skills/aipoch/open-science/ligandmpnn/Gen Agent Trust Hub

ligandmpnn

Fail

Audited by Gen Agent Trust Hub on Sep 22, 2026

Risk Level: HIGHEXTERNAL_DOWNLOADSREMOTE_CODE_EXECUTIONCOMMAND_EXECUTIONINDIRECT_PROMPT_INJECTIONDYNAMIC_EXECUTION
Full Analysis
  • [EXTERNAL_DOWNLOADS]: The skill clones a software repository from an external GitHub account (dauparas/LigandMPNN) that is not part of the established trusted organizations list.
  • [REMOTE_CODE_EXECUTION]: The skill proceeds to execute a shell script (get_model_params.sh) and a Python script (run.py) directly from the newly cloned remote repository, creating a significant dependency on the security of that external source.
  • [COMMAND_EXECUTION]: The skill uses shell commands like 'sed' to modify downloaded files and 'bash' to run setup scripts, which are executed in the local environment.
  • [DYNAMIC_EXECUTION]: The documentation notes that one dependency (ProDy) may require runtime compilation from source using 'gcc' or 'g++' if compatible binaries are not found, which involves invoking a compiler during the installation process.
  • [INDIRECT_PROMPT_INJECTION]: The skill is designed to ingest and process external files (PDB and JSON) which represent an attack surface for indirect prompt injection.
  • Ingestion points: Reads protein/ligand structures via --pdb_path and amino acid constraints from JSON files.
  • Boundary markers: No explicit markers or instructions are provided to the agent to isolate or ignore potentially malicious content within these data files.
  • Capability inventory: The environment allows for package installation, shell script execution, and file modification.
  • Sanitization: The skill relies on the third-party model code for parsing without additional validation layers documented in the instructions.
Recommendations
  • AI detected serious security threats
Audit Metadata
Risk Level
HIGH
Analyzed
Sep 22, 2026, 12:56 PM