analyzing-malware-persistence-with-autoruns

analyzing-malware-persistence-with-autoruns is a skill for Claude Code, Codex from Youngmaidainon/Agent-Level-Up. It costs 74 tokens per session (1,105 once invoked), scanned A, a copy of analyzing-malware-persistence-with-autoruns, MIT.

A Windows malware-investigation procedure using Sysinternals Autoruns to list places where programs start automatically, such as registry entries, scheduled tasks, services, drivers, and startup folders.

In plain words
What is it for?
Use it during Windows incident response, endpoint triage, malware-persistence hunting, and checks of security-monitoring coverage.
Why use it?
It helps investigators find malware that starts again after a computer reboots. It also supports comparing a system with a clean baseline and checking file reputation.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it during Windows incident response, endpoint triage, malware-persistence hunting, and checks of security-monitoring coverage.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/youngmaidainon/agent-level-up/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 Youngmaidainon/Agent-Level-Up --skill analyzing-malware-persistence-with-autoruns
Clone the repo
git clone --depth 1 https://github.com/Youngmaidainon/Agent-Level-Up

Made for: Claude Code, Codex.

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/youngmaidainon/agent-level-up/analyzing-malware-persistence-with-autoruns/github.svg)](https://agentmods.dev/skills/youngmaidainon/agent-level-up/analyzing-malware-persistence-with-autoruns)
Your own site
<a href="https://agentmods.dev/skills/youngmaidainon/agent-level-up/analyzing-malware-persistence-with-autoruns"><img src="https://agentmods.dev/badge/skills/youngmaidainon/agent-level-up/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/youngmaidainon/agent-level-up/analyzing-malware-persistence-with-autoruns"><img src="https://agentmods.dev/badge/skills/youngmaidainon/agent-level-up/analyzing-malware-persistence-with-autoruns.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 74 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,105 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 100% 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 $0.00074 $0.01105
Opus 5 $0.00037 $0.00553
Sonnet 5 $0.00015 $0.00221
Haiku 4.5 $0.00007 $0.00111

Measured 10d ago against content hash 0c2313ca57d3, 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 10d 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

100% identical to analyzing-malware-persistence-with-autoruns — 0 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.

cyber-security/ctf/analyzing-malware-persistence-with-autoruns/SKILL.md · 130 lines

How it starts

The opening of the file, as written. The whole thing — 130 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 · 130 lines

Files

What ships with it

5 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. 10d ago First seen · 130 lines · 74 tokens per session scan A 0c2313ca57d3

Subscribe to this mod's changes

analyzing-malware-persistence-with-autoruns is a skill published in the GitHub repository Youngmaidainon/Agent-Level-Up (3 stars, last pushed 16d ago), licensed MIT. It adds 74 tokens to every session and 1,105 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). It is 100% identical to analyzing-malware-persistence-with-autoruns, differing in 0 lines, and is treated as a copy.

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