Analyzing Malware Persistence With Autoruns

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

Trigger phrases:

• "analyzing malware persistence with autoruns"

• "Use Sysinternals Autoruns to systematically identify and analyze malware persist"

• 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

1. Isolate the sample — ensure the malware is in a sandboxed environment with no network access
2. Record file metadata — hash the sample and note file type, size, and compile timestamp
3. Static analysis — examine strings, imports, and disassembled code without execution
4. Dynamic analysis — execute in a monitored sandbox and record behavior (file, registry, network)
5. Document IOCs — extract indicators of compromise and write the analysis report

Step 1: Automated Persistence Scanning

#!/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

When NOT to Use

• You need to perform the attack, not analyze it (use performing-* skills)
• Task is about detection, not analysis (use detecting-* skills)
• You need to implement controls (use implementing-* skills)
• Task is about threat hunting, not post-incident analysis (use hunting-* skills)
• You don't have access to the artifacts/logs to analyze
• Task requires real-time monitoring (use SOC tools)

Red Flags

• Performing actions without explicit written authorization from the asset owner
• Testing against production systems without a defined scope and rules of engagement
• Analyzing malware on a machine connected to the production network
• Failing to isolate the analysis environment from the internet
• Executing samples without proper containment (VM, sandbox)

Verification

• All steps executed successfully against a test environment before production use
• Output documented with screenshots or logs demonstrating expected behavior
• Sample hash recorded and verified (MD5, SHA-1, SHA-256)
• Analysis environment confirmed isolated from production network
• Indicators of compromise (IOCs) extracted and documented

References

• Sysinternals Autoruns
• SANS - Offline Autoruns Revisited
• Hunting Malware with Autoruns
• MITRE ATT&CK T1547 - Boot or Logon Autostart

Process

1. Analyze the task requirements
2. Apply domain expertise
3. Verify output quality

Anti-Rationalization Table