Analyzing Malicious PDF with peepdf
SkillDocs & knowledgeLets your agent inspect suspicious PDF files to find hidden malicious content.
Available today. Use it from your connected AI after setup.
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Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Analyzing Malicious PDF with peepdf skill
About this capability
Perform static analysis of malicious PDF documents using peepdf, pdfid,
What this skill tells your AI
The instructions your AI receives, as published by mukul975/anthropic-cybersecurity-skills in skills/analyzing-malicious-pdf-with-peepdf/SKILL.md and read by ahel’s review.
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 |
Output Format
Analysis Report: PDF-MAL-[DATE]-[SEQ]
File: [filename.pdf]
SHA-256: [hash]
Suspicious Keywords: [/JS, /OpenAction, etc.]
Objects with JavaScript: [Object IDs]
Extracted URLs: [List]
Shellcode Detected: [Yes/No]
Embedded Files: [Count and types]
VirusTotal Detections: [X/Y engines]
Risk Level: [Critical/High/Medium/Low]
Signals
- GitHub stars
- 33k
- Forks
- 4k
- Last commit
- Aug 2026
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analyzing-malicious-pdf-with-peepdf-mukul975- Source
- github.com/mukul975/anthropic-cybersecurity-skills