tao-analyze-gaps-vlm-bcq
Pass
Audited by Gen Agent Trust Hub on Sep 17, 2026
Risk Level: SAFE
Full Analysis
- [INDIRECT_PROMPT_INJECTION]: The skill ingests model-generated text from a
predictions_jsonfile. This represents a potential surface for indirect prompt injection if the VLM output contains malicious instructions that are subsequently processed by an agent. - Ingestion points: The
predictions_jsonfile processed by the gap analysis tool. - Boundary markers: The skill uses structured JSON for data ingestion but does not employ specific delimiters or warnings to ignore instructions within the VLM response fields.
- Capability inventory: The skill leverages
ReadandBashtools to execute containerized analysis and read report files. - Sanitization: The analysis logic utilizes word-boundary matching for 'yes' and 'no' keywords, which restricts the potential for command execution or logic subversion during the analysis phase itself.
- [EXTERNAL_DOWNLOADS]: The skill references an official container image
nvcr.io/nvidia/tao/tao-toolkit:7.2.0-data-services. This resource belongs to the skill's authoring organization (NVIDIA) and is consistent with the stated functionality of the TAO Toolkit.
Audit Metadata