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.
Best use case
analyzing-malicious-pdf-with-peepdf is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Perform static analysis of malicious PDF documents using peepdf, pdfid, and pdf-parser to extract embedded JavaScript, shellcode, and suspicious objects.
Teams using analyzing-malicious-pdf-with-peepdf should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/analyzing-malicious-pdf-with-peepdf/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How analyzing-malicious-pdf-with-peepdf Compares
| Feature / Agent | analyzing-malicious-pdf-with-peepdf | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Perform static analysis of malicious PDF documents using peepdf, pdfid, and pdf-parser to extract embedded JavaScript, shellcode, and suspicious objects.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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 1. **Triage with pdfid**: Scan PDF for suspicious keywords (/JS, /JavaScript, /OpenAction, /Launch, /EmbeddedFile). 2. **Interactive Analysis**: Open PDF in peepdf interactive mode to explore object structure. 3. **Identify Suspicious Objects**: Locate objects containing JavaScript, streams, or encoded data. 4. **Extract Content**: Dump suspicious streams and decode filters (FlateDecode, ASCIIHexDecode). 5. **Deobfuscate JavaScript**: Analyze extracted JS for shellcode, heap sprays, or exploit code. 6. **Check VirusTotal**: Use peepdf vtcheck to cross-reference file hash with AV detections. 7. **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] ```