investigating-ransomware-attack-artifacts

investigating-ransomware-attack-artifacts is a skill for Claude Code, Codex from adriannoes/awesome-agentic-ai. It costs 36 tokens per session (4,329 once invoked), scanned B, original, MIT.

A digital-forensics process for examining evidence left by a ransomware attack. Ransomware is malicious software that encrypts files, often to demand payment.

In plain words
What is it for?
Use it to identify the ransomware variant, investigate how attackers got in, determine which systems and files were affected, and assess whether recovery or decryption is possible.
Why use it?
It helps preserve evidence before systems are changed or shut down and clarifies how far the attack spread. The findings can support recovery decisions, law-enforcement reports, and insurance claims.

Skill for Claude CodeCodex

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

Good fit Use it to identify the ransomware variant, investigate how attackers got in, determine which systems and files were affected, and assess whether recovery or decryption is possible.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/adriannoes/awesome-agentic-ai/investigating-ransomware-attack-artifacts
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 adriannoes/awesome-agentic-ai --skill investigating-ransomware-attack-artifacts
Clone the repo
git clone --depth 1 https://github.com/adriannoes/awesome-agentic-ai

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 investigating-ransomware-attack-artifacts

README.md
[![agentmods](https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/investigating-ransomware-attack-artifacts/github.svg)](https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/investigating-ransomware-attack-artifacts)
Your own site
<a href="https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/investigating-ransomware-attack-artifacts"><img src="https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/investigating-ransomware-attack-artifacts/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 investigating-ransomware-attack-artifacts

Your own site · 80×15
<a href="https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/investigating-ransomware-attack-artifacts"><img src="https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/investigating-ransomware-attack-artifacts.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 36 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,329 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 2 findings, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high YARA Match · line 400
    YARA rule matched a known malware signature (reverse shell, backdoor, ransomware, C2 framework, or info stealer).
    Fix: Remove the malware payload or compromised file entirely. Investigate how it entered the skill and audit all other artifacts for additional indicators of compromise.
  • medium Privilege Escalation · line 85
    Commands invoke sudo or root privileges. Verify this elevated access is necessary and justified.
    Fix: Avoid sudo/root unless strictly required. Prefer least-privilege patterns. If elevation is needed, document the justification and scope.
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 $0.00036 $0.04329
Opus 5 $0.00018 $0.02165
Sonnet 5 $0.00007 $0.00866
Haiku 4.5 $0.00004 $0.00433

Measured 8d ago against content hash 69645e50cba7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade B, and why

investigating-ransomware-attack-artifacts scanned grade B 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 8d 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.

Asks for rootmediumPrivilege escalation

A mod that escalates privileges can change anything on the machine, not only the project.

# Linux: sudo insmod lime.ko "path=/evidence/memory.lime format=lime"
cursor-claude-codex/skills/anthropic-cybersecurity-skills/skills/investigating-ransomware-attack-artifacts/SKILL.md · 418 lines

How it starts

The opening of the file, as written. The whole thing — 418 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Investigating Ransomware Attack Artifacts

When to Use

  • Immediately after discovering ransomware encryption on systems
  • When performing forensic analysis to understand the full scope of a ransomware incident
  • For identifying the ransomware variant and determining if decryption is possible
  • When tracing the attack chain from initial access to encryption
  • For documenting evidence to support law enforcement and insurance claims

Prerequisites

  • Forensic images of affected systems (preserve before remediation)
  • Memory dumps captured before system shutdown (if available)
  • Ransom notes and encrypted file samples
  • Network traffic captures from the attack period
  • Windows Event Logs, Prefetch files, and registry hives
  • Access to ransomware identification tools (ID Ransomware, No More Ransom)
  • Isolated sandbox environment for malware analysis

Workflow

Step 1: Preserve Evidence and Identify the Ransomware Variant

# CRITICAL: Do NOT restart systems. Preserve memory first if possible.
# Encryption keys may still be in memory.

# Capture memory from running systems
# Windows: DumpIt.exe (generates memory.raw)
# Linux: sudo insmod lime.ko "path=/evidence/memory.lime format=lime"

