NYC
skills/answerzhao/agent-skills/pdf/Gen Agent Trust Hub

pdf

Fail

Audited by Gen Agent Trust Hub on Feb 16, 2026

Risk Level: HIGHPROMPT_INJECTIONCOMMAND_EXECUTIONREMOTE_CODE_EXECUTION
Full Analysis
  • [Indirect Prompt Injection] (HIGH): The skill is designed to ingest untrusted PDF data which can then influence the agent's actions or logic.
  • Ingestion Points: SKILL.md, scripts/convert_pdf_to_images.py, and scripts/extract_form_field_info.py extract text and metadata from user-provided PDFs.
  • Boundary Markers: Absent. There are no delimiters or instructions to treat PDF-extracted text as untrusted content.
  • Capability Inventory: Subprocess calls to qpdf, pdftotext, and pdftk; file writes in fill_pdf_form_with_annotations.py and fill_fillable_fields.py.
  • Sanitization: None. Field IDs and text content from PDFs are used directly in logic and file generation.
  • [Dynamic Execution] (MEDIUM): scripts/fill_fillable_fields.py employs runtime library modification.
  • Evidence: The monkeypatch_pydpf_method function (line 98) replaces pypdf.generic.DictionaryObject.get_inherited at runtime. This technique can be used to hide malicious logic or bypass expected library behavior.
  • [Command Execution] (MEDIUM): Heavy reliance on external command-line utilities.
  • Evidence: Usage of pdftotext, qpdf, and pdftk is documented in SKILL.md (lines 106-135). Insecure handling of filenames or PDF metadata in these commands could lead to command injection.
  • [Prompt Injection] (LOW): Use of high-severity instructional language.
  • Evidence: forms.md contains several 'CRITICAL' and 'REQUIRED' markers designed to override standard agent decision-making.
Recommendations
  • AI detected serious security threats
Audit Metadata
Risk Level
HIGH
Analyzed
Feb 16, 2026, 02:43 AM