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 Youngmaidainon/Agent-Level-Up --skill analyzing-malicious-pdf-with-peepdfgit clone --depth 1 https://github.com/Youngmaidainon/Agent-Level-UpWrote 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/youngmaidainon/agent-level-up/analyzing-malicious-pdf-with-peepdf)<a href="https://agentmods.dev/skills/youngmaidainon/agent-level-up/analyzing-malicious-pdf-with-peepdf"><img src="https://agentmods.dev/badge/skills/youngmaidainon/agent-level-up/analyzing-malicious-pdf-with-peepdf/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/youngmaidainon/agent-level-up/analyzing-malicious-pdf-with-peepdf"><img src="https://agentmods.dev/badge/skills/youngmaidainon/agent-level-up/analyzing-malicious-pdf-with-peepdf.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 | $0.00073 | $0.00803 |
| Opus 5 | $0.00036 | $0.00402 |
| Sonnet 5 | $0.00015 | $0.00161 |
| Haiku 4.5 | $0.00007 | $0.00080 |
Grade A, and why
analyzing-malicious-pdf-with-peepdf 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 10d 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.
This is a copy
100% identical to analyzing-malicious-pdf-with-peepdf — 0 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.
How it starts
The opening of the file, as written. The whole thing — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analyzing Malicious PDF with peepdf
When to Use
- When triaging suspicious PDF attachments from phishing emails
- During malware analysis of PDF-based exploit documents
- When extracting embedded JavaScript, shellcode, or executables from PDFs
- For forensic examination of weaponized document artifacts
- When building detection signatures for PDF-based threats
Prerequisites
- Python 3.8+ with peepdf-3 installed (pip install peepdf-3)
- pdfid.py and pdf-parser.py from Didier Stevens suite
- Isolated analysis environment (VM or sandbox)
- Optional: PyV8 for JavaScript emulation within peepdf
- Optional: Pylibemu for shellcode analysis
Workflow
- Triage with pdfid: Scan PDF for suspicious keywords (/JS, /JavaScript, /OpenAction, /Launch, /EmbeddedFile).
- Interactive Analysis: Open PDF in peepdf interactive mode to explore object structure.
- Identify Suspicious Objects: Locate objects containing JavaScript, streams, or encoded data.
- Extract Content: Dump suspicious streams and decode filters (FlateDecode, ASCIIHexDecode).
- Deobfuscate JavaScript: Analyze extracted JS for shellcode, heap sprays, or exploit code.
- Check VirusTotal: Use peepdf vtcheck to cross-reference file hash with AV detections.
- Generate IOCs: Extract URLs, domains, hashes, and shellcode signatures.
Key Concepts
| Concept | Description |
|---|---|
| /OpenAction | Automatic action executed when PDF is opened |
| /JavaScript /JS | Embedded JavaScript code in PDF objects |
| /Launch | Action that launches external applications |
| /EmbeddedFile | File embedded within the PDF structure |
| FlateDecode | zlib compression filter used to hide content |
| Object Streams | PDF objects stored in compressed streams |
Tools & Systems
| Tool | Purpose |
|---|---|
| peepdf / peepdf-3 | Interactive PDF analysis with JS emulation |
| pdfid.py | Quick triage scanning for suspicious keywords |
| pdf-parser.py | Deep object-level PDF parsing |
| VirusTotal | Hash lookup and AV detection cross-reference |
| CyberChef | Decode and transform extracted payloads |
What ships with it
2 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.
- 10d ago First seen · 97 lines · 73 tokens per session scan A 7cdd9a208444
analyzing-malicious-pdf-with-peepdf is a skill published in the GitHub repository Youngmaidainon/Agent-Level-Up (3 stars, last pushed 16d ago), licensed MIT. It adds 73 tokens to every session and 803 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to analyzing-malicious-pdf-with-peepdf, differing in 0 lines, and is treated as a copy.
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Perform static analysis of malicious PDF documents using peepdf, pdfid, and pdf-parser to extract embedded JavaScript, shellcode, and suspicious objects.
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analyzing-malicious-pdf-with-peepdf
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analyzing-malicious-pdf-with-peepdf
A Chinese-language skill for examining suspicious PDF files with peepdf, pdfid, and pdf-parser. It is intended for static malware analysis, which studies a file without running it.
analyzing-malicious-pdf-with-peepdf
Perform static analysis of malicious PDF documents using peepdf, pdfid, and pdf-parser to extract embedded JavaScript, shellcode, and suspicious objects.