mirror of
https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git
synced 2026-07-17 21:19:40 +03:00
mukul975
efca3ec611
Mapped every skill to NIST CSF 2.0 subcategory IDs (GV/ID/PR/DE/RS/RC functions) based on subdomain and content analysis. Restores 11 skills corrupted during prior rebase, re-enriching with ATLAS, D3FEND, NIST AI RMF, and CSF 2.0 fields. All 754 skills now carry structured mappings for all 5 security frameworks: - MITRE ATT&CK (in tags) - MITRE ATLAS v5.5 (atlas_techniques) - MITRE D3FEND v1.3 (d3fend_techniques) - NIST AI RMF 1.0 (nist_ai_rmf) - NIST CSF 2.0 (nist_csf)
2.9 KiB
2.9 KiB
name, description, domain, subdomain, tags, version, author, license, nist_csf
| name | description | domain | subdomain | tags | version | author | license | nist_csf | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 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. | cybersecurity | malware-analysis |
|
1.0 | mahipal | Apache-2.0 |
|
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 |
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]