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 meltedinhex/analyst-ai-pack --skill analyzing-malicious-office-macrosgit clone --depth 1 https://github.com/meltedinhex/analyst-ai-packWrote 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/meltedinhex/analyst-ai-pack/analyzing-malicious-office-macros)<a href="https://agentmods.dev/skills/meltedinhex/analyst-ai-pack/analyzing-malicious-office-macros"><img src="https://agentmods.dev/badge/skills/meltedinhex/analyst-ai-pack/analyzing-malicious-office-macros/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/meltedinhex/analyst-ai-pack/analyzing-malicious-office-macros"><img src="https://agentmods.dev/badge/skills/meltedinhex/analyst-ai-pack/analyzing-malicious-office-macros.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 | $0.00069 | $0.00892 |
| Opus 5 | $0.00034 | $0.00446 |
| Sonnet 5 | $0.00014 | $0.00178 |
| Haiku 4.5 | $0.00007 | $0.00089 |
Grade A, and why
analyzing-malicious-office-macros 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 11d 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 — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analyzing Malicious Office Macros
When to Use
- A Word/Excel/PowerPoint document is suspected of delivering malware via macros.
- You need to extract VBA, identify auto-exec triggers, and see what the macro does.
- You are determining the next-stage payload or URL a maldoc fetches.
Do not use the document's "Enable Content" path to analyze it — never open a maldoc in Office. Extract and read the macro statically; detonate only in the isolated lab if needed.
Prerequisites
oletools(pip install oletools) forolevba/oleid, or the bundled OLE/OOXML extractor.- The document in neutralized form inside the lab.
Safety & Handling
- Do not open the document in Microsoft Office. Macros may auto-run on open/close.
- Static extraction only; if dynamic analysis is required, detonate in the isolated victim VM.
Workflow
Step 1: Identify the container and locate macros
OOXML (.docm, .xlsm) is a ZIP; legacy (.doc, .xls) is OLE2. Macros live in a
vbaProject.bin OLE stream. Extract it:
python scripts/analyst.py extract maldoc.docm
Step 2: Flag auto-exec triggers
Look for entry points that run without user action beyond enabling macros:
AutoOpen, Document_Open, AutoClose, Workbook_Open, Auto_Open, Document_Close
Step 3: Find suspicious calls
Identify execution and download primitives:
Shell, WScript.Shell, CreateObject, powershell, cmd /c
URLDownloadToFile, MSXML2.XMLHTTP, ADODB.Stream (drop to disk)
Environ, GetObject("winmgmts:") (WMI)
Step 4: Deobfuscate
Maldocs commonly use Chr()/string concatenation, base64, and split-and-join. Resolve these to recover the real command and any URL or dropped path.
Step 5: Extract IOCs and the next stage
Pull URLs, dropped file paths, and the spawned command line. These become the report's IOCs and pivot points.
Validation
- The recovered command line and URL make sense together (download → drop → execute).
- Auto-exec triggers explain how the macro starts.
- Deobfuscated strings match what dynamic detonation would reveal (if you confirm in the lab).
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.
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.
- 11d ago First seen · 109 lines · 69 tokens per session scan A 42fa12e484d5
analyzing-malicious-office-macros is a skill published in the GitHub repository meltedinhex/analyst-ai-pack (22 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 69 tokens to every session and 892 once invoked, about $0.0003 per session on Opus 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 2026-08-30.
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