analyzing-malware-persistence-with-autoruns

analyzing-malware-persistence-with-autoruns is a skill for Claude Code from plurigrid/asi. It costs 44 tokens per session (954 once invoked), scanned A, original, MIT.

A guide to using Sysinternals Autoruns to inspect the Windows locations that start programs automatically. It covers registry entries, scheduled tasks, services, drivers, startup folders, and other persistence points.

In plain words
What is it for?
Use it to investigate Windows persistence, check signatures, compare before-and-after startup data, inspect offline disk images, and review file reputation.
Why use it?
Malware can restart after a reboot by hiding in many different Windows startup locations. A systematic scan helps find suspicious entries and compare a system with a known-clean baseline.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the asi plugin — 56 skills shipped together

Good fit Use it to investigate Windows persistence, check signatures, compare before-and-after startup data, inspect offline disk images, and review file reputation.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/plurigrid/asi/analyzing-malware-persistence-with-autoruns
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add plurigrid/asi --skill analyzing-malware-persistence-with-autoruns
Clone the repo
git clone --depth 1 https://github.com/plurigrid/asi

Made for: Claude Code.

Or install asi, the plugin that ships this one along with the rest of its 56 skills.

Wrote this? Show the measurements

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README.md
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Your own site
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Per session 44 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 954 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00044 $0.00954
Opus 5 $0.00022 $0.00477
Sonnet 5 $0.00009 $0.00191
Haiku 4.5 $0.00004 $0.00095

Measured 7d ago against content hash 52f7596f8a34, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

analyzing-malware-persistence-with-autoruns scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Runs shell commandslowCapability

Expected in a hook, worth knowing in a rule or an instructions file.

result = subprocess.run(cmd, capture_output=True, text=True, timeout=600)
Origin

Copies of this mod

4 near-identical copies found in the catalogue:

plugins/asi/skills/analyzing-malware-persistence-with-autoruns/SKILL.md · 101 lines

How it starts

The opening of the file, as written. The whole thing — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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}")

Read the full file on GitHub · 101 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 7d ago First seen · 101 lines · 44 tokens per session scan A 52f7596f8a34

Subscribe to this mod's changes

analyzing-malware-persistence-with-autoruns is a skill published in the GitHub repository plurigrid/asi (62 stars, last pushed 2mo ago), licensed MIT. It adds 44 tokens to every session and 954 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

Related

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