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.
npx skills add HermeticOrmus/LibreSecOps-Claude-Code --skill malware-analysis-methodologygit clone --depth 1 https://github.com/HermeticOrmus/LibreSecOps-Claude-CodeWrote 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.
[](https://agentmods.dev/skills/hermeticormus/libresecops-claude-code/malware-analysis-methodology)<a href="https://agentmods.dev/skills/hermeticormus/libresecops-claude-code/malware-analysis-methodology"><img src="https://agentmods.dev/badge/skills/hermeticormus/libresecops-claude-code/malware-analysis-methodology/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.
<a href="https://agentmods.dev/skills/hermeticormus/libresecops-claude-code/malware-analysis-methodology"><img src="https://agentmods.dev/badge/skills/hermeticormus/libresecops-claude-code/malware-analysis-methodology.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00065 | $0.01876 |
| Opus 5.5 | $0.00026 | $0.00750 |
| Sonnet 5.5 | $0.00013 | $0.00375 |
| Haiku 4.5 | $0.00006 | $0.00188 |
Grade A, and why
malware-analysis-methodology scanned grade A with 0 findings 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 12d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Malware Analysis Methodology
Complete reference for the defensive malware analysis workflow, from safe handling and triage through static analysis, dynamic analysis, and reporting.
Knowledge Base
Analysis Phases
Malware analysis follows a structured progression from least-interactive to most-interactive techniques. Each phase builds on the previous, and analysts should extract maximum value from safer (non-execution) methods before moving to dynamic analysis.
Phase 1: Triage (5-15 minutes)
- File type identification via magic bytes (
filecommand, not extension) - Hash generation (MD5, SHA-1, SHA-256, ssdeep)
- Reputation lookups (VirusTotal, MalwareBazaar, CIRCL hashlookup)
- Quick string scan for obvious indicators
- Decision: known malware (skip to IOC extraction) vs unknown (proceed to Phase 2)
Phase 2: Static Analysis (30 minutes - several hours)
- String extraction: ASCII, Unicode, stack strings (FLOSS), encoded strings
- PE/ELF header analysis: compile timestamp, sections, imports/exports
- Entropy analysis: per-section entropy to detect packing/encryption
- Import analysis: categorize API calls by function (network, file, process, crypto, registry)
- Resource analysis: embedded files, icons, version info, manifests
- Packer/compiler identification: signature matching, heuristic detection
- Disassembly: function identification, control flow, key routines
- Decompilation: pseudo-code review for high-level logic understanding
Phase 3: Dynamic Analysis (1-4 hours)
- Environment preparation: isolated VM/sandbox, network simulation, monitoring tools
- Execution monitoring: process creation, API calls, file/registry activity
- Network capture: DNS requests, HTTP/HTTPS traffic, raw connections
- Memory analysis: dumping unpacked payloads, injected code, credentials
- Behavioral profiling: persistence installation, lateral movement attempts, data collection
Phase 4: Reporting and IOC Extraction
- MITRE ATT&CK technique mapping
- IOC extraction and categorization
- Detection signature creation (YARA, Snort/Suricata, Sigma)
- Analyst report (technical) and executive summary
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.
- 12d ago Changed · +5 lines · +65 tokens per session ada95324490d
- 1mo ago First seen · 139 lines · 0 tokens per session scan A 499535589ee7
malware-analysis-methodology is a skill published in the GitHub repository HermeticOrmus/LibreSecOps-Claude-Code (4 stars, last pushed 9d ago), licensed MIT. It adds 65 tokens to every session and 1,876 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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