malware-analysis
Skill46 starsChanged 2 months agoMITView on GitHub
Orchestrate the complete malware analysis lifecycle across triage, dynamic analysis, detection engineering, and report writing. Use as the single entry point for any malware analysis task — routes to specialized sub-skills by file type and phase, carries findings between phases, and supports multi-sample batch workflows.
14 other projects use a version of this.
Adopted by
Most recently taken up by
- lza6/claw-code-tingfengtheir own version, first seen Nov 1, 2026
- lushun2014/lushibo-skillstheir own version, first seen Oct 15, 2026
- 2233admin/reverse-skill-evolvertheir own version, first seen Oct 15, 2026
- zhaoxuya520/reverse-skill-privatetheir own version, first seen Oct 8, 2026
- DorianGallo/reverse-skilltheir own version, first seen Oct 8, 2026
- Liberty91LTD/cti-skillstheir own version, first seen Sep 30, 2026
Used with
Projects with it also use attack-chain, binary-diff and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
DorianGalloSkillattack-chain
Also in 6 projects that use this
DorianGalloSkillbinary-diff
跨版本符号迁移与二进制差分。当你有旧版本的符号/逆向结果,需要快速迁移到新版本时使用。 适用场景:内核缺 PDB 用旧版符号推导、程序更新后批量迁移函数名、应用更新后快速定位新偏移。 核心方法:用 LLM 做结构化差异比对,程序化输入输出,成本极低(200 函数 ~1 元)。 触发关键词:符号迁移、bindiff、跨版本、PDB 缺失、函数偏移迁移、symbol migration、binary diff、版本对比。
Also in 6 projects that use this
Roshu18Skillpentest-tools
Tool selection policy for BearStrike based on target type, scan risk, and signal strength.
Also in 6 projects that use this
hardw00tSkillllm-security
LLM and AI application security testing skill for prompt injection (direct, indirect, multimodal), system-prompt extraction, RAG poisoning, memory poisoning, MCP server injection, skill-file injection, agentic tool misuse, computer-use UI injection, and excessive agency. Authorization required — this skill tests AI systems you are explicitly permitted to assess. Triggers on requests to test LLM / AI-agent / RAG / MCP / computer-use security, perform prompt injection, extract system prompts, poison RAG or memory, audit agent tool use, or evaluate AI guardrails.
Also in 6 projects that use this
- +8 more from DorianGallo
Other versions14 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 14
- zhaoxuya520/reverse-skill-private★ 40ksame name
- zhaoxuya520/reverse-skill★ 38ksame name
- hypnguyen1209/offensive-claude★ 401same name
- tsale/awesome-dfir-skills★ 323same name
- z91772524-ai/pojia-next-mac★ 39same name
- Liberty91LTD/cti-skills★ 35same name
- 2233admin/reverse-skill-evolver★ 26same name
- Snausage0x45/ClaudeSkills★ 6same name
- lza6/claw-code-tingfeng★ 5same name
- DorianGallo/reverse-skill★ 2same name
4 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository6 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- detection-engineerSkill
- malware-dynamic-analysisSkill
- malware-report-writerSkill
- malware-triageSkill
- specialized-file-analyzerSkill
The file
Show its rules and text
We split this skill into the rules it gives an agent
15 rules. 0 are common, 5 are distinctive, and 10 are very specific to this project.
0
Common
Most of the 6 edited versions we read keep these.
5
Distinctive
This author's own choices. Worth a look.
10
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 38
Run --self-test on any of them if in doubt.
- Very specific: line 60
When routing by file type, use the file command output.
- Distinctive: line 93
After each phase completes:
- Distinctive: line 100
Never auto-chain phases: Every transition requires user confirmation.
- Very specific: line 104
Before dynamic analysis, hand the user the runbook from malware-dynamic-analysis/SKILL.md Part A, tailored with the triage predictions …
- Very specific: line 108
If the user returns with PML/PCAP/EVTX, give the conversion command from the dynamic skill's Converting Binary Evidence table (tshark and …
- Distinctive: line 158
Create: when the user begins an engagement (first sample provided)
- Distinctive: line 169
Sequential deep analysis: Run the full phase sequence on high-priority samples one at a time, confirming with the user at each phase …
- Distinctive: line 170
State tracking: Update state file per-sample so the user can see which samples are triaged, analyzed, and reported
- Very specific: line 174
All IOCs in state files and reports must be defanged (hxxp://, [.]com, [@])
- Very specific: line 190
Session restart: Read analysis_state.md to restore context and resume from the last recorded phase
- Very specific: line 193
Benign sample: If triage determines a sample is clean/benign, mark its phase as Benign in the state file, note the reasoning, and move to …
- Very specific: line 194
Unrecognized file type: If file output doesn't match any known routing pattern, default to malware-triage/SKILL.md for manual assessment.
