alterlab-lamindb
Pass
Audited by Gen Agent Trust Hub on Apr 12, 2026
Risk Level: SAFEEXTERNAL_DOWNLOADSCOMMAND_EXECUTIONDATA_EXFILTRATIONPROMPT_INJECTION
Full Analysis
- [COMMAND_EXECUTION]: Documentation provides instructions for using the lamin CLI tool and other standard utilities such as pip and git. It includes guidance for system-level configuration of a shared multi-user cache which involves using sudo to manage directory permissions in setup-deployment.md.\n- [EXTERNAL_DOWNLOADS]: The skill provides instructions for installing the lamindb Python library and its plugins from public package registries. It also describes fetching biological data and ontologies from remote sources including AWS S3, Google Cloud Storage, and public HTTP endpoints in the integrations.md and ontologies.md references.\n- [DATA_EXFILTRATION]: The framework's documented core capability includes synchronizing local data artifacts to cloud storage (S3, GCS), which is the intended mechanism for collaborative data management and research backup as described in integrations.md.\n- [PROMPT_INJECTION]: The skill defines an indirect prompt injection surface as it instructs the agent to ingest and process external biological datasets.\n
- Ingestion points: Data is loaded from various formats (CSV, Parquet, AnnData) via local files, cloud storage (S3, GCS), and HTTP APIs as described in data-management.md and integrations.md.\n
- Boundary markers: None identified; the documentation does not suggest the use of delimiters or instructions to ignore embedded content within the data artifacts.\n
- Capability inventory: The agent is expected to use the lamindb Python API and scientific libraries for data analysis, which includes file system and network access across the described workflows.\n
- Sanitization: No specific content sanitization or metadata filtering is provided to mitigate potential instruction injection within biological data files.
Audit Metadata