mcpField
A
analyzing-malware-persistence-with-autoruns

analyzing-malware-persistence-with-autoruns

github.com/mukul975Security35.2k358 installsUpdated 8w ago
Repository

About analyzing-malware-persistence-with-autoruns

A procedural skill for investigating Windows malware persistence with Sysinternals Autoruns and Autorunsc. It covers scanning autostart locations, filtering signed entries, comparing a clean baseline, and checking file reputation.

Key features

  1. 01Scan Windows autostart locations
  2. 02Flag unsigned and suspicious entries
  3. 03Compare results with a baseline
  4. 04Check hashes with VirusTotal
  5. 05Analyze disk images offline

Use cases

  1. 01Investigate persistence during incident response
  2. 02Find newly added autostart mechanisms
  3. 03Validate monitoring coverage for persistence techniques

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill analyzing-malware-persistence-with-autoruns

After installing, type/analyzing-malware-persistence-with-autorunsin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

LICENSE
assets/
template.md
references/
api-reference.md
standards.md
workflows.md
scripts/
agent.py

Details

From the project README

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
#!/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

Comments

Markdown supported