- Very specific: line 195
State file conflicts: If an existing analysis_state.md is found, ask whether to resume the existing engagement or start a new one (with a …
- Very specific: line 196
Running from the skill repo: If the working directory appears to be this skill repository itself (contains malware-triage/, …
“Common” is measured: kept by at least 6 in 10 of the 6 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Malware Analysis Orchestrator
Single entry point for malware analysis engagements. Routes to specialized sub-skills, carries findings between phases, and manages multi-sample workflows.
How This Works
You describe what you need — "analyze this sample", "I have 5 files to triage", "create detection rules from my findings" — and this orchestrator:
- Determines which sub-skill to use based on your file type and intent
- Runs the analysis using that sub-skill: Claude executes the static tooling, parses exported evidence, writes rules and reports itself
- Records findings in a state file (
analysis_state.md) - Recommends the next phase when the current one completes
- Waits for your confirmation before proceeding
You never need to invoke sub-skills directly.
Execution Model
- Claude does the work on the host. Hashing,
file, PE parsing, strings, IOC extraction, macro/PDF/script deobfuscation, .NET decompilation, Procmon/Sysmon/tshark parsing, rule authoring and testing, report writing — all run by Claude with Bash. Do not turn a step into "ask the user to run X and paste the output" unless the tool is missing and cannot be installed. - The only thing the analyst does by hand is execute the sample in the isolated VM and export text evidence.
malware-dynamic-analysisproduces the runbook for that. - Never execute a sample or any extracted stage on the host. Static tooling only. Never upload a sample anywhere without explicit consent (hash lookups are fine).
- Locate skill files. The sub-skill
SKILL.mdfiles and the scripts below ship in this skill's directory tree. SetR="${CLAUDE_PLUGIN_ROOT:-<dir containing this SKILL.md>}"once — when installed as a plugin$CLAUDE_PLUGIN_ROOTpoints at the install; otherwise it is this skill folder. The working directory is the user's analysis workspace, so read sub-skills and run scripts by absolute path, e.g.python3 "$R"/scripts/ioc_extract.pyand read"$R"/malware-triage/SKILL.md. Bundled scripts (paths below are relative to
$R):Script Used by Purpose scripts/ioc_extract.pyall phases extract + defang IOCs from any text ( --format csv/json,--refang)malware-triage/scripts/pe_info.pytriage PE headers, sections, entropy, imports, packing verdict, signature, overlay, resources (needs pefile)malware-triage/scripts/hash_calculator.pytriage MD5/SHA1/SHA256 malware-dynamic-analysis/scripts/procmon_summary.pydynamic Procmon CSV → process tree, file/registry writes, network, persistence flags malware-dynamic-analysis/scripts/sysmon_summary.pydynamic Sysmon JSON/CSV/evtx_dump → tree, network + beaconing, DNS, injection, persistence Run
--self-teston any of them if in doubt.- Host tool check at engagement start (once), then degrade gracefully and say what is missing:
command -v file strings upx 7z yara tshark olevba oledump.py pdfid.py ilspycmd js-beautify readelf jq; python3 -c "import pefile" 2>&1 | tail -1 - Big outputs go to files under the engagement workspace; inspect with
wc -l,head,grep, and the summary scripts — nevercata strings dump or a Procmon CSV.
Routing Logic
| Signal | Routes To |
| Unknown file / "what is this?" / initial assessment | malware-triage |
| PE executable after triage, needing behavior monitoring | malware-dynamic-analysis |
| .NET / Office / PDF / script / archive / LNK / ELF / HTA / ISO / IMG / VHD / VHDX | specialized-file-analyzer |
| "Create detection rules" / post-analysis phase | detection-engineer |
| "Write the report" / final documentation phase | malware-report-writer |
| YARA rules specifically | malware-report-writer (not detection-engineer) |
Triage is always the entry point for new samples. The table above describes which analysis skill follows triage.
