analyzing-pdf-malware-with-pdfid
Analyzes malicious PDF files using PDFiD, pdf-parser, and peepdf to identify embedded JavaScript, shellcode, exploits, and suspicious objects without opening the document. Determines the attack vector and extracts embedded payloads for further analysis. Activates for requests involving PDF malware analysis, malicious document analysis, PDF exploit investigation, or suspicious attachment triage.
65
78%
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Low
Low-risk findings worth noting
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tessl review fix ./skills/analyzing-pdf-malware-with-pdfid/SKILL.mdLow
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
W011: Third-party content exposure detected (indirect prompt injection risk).
What this means
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Why it was flagged
The required runtime workflow ingests the analyzed PDF file’s contents (including any embedded JavaScript/URLs/shellcode text extracted from the PDF) into the agent’s LLM context via the extracted readable prose/preview/code it prints/returns; if that PDF is outsider-authored (e.g., an email attachment from someone else), this is outsider free text entering the LLM context.
- Repository
- mukul975/Anthropic-Cybersecurity-Skills
- Commit
9429fe9
- Audited
- Security analysis
Is this your skill?
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.