# Collect ransom note
cp /mnt/evidence/Users/*/Desktop/README*.txt /cases/case-2024-001/ransomware/ransom_notes/
cp /mnt/evidence/Users/*/Desktop/DECRYPT*.txt /cases/case-2024-001/ransomware/ransom_notes/
cp /mnt/evidence/Users/*/Desktop/HOW_TO*.txt /cases/case-2024-001/ransomware/ransom_notes/
find /mnt/evidence/ -name "*.hta" -o -name "*DECRYPT*" -o -name "*RANSOM*" -o -name "*README*" \
   2>/dev/null | head -20 > /cases/case-2024-001/ransomware/note_locations.txt

# Collect sample encrypted files (for identification)
find /mnt/evidence/Users/ -name "*.encrypted" -o -name "*.locked" -o -name "*.crypted" \
   -o -name "*.crypt" -o -name "*.enc" | head -10 > /cases/case-2024-001/ransomware/encrypted_samples.txt

# Copy sample encrypted files
mkdir -p /cases/case-2024-001/ransomware/samples/
head -5 /cases/case-2024-001/ransomware/encrypted_samples.txt | while read f; do
    cp "$f" /cases/case-2024-001/ransomware/samples/
done

# Identify ransomware variant using file extension and ransom note
python3 << 'PYEOF'
import os, hashlib, json

ransomware_indicators = {
    '.lockbit': 'LockBit',
    '.blackcat': 'BlackCat/ALPHV',
    '.royal': 'Royal',
    '.akira': 'Akira',
    '.clop': 'Cl0p',
    '.conti': 'Conti',
    '.ryuk': 'Ryuk',
    '.revil': 'REvil/Sodinokibi',
    '.maze': 'Maze',
    '.phobos': 'Phobos',
    '.dharma': 'Dharma/CrySIS',
    '.stop': 'STOP/Djvu',
    '.hive': 'Hive',
    '.blackbasta': 'Black Basta',
    '.play': 'Play',
}

# Check encrypted file extensions
samples_dir = '/cases/case-2024-001/ransomware/samples/'
for f in os.listdir(samples_dir):
    ext = os.path.splitext(f)[1].lower()
    variant = ransomware_indicators.get(ext, 'Unknown')
    sha256 = hashlib.sha256(open(os.path.join(samples_dir, f), 'rb').read()).hexdigest()
    print(f"File: {f}")
    print(f"  Extension: {ext}")
    print(f"  Suspected Variant: {variant}")
    print(f"  SHA-256: {sha256}")
    print()

# Parse ransom note for IoCs
note_dir = '/cases/case-2024-001/ransomware/ransom_notes/'
for note in os.listdir(note_dir):
    with open(os.path.join(note_dir, note), 'r', errors='ignore') as f:
        content = f.read()
        print(f"\n=== Ransom Note: {note} ===")
        # Extract bitcoin addresses
        import re
        btc = re.findall(r'[13][a-km-zA-HJ-NP-Z1-9]{25,34}|bc1[a-zA-HJ-NP-Z0-9]{25,39}', content)
        tor = re.findall(r'[a-z2-7]{56}\.onion', content)
        emails = re.findall(r'[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}', content)

        if btc: print(f"  Bitcoin addresses: {btc}")
        if tor: print(f"  Tor addresses: {tor}")
        if emails: print(f"  Contact emails: {emails}")
PYEOF

Read the full file on GitHub · 418 lines

Files

What ships with it

3 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. 8d ago First seen · 418 lines · 36 tokens per session scan B 69645e50cba7

Subscribe to this mod's changes

investigating-ransomware-attack-artifacts is a skill published in the GitHub repository adriannoes/awesome-agentic-ai (57 stars, last pushed 14d ago), licensed MIT. It adds 36 tokens to every session and 4,329 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it B with 1 finding (asks for root). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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