File Type Priority Order
When routing by file type, use the file command output. Check in this order — first match wins:
- "Mono/.Net assembly" → read and follow
specialized-file-analyzer/SKILL.md - "Microsoft Office Document" → read and follow
specialized-file-analyzer/SKILL.md - "PDF document" → read and follow
specialized-file-analyzer/SKILL.md - "ELF" → read and follow
specialized-file-analyzer/SKILL.md - "PE32" / "PE64" (only if .NET was NOT matched) → read and follow
malware-triage/SKILL.md, thenmalware-dynamic-analysis/SKILL.md - "MS Windows shortcut" (LNK) → read and follow
specialized-file-analyzer/SKILL.md - ASCII text / script content → read and follow
specialized-file-analyzer/SKILL.md - Archive formats (Zip, RAR, 7z) → read and follow
specialized-file-analyzer/SKILL.md - HTML Application (.hta) → read and follow
specialized-file-analyzer/SKILL.md - ISO/IMG disk images → read and follow
specialized-file-analyzer/SKILL.md(mount/extract, then analyze contents) - VHD/VHDX virtual hard disks → read and follow
specialized-file-analyzer/SKILL.md(mount/extract, then analyze contents) - "data" / zero-byte / unrecognized → read and follow
malware-triage/SKILL.mdfor manual assessment
.NET is the key ambiguity: file outputs both "PE32" and "Mono/.Net assembly" for .NET assemblies. Always check for .NET before checking for PE.
Phase Sequence
Each sample follows this sequence:
Triage → [Dynamic Analysis OR Specialized File Analysis] → Detection Engineering → Report Writing- Triage is always first — read and follow
malware-triage/SKILL.md - Dynamic analysis for PE executables — read and follow
malware-dynamic-analysis/SKILL.md - Specialized file analysis for non-PE files (.NET, Office, PDF, scripts, archives, LNK, ELF) — read and follow
specialized-file-analyzer/SKILL.md - Detection engineering consolidates IOCs into Sigma/Suricata rules — read and follow
detection-engineer/SKILL.md - Report writing is always last — read and follow
malware-report-writer/SKILL.md
Phase Transitions (Suggest-Next Mode)
After each phase completes:
- Summarize what was found in the current phase
- Update
analysis_state.mdwith findings and IOCs - Recommend the next skill with reasoning based on findings
- Wait for user confirmation before proceeding
Never auto-chain phases. Every transition requires user confirmation.
VM Isolation Boundary
Before dynamic analysis, hand the user the runbook from malware-dynamic-analysis/SKILL.md Part A, tailored with the triage predictions (process names to filter, expected protocol, expected persistence), and state the boundary explicitly:
"The next phase requires executing the sample in your isolated VM (REMnux/FlareVM). Follow the runbook: snapshot → start Procmon/Wireshark/System Informer/Sysmon → execute → observe 15+ min → export evidence with the A4 commands (Procmon CSV, Sysmon JSON, tshark text, autoruns CSV, dropped files) → revert. Bring the
evidence/directory back and I'll parse it."
If the user returns with PML/PCAP/EVTX, give the conversion command from the dynamic skill's Converting Binary Evidence table (tshark and evtx_dump can run on the host) rather than refusing the files.
State File: analysis_state.md
Created in the user's working directory (not this skill repo) when the first sample is provided. Updated after each phase.
Structure
# Malware Analysis — [Engagement Name/Date]
**Analyst:** [name]
**Started:** [date]
**Status:** [In Progress / Complete]
---
## Samples
### Sample 1: [filename]
- **File Type:** [type]
- **MD5:** [hash]
- **SHA1:** [hash]
- **SHA256:** [hash]
- **Size:** [bytes]
- **Priority:** [Immediate / Standard / Low]
- **Classification:** [Trojan / Ransomware / etc. or Pending]
- **Threat Level:** [Critical / High / Medium / Low or Pending]
- **Current Phase:** [Triage / Dynamic Analysis / Specialized Analysis / Detection / Reporting / Complete / Benign]
#### Triage Findings
- [findings appended after triage phase]
#### Analysis Findings
- [findings appended after dynamic/specialized analysis]
#### IOCs Identified
- [accumulated IOCs, defanged]
#### Detection Rules Created
- [list of rules created and their locations]
---
## Next Steps
- [orchestrator's recommendation for what to do next and why]State File Rules
- Create when the user begins an engagement (first sample provided)
- Append findings after each phase — never overwrite previous findings
- Replace the "Next Steps" section at each transition (not append)
- Resume from state file if the user returns in a new conversation — read
analysis_state.mdto restore context - All IOCs must be defanged at the point they are recorded to the state file, regardless of which phase produces them
Multi-Sample Batch Workflow
- Intake: Prompt for all known samples upfront — "How many samples do you have? Let's list them all before we begin."
