paper-analyzer
Fail
Audited by Gen Agent Trust Hub on Apr 13, 2026
Risk Level: HIGHEXTERNAL_DOWNLOADSCOMMAND_EXECUTIONPROMPT_INJECTION
Full Analysis
- [EXTERNAL_DOWNLOADS]: The skill uses
curlto download PDFs, archives, and HTML content fromarxiv.org. While ArXiv is a trusted and well-known academic repository, fetching external content creates a data ingestion surface that the agent must process. - [COMMAND_EXECUTION]: Local Python scripts (
generate_note.pyandupdate_graph.py) are executed via shell commands defined inSKILL.md. These commands interpolate user-controlled or paper-controlled variables like$TITLEand$AUTHORSdirectly into the shell execution context. - [PROMPT_INJECTION]: Indirect Prompt Injection Surface. Metadata extracted from untrusted external papers flows into shell arguments and Markdown templates. A paper with a malicious title or author field containing shell control characters or Markdown injection sequences could attempt to influence the agent's behavior or corrupt the formatting of the generated research notes.
- Ingestion points: ArXiv paper content and metadata retrieved via network requests in
SKILL.md. - Boundary markers: None identified. Metadata is used directly in shell command templates and f-string file generation.
- Capability inventory: Shell command execution, local file system writes, and modification of structured JSON data.
- Sanitization:
generate_note.pyincludes basic character replacement for filenames, but it does not sanitize metadata used inside the Markdown content or within the shell command invocation defined inSKILL.md.
Recommendations
- HIGH: Downloads and executes remote code from: https://arxiv.org/pdf/[PAPER_ID] - DO NOT USE without thorough review
Audit Metadata