analyzing-malware-persistence-with-autoruns
Use Sysinternals Autoruns to systematically enumerate and analyze malware
Install / Use
npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-malware-persistence-with-autorunsInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
SecuritySupported Platforms
Our assessment of analyzing-malware-persistence-with-autoruns
analyzing-malware-persistence-with-autoruns scores 88/100 on our quality scale, 289th of 544 Security skills we index.
Its SKILL.md is 4.6 KB long, well organised into 8 sections with 1 code example: a solid amount of guidance for an agent.
With 33,340 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 25 days ago, so analyzing-malware-persistence-with-autoruns is actively maintained.
- It is released under the Apache-2.0 license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.
AI review by kimi-k2.7-code on 2026-09-26. Automated pattern scan on 2026-09-25. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
analyzing-malware-persistence-with-autoruns compared with similar skills
All 4 of these similar skills score higher than analyzing-malware-persistence-with-autoruns; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| analyzing-malware-persistence-with-autoruns (this skill)by mukul975 | 88 | 33.3k | 25d ago | SKILL.md |
| algorithmic-artby anthropics | 100 | 177.9k | 3d ago | SKILL.md |
| pptxby anthropics | 100 | 177.9k | 3d ago | SKILL.md |
| designby nextlevelbuilder | 100 | 130.2k | 4d ago | SKILL.md |
| ui-ux-pro-maxby nextlevelbuilder | 100 | 130.2k | 4d ago | SKILL.md |
Frequently asked questions
- How do I install analyzing-malware-persistence-with-autoruns?
- Run
npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-malware-persistence-with-autoruns. The install tabs above show the steps for each supported agent. - Which AI agents does analyzing-malware-persistence-with-autoruns work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is analyzing-malware-persistence-with-autoruns safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It is Apache-2.0-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is analyzing-malware-persistence-with-autoruns still maintained?
- The repository was last updated 25 days ago, so analyzing-malware-persistence-with-autoruns is actively maintained.
Skill content
View source on GitHubname: 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
#!/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
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Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
