modal

Pass

Audited by Gen Agent Trust Hub on Mar 24, 2026

Risk Level: SAFEDATA_EXFILTRATIONCOMMAND_EXECUTIONPROMPT_INJECTION
Full Analysis
  • [DATA_EXFILTRATION]: Documentation examples demonstrate patterns for exposing sensitive local files and directory structures to remote cloud environments.\n
  • Evidence: references/images.md provides an example for mounting the ~/.aws credentials directory into a container image via .add_local_dir("/user/erikbern/.aws", ...).\n
  • Evidence: references/web-endpoints.md demonstrates an example of serving the root directory (/) of a remote container via an unauthenticated web server using python -m http.server -d /.\n- [COMMAND_EXECUTION]: The skill facilitates the execution of arbitrary Python code and shell commands on remote infrastructure as a core feature.\n
  • Evidence: Use of @app.function, modal run, and subprocess.Popen in examples throughout the skill documentation and reference files.\n- [PROMPT_INJECTION]: The skill provides patterns for building public web endpoints that ingest untrusted data, serving as a surface for indirect prompt injection.\n
  • Ingestion points: Web endpoints defined in references/web-endpoints.md (e.g., @modal.fastapi_endpoint() processing data: dict).\n
  • Boundary markers: Examples do not utilize delimiters or specific instructions to isolate data from processing commands.\n
  • Capability inventory: The skill documents extensive capabilities including remote code execution, persistent volume writes, and network operations.\n
  • Sanitization: Provided examples do not demonstrate validation, escaping, or filtering of data received from external API requests.
Audit Metadata
Risk Level
SAFE
Analyzed
Mar 24, 2026, 08:45 AM