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Use Sysinternals Autoruns to systematically identify and analyze malware persistence mechanisms across registry keys, scheduled tasks, services, drivers, and startup locations on Windows systems.
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Basado en la clasificación ocupacional SOC
Produces a structured Windows system report that synthesises performance and security signals into a single Markdown document and writes it to disk. Combines sysinfo, tasklist, network connections, recent event log entries, Defender state, autoruns, hotfix list, and disk usage into an executive summary plus per-axis sections plus actionable findings. Activates when the user asks Lucy to "generate / produce / build / write / compile / elaborate" a "report / informe / reporte / auditoría / overview" of "the machine / la maquina / mi equipo / mi laptop / the host" with optional persistence target (escritorio / desktop / archivo / .md / .pdf).
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Perform static analysis of Android APK malware samples using apktool for decompilation, jadx for Java source recovery, and androguard for permission analysis, manifest inspection, and suspicious API call detection.
Parses API Gateway access logs (AWS API Gateway, Kong, Nginx) to detect BOLA/IDOR attacks, rate limit bypass, credential scanning, and injection attempts. Uses pandas for statistical analysis of request patterns and anomaly detection. Use when investigating API abuse or building API-specific threat detection rules.
Queries Azure Monitor activity logs and sign-in logs via azure-monitor-query to detect suspicious administrative operations, impossible travel, privilege escalation, and resource modifications. Builds KQL queries for threat hunting in Azure environments. Use when investigating suspicious Azure tenant activity or building cloud SIEM detections.
| name | analyzing-malware-persistence-with-autoruns |
| description | Use Sysinternals Autoruns to systematically identify and analyze malware persistence mechanisms across registry keys, scheduled tasks, services, drivers, and startup locations on Windows systems. |
| domain | cybersecurity |
| subdomain | malware-analysis |
| tags | ["autoruns","persistence","malware-analysis","sysinternals","windows","registry","startup","incident-response"] |
| mitre_attack | ["T1547","T1053","T1543","T1546"] |
| 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"] |
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.
#!/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}")