analyzing-malware

A safe workflow for examining suspected malware, meaning software designed to harm, spy on, or gain unauthorized access to systems. It starts with containment, then studies the file and its behavior in an isolated environment.

In plain words
What is it for?
Triaging suspicious files and alerts, identifying capabilities and command-and-control behavior, extracting indicators such as hashes or domains, and creating YARA or behavioral detections.
Why use it?
It reduces the risk of infecting real systems and helps turn a suspicious sample into evidence for an investigation.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/evilfreelancer/secs/analyzing-malware
Any agent
npx skills add EvilFreelancer/secs --skill analyzing-malware
Clone the repo
git clone --depth 1 https://github.com/EvilFreelancer/secs

Made for: Claude Code, Codex.

Per session 69 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,571 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. Scan, not verified.
Origin 98% 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 $0.00069 $0.03571
Opus 5 $0.00034 $0.01785
Sonnet 5 $0.00014 $0.00714
Haiku 4.5 $0.00007 $0.00357

Measured 2d ago against content hash bd4ec6cbad2c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

analyzing-malware 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 2d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -sL "https://defuddle.md/<url>" # scheme in the path is optional
Origin

This is a copy

98% identical to analyzing-malware — 10 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.

.agents/skills/analyzing-malware/SKILL.md · 317 lines

How it starts

The opening of the file, as written. The whole thing — 317 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Analyzing Malware

The analysis is the easy part. The part that goes wrong is containment: a sample detonated on a machine that can reach production, or an IOC published that burns an active investigation. Get the environment right first.

When to Use

  • Triaging a suspicious file, attachment, script, or dropped binary
  • Determining a sample's capability, persistence, and command-and-control
  • Extracting indicators for hunting and blocking
  • Writing YARA or behavioural detection from a specimen
  • Supporting an incident with sample-derived intelligence

When NOT to Use

  • Writing malware, droppers, loaders, or evasion code — out of scope for this skill regardless of framing
  • Pure RE of a benign binary — use analyzing-binaries
  • A raw shellcode blob with no PE/ELF header — use analyzing-binaries
  • The sample's network capture — use analyzing-network-traffic
  • Sweeping a whole web source tree for planted webshells (not one recovered sample) — use hunting-web-backdoors
  • Writing a YARA signature for the family — use writing-yara-rules
  • The wider incident — use responding-to-incidents
  • Turning findings into deployed rules — use engineering-detections
  • Pivoting sample IOCs into related infrastructure, actor tracking, or a finished intel product — use producing-threat-intelligence

Containment: Do This Before Anything Else

Control Requirement
Host Disposable VM or dedicated bare-metal, snapshot taken before execution
Network Isolated segment; simulated services (INetSim/FakeNet-NG) by default
Shares No host folder sharing, no clipboard sharing, no mounted host drives
Credentials No real accounts, no domain join, no password manager
Handling Sample stored in a password-protected archive, extension neutered (.bin, .mal)
Egress Real internet only with an explicit decision and a plan for attribution leakage

Live C2 contact tells the operator you are looking. On an active incident, do not resolve the C2 domain, submit the hash publicly, or upload the sample to a multi-scanner service until the incident lead approves it — public submission is a disclosure.

Read the full file on GitHub · 317 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. 2d ago First seen · 317 lines · 69 tokens per session scan A bd4ec6cbad2c

Subscribe to this mod's changes

analyzing-malware is a skill published in the GitHub repository EvilFreelancer/secs (10 stars, last pushed 24d ago), licensed Apache-2.0. It adds 69 tokens to every session and 3,571 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 98% identical to analyzing-malware, differing in 10 lines, and is treated as a copy.

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