Perform static analysis of malicious PDF documents using peepdf, pdfid, and pdf-parser to extract embedded JavaScript, shellcode, and suspicious objects. Use wh
复制下面这句话,粘贴给 Claude Code、Codex、Cursor 等 AI 编程工具,它会读取安装说明并在你确认后完成安装。
请阅读 https://ai.atlankj.com/install/asset/gh-analyzing-malicious-pdf-with-peepdf-303c760f92ea ,按照其中的说明把「analyzing-malicious-pdf-with-peepdf」安装到你(当前 AI 工具)中。执行前先告诉我将运行的命令和写入的位置,等我确认。
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内容来自 GitHub 原始文件,由原作者维护。在 GitHub 查看
| 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 |
| 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 |
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]