- Batch triage: Quick triage pass on all samples (5-10 min each — hashes, file type, reputation check, classification per the triage skill's "Quick Triage" tier)
- Priority ranking: Rank samples as Immediate / Standard / Low based on triage findings
- Sequential deep analysis: Run the full phase sequence on high-priority samples one at a time, confirming with the user at each phase transition
- State tracking: Update state file per-sample so the user can see which samples are triaged, analyzed, and reported
Conventions Enforced
- All IOCs in state files and reports must be defanged (
hxxp://,[.]com,[@]) - Reports always include all three hash types: MD5, SHA1, SHA256
- Evidence must be in text-parseable formats (CSV, JSON, TXT)
- Detection rules (YARA, Sigma, Suricata) must be tested before inclusion
- MITRE ATT&CK technique IDs must be tagged in Sigma rules
- Sigma rules require unique UUIDs
- Custom Suricata rules use SIDs starting at 1000000+
IOC Defanging Ownership
Each phase defangs IOCs before appending them to the state file. The detection-engineer sub-skill handles bulk defanging, format conversion (STIX, CSV, OpenIOC), and confidence assessment during its dedicated phase.
Edge Cases
- User wants to skip a phase: Allow it, note the skip in the state file, and proceed to the requested phase
- User provides evidence without explicit routing: Infer the phase from evidence type (Procmon CSV → dynamic analysis, Sysmon JSON → dynamic analysis, olevba output → specialized file analysis, etc.)
- Session restart: Read
analysis_state.mdto restore context and resume from the last recorded phase - Single sample, known type: Skip batch triage and go directly to the appropriate skill
- User explicitly requests a specific sub-skill: Defer to the user's choice
- Benign sample: If triage determines a sample is clean/benign, mark its phase as
Benignin the state file, note the reasoning, and move to the next sample. Do not proceed with further analysis phases. - Unrecognized file type: If
fileoutput doesn't match any known routing pattern, default tomalware-triage/SKILL.mdfor manual assessment. Note the unknown type in the state file. - State file conflicts: If an existing
analysis_state.mdis found, ask whether to resume the existing engagement or start a new one (with a timestamped filename likeanalysis_state_2026-03-15.md) - Running from the skill repo: If the working directory appears to be this skill repository itself (contains
malware-triage/,detection-engineer/, etc. as subdirectories), warn the user and ask them to switch to their analysis workspace before creating a state file
Sub-Skill Reference
The orchestrator delegates to these sub-skills by reading their SKILL.md files at execution time:
| Sub-Skill | Path | Purpose |
| Malware Triage | malware-triage/SKILL.md | Rapid assessment, classification, prioritization |
| Dynamic Analysis | malware-dynamic-analysis/SKILL.md | Safe execution, behavior monitoring in isolated VMs |
| Specialized File Analyzer | specialized-file-analyzer/SKILL.md | Non-PE file analysis (.NET, Office, PDF, scripts, archives, LNK, ELF) |
| Detection Engineer | detection-engineer/SKILL.md | Sigma rules, Suricata rules, hunting queries, IOC defanging |
| Report Writer | malware-report-writer/SKILL.md | Professional reports, YARA rules, quality checklists |
Paths are relative to the directory containing this SKILL.md (the sub-skills are not registered as separate skills — this orchestrator reads them by path). When entering a phase, read the corresponding SKILL.md file and follow its instructions. Carry forward the accumulated state from previous phases.
MCP Server Integrations (Optional)
MCP servers can automate manual steps like hash lookups and IOC enrichment. If available, use them to accelerate the workflow — but they are not required.
See references/mcp_integrations.md for setup instructions and a mapping of which MCP servers benefit which skills. The two highest-impact integrations are:
- VirusTotal MCP — automates hash/URL/domain reputation checks during triage
- Threat Intel MCP — unified access to MalwareBazaar, ThreatFox, AbuseIPDB, and GreyNoise for IOC validation
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

