analyzing-malware-persistence-with-autoruns

analyzing-malware-persistence-with-autoruns is a skill for Claude Code from Mikaru0Mystic/sectinel. It costs 44 tokens per session (1,055 once invoked), scanned A, a copy of analyzing-malware-persistence-with-autoruns, Apache-2.0.

A Windows malware-investigation procedure built around Sysinternals Autoruns, a tool that lists programs and settings started automatically.

In plain words
What is it for?
Use it to investigate incidents, compare a system with a clean baseline, check file reputations, inspect disk images, and develop detection rules.
Why use it?
It helps reveal malware that survives a restart by hiding in startup settings, services, scheduled tasks, drivers, or other Windows locations.

Skill for Claude Code

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

Part of the cybersecurity-skills plugin — 56 skills shipped together

Good fit Use it to investigate incidents, compare a system with a clean baseline, check file reputations, inspect disk images, and develop detection rules.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/mikaru0mystic/sectinel/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 Mikaru0Mystic/sectinel --skill analyzing-malware-persistence-with-autoruns
Clone the repo
git clone --depth 1 https://github.com/Mikaru0Mystic/sectinel

Made for: Claude Code.

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

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for analyzing-malware-persistence-with-autoruns

README.md
[![agentmods](https://agentmods.dev/badge/skills/mikaru0mystic/sectinel/analyzing-malware-persistence-with-autoruns/github.svg)](https://agentmods.dev/skills/mikaru0mystic/sectinel/analyzing-malware-persistence-with-autoruns)
Your own site
<a href="https://agentmods.dev/skills/mikaru0mystic/sectinel/analyzing-malware-persistence-with-autoruns"><img src="https://agentmods.dev/badge/skills/mikaru0mystic/sectinel/analyzing-malware-persistence-with-autoruns/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for analyzing-malware-persistence-with-autoruns

Your own site · 80×15
<a href="https://agentmods.dev/skills/mikaru0mystic/sectinel/analyzing-malware-persistence-with-autoruns"><img src="https://agentmods.dev/badge/skills/mikaru0mystic/sectinel/analyzing-malware-persistence-with-autoruns.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 44 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,055 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.
Origin 88% copy Near-identical to another mod 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 $0.01055
Opus 5 $0.00022 $0.00528
Sonnet 5 $0.00009 $0.00211
Haiku 4.5 $0.00004 $0.00105

Measured 11d ago against content hash 00165a5b6444, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, 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 11d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/agent.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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

This is a copy

88% identical to analyzing-malware-persistence-with-autoruns — 31 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

arsenal/Anthropic-Cybersecurity-Skills/skills/analyzing-malware-persistence-with-autoruns/SKILL.md · 126 lines

How it starts

The opening of the file, as written. The whole thing — 126 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 · 126 lines

Files

What ships with it

6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 11d ago First seen · 126 lines · 44 tokens per session scan A 00165a5b6444

Subscribe to this mod's changes

analyzing-malware-persistence-with-autoruns is a skill published in the GitHub repository Mikaru0Mystic/sectinel (11 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 44 tokens to every session and 1,055 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). It is 88% identical to analyzing-malware-persistence-with-autoruns, differing in 31 lines, and is treated as a copy.

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