mirror of
https://github.com/SHOGGOTH-SECTOR/sica-fondt.git
synced 2026-08-01 08:30:20 +00:00
24f816b6a3
Place useful parts of the surrounding repos into sica-fondt by layer, per the
body model (Ada = membrane; brain/endocrine/capabilities/knowledge non-Ada):
- brain/ LLM reasoning + providers (dapr, hermes, MoMoA)
- capabilities/ REPRAG sidecars: hermes tools/skills, dapr tools, parallel
dispatch, A51 channels, and the OSINT cluster
- knowledge/ LORAG corpus: 754 cyber-skills, agency personas, secure-coding,
MITRE ATT&CK data
- reference/ defensive threat-reference (C3, shhbruh doc) + AdaYaml parser
License handling: AGPL sources (worldosint, advanced_evolution, mercury,
Reticulum) and GPL DeTTECT are SPEC-only clean-room/port descriptions — no
copyleft code copied. MIT/Apache/data parts copied as working trees.
Safety: shhbruh escape/persistence material and C3 covert-C2 kept as reference
only, not wired into the running organism. See CONSOLIDATION.md.
https://claude.ai/code/session_01UehUqEXXJJCsHoA4voCU5c
89 lines
2.9 KiB
Markdown
89 lines
2.9 KiB
Markdown
---
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name: analyzing-malicious-pdf-with-peepdf
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description: Perform static analysis of malicious PDF documents using peepdf, pdfid, and pdf-parser to extract embedded JavaScript,
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shellcode, and suspicious objects.
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domain: cybersecurity
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subdomain: malware-analysis
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tags:
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- malware-analysis
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- pdf
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- peepdf
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- pdfid
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- pdf-parser
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- static-analysis
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- reverse-engineering
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- dfir
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version: '1.0'
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author: mahipal
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license: Apache-2.0
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nist_csf:
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- DE.AE-02
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- RS.AN-03
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- ID.RA-01
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- DE.CM-01
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---
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# Analyzing Malicious PDF with peepdf
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## When to Use
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- When triaging suspicious PDF attachments from phishing emails
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- During malware analysis of PDF-based exploit documents
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- When extracting embedded JavaScript, shellcode, or executables from PDFs
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- For forensic examination of weaponized document artifacts
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- When building detection signatures for PDF-based threats
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## Prerequisites
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- Python 3.8+ with peepdf-3 installed (pip install peepdf-3)
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- pdfid.py and pdf-parser.py from Didier Stevens suite
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- Isolated analysis environment (VM or sandbox)
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- Optional: PyV8 for JavaScript emulation within peepdf
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- Optional: Pylibemu for shellcode analysis
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## Workflow
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1. **Triage with pdfid**: Scan PDF for suspicious keywords (/JS, /JavaScript, /OpenAction, /Launch, /EmbeddedFile).
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2. **Interactive Analysis**: Open PDF in peepdf interactive mode to explore object structure.
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3. **Identify Suspicious Objects**: Locate objects containing JavaScript, streams, or encoded data.
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4. **Extract Content**: Dump suspicious streams and decode filters (FlateDecode, ASCIIHexDecode).
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5. **Deobfuscate JavaScript**: Analyze extracted JS for shellcode, heap sprays, or exploit code.
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6. **Check VirusTotal**: Use peepdf vtcheck to cross-reference file hash with AV detections.
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7. **Generate IOCs**: Extract URLs, domains, hashes, and shellcode signatures.
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## Key Concepts
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| Concept | Description |
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|---------|-------------|
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| /OpenAction | Automatic action executed when PDF is opened |
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| /JavaScript /JS | Embedded JavaScript code in PDF objects |
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| /Launch | Action that launches external applications |
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| /EmbeddedFile | File embedded within the PDF structure |
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| FlateDecode | zlib compression filter used to hide content |
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| Object Streams | PDF objects stored in compressed streams |
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## Tools & Systems
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| Tool | Purpose |
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|------|---------|
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| peepdf / peepdf-3 | Interactive PDF analysis with JS emulation |
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| pdfid.py | Quick triage scanning for suspicious keywords |
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| pdf-parser.py | Deep object-level PDF parsing |
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| VirusTotal | Hash lookup and AV detection cross-reference |
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| CyberChef | Decode and transform extracted payloads |
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## Output Format
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```
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Analysis Report: PDF-MAL-[DATE]-[SEQ]
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File: [filename.pdf]
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SHA-256: [hash]
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Suspicious Keywords: [/JS, /OpenAction, etc.]
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Objects with JavaScript: [Object IDs]
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Extracted URLs: [List]
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Shellcode Detected: [Yes/No]
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Embedded Files: [Count and types]
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VirusTotal Detections: [X/Y engines]
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Risk Level: [Critical/High/Medium/Low]
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```
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