analyzing-malware-persistence-with-autoruns
Autoruns systematically identifies malware persistence mechanisms by scanning Windows Auto-Start Extensibility Points across 18+ categories including registry keys, services, scheduled tasks, and drivers. Use this skill when investigating security incidents requiring persistence analysis, building threat detection rules, performing forensic examinations of disk images, or validating SOC monitoring coverage for persistence techniques.
git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills /tmp/analyzing-malware-persistence-with-autoruns && cp -r /tmp/analyzing-malware-persistence-with-autoruns/skills/analyzing-malware-persistence-with-autoruns ~/.claude/skills/analyzing-malware-persistence-with-autorunsSKILL.md
# Analyzing Malware Persistence with Autoruns
## Overview
Sysinternals Autoruns extracts data from hundreds of Auto-Start Extensibility Points (ASEPs) on Windows, scanning 18+ categories including Run/RunOnce keys, services, scheduled tasks, drivers, Winlogon entries, LSA providers, print monitors, WMI subscriptions, and AppInit DLLs. Digital signature verification filters Microsoft-signed entries. The compare function identifies newly added persistence via baseline diffing. VirusTotal integration checks hash reputation. Offline analysis via -z flag enables forensic disk image examination.
## When to Use
- When investigating security incidents that require analyzing malware persistence with autoruns
- When building detection rules or threat hunting queries for this domain
- When SOC analysts need structured procedures for this analysis type
- When validating security monitoring coverage for related attack techniques
## Prerequisites
- Sysinternals Autoruns (GUI) and Autorunsc (CLI)
- Administrative privileges on target system
- Python 3.9+ for automated analysis
- VirusTotal API key for reputation checks
- Clean baseline export for comparison
## Workflow
### Step 1: Automated Persistence Scanning
```python
#!/usr/bin/env python3
"""Automate Autoruns-based persistence analysis."""
import subprocess
import csv
import json
import sys
def scan_and_analyze(autorunsc_path="autorunsc64.exe", csv_path="scan.csv"):
cmd = [autorunsc_path, "-a", "*", "-c", "-h", "-s", "-nobanner", "*"]
result = subprocess.run(cmd, capture_output=True, text=True, timeout=600)
with open(csv_path, 'w') as f:
f.write(result.stdout)
return parse_and_flag(csv_path)
def parse_and_flag(csv_path):
suspicious = []
with open(csv_path, 'r', errors='replace') as f:
for row in csv.DictReader(f):
reasons = []
signer = row.get("Signer", "")
if not signer or signer == "(Not verified)":
reasons.append("Unsigned binary")
if not row.get("Description") and not row.get("Company"):
reasons.append("Missing metadata")
path = row.get("Image Path", "").lower()
for sp in ["\temp\\", "\appdata\local\temp", "\users\public\\"]:
if sp in path:
reasons.append(f"Suspicious path")
launch = row.get("Launch String", "").lower()
for kw in ["powershell", "cmd /c", "wscript", "mshta", "regsvr32"]:
if kw in launch:
reasons.append(f"LOLBin: {kw}")
if reasons:
row["reasons"] = reasons
suspicious.append(row)
return suspicious
if __name__ == "__main__":
if len(sys.argv) > 1:
results = parse_and_flag(sys.argv[1])
print(f"[!] {len(results)} suspicious entries")
for r in results:
print(f" {r.get('Entry','')} - {r.get('Image Path','')}")
for reason in r.get('reasons', []):
print(f" - {reason}")
```
## Validation Criteria
- All ASEP categories scanned and cataloged
- Unsigned entries flagged for investigation
- Suspicious paths and LOLBin launch strings highlighted
- Baseline comparison identifies new persistence mechanisms
## References
- [Sysinternals Autoruns](https://learn.microsoft.com/en-us/sysinternals/downloads/autoruns)
- [SANS - Offline Autoruns Revisited](https://www.sans.org/blog/offline-autoruns-revisited-auditing-malware-persistence/)
- [Hunting Malware with Autoruns](https://nasbench.medium.com/hunting-malware-with-windows-sysinternals-autoruns-19cbfe4103c2)
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