicators
6. Generate Detection Report — Produce a structured report of all LOLBin abuse detections with MITRE ATT&CK mapping

Expected Output

• JSON report listing detected LOLBin abuse events with severity scores
• MITRE ATT&CK technique mapping for each detection (T1218, T1105, T1140, T1127)
• Parent-child process anomaly analysis
• Sigma rule match details with raw event data