Analyzing Malware Persistence With AutorunsSAFE

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The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: analyzing-malware-persistence-with-autoruns
description: Use Sysinternals Autoruns to systematically enumerate and analyze malware
  persistence mechanisms across Windows registry run keys, scheduled tasks, services,
  drivers, and startup locations. Use when hunting for persistence during Windows
  incident response, triaging a compromised endpoint, or validating that malware
  autostart entries have been fully identified and removed.
domain: cybersecurity
subdomain: malware-analysis
tags:
- autoruns
- persistence
- malware-analysis
- sysinternals
- windows
- registry
- startup
- incident-response
mitre_attack:
- T1547.001
- T1543.003
- T1053.005
- T1574.001
- T1037.001
version: '1.0'
author: mahipal
license: Apache-2.0
d3fend_techniques:
- Executable Denylisting
- Execution Isolation
- File Metadata Consistency Validation
- Content Format Conversion
- File Content Analysis
nist_csf:
- DE.AE-02
- RS.AN-03
- ID.RA-01
- DE.CM-01
---
# 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)
- [MITRE ATT&CK T1547 - Boot or Logon Autostart](https://attack.mitre.org/techniques/T1547/)

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

What the source does

Filesystem

none-observed

Network

none-observed

Shell

none-observed

Dependencies

pinned

Secrets in source

none-found

Findings (0)

No findings outside the package's declared scope.

Gates applied: no_behavioural_pass.