data-tools
Pass
Audited by Gen Agent Trust Hub on Oct 7, 2026
Risk Level: SAFEINDIRECT_PROMPT_INJECTIONDYNAMIC_EXECUTIONDATA_EXFILTRATION
Full Analysis
- [INDIRECT_PROMPT_INJECTION]: The skill is designed to ingest and process data from diverse external sources, including JSON, CSV, and YAML files, as well as API responses from GitHub and GitLab. This represents a vulnerability surface where malicious instructions could be embedded in data processed by the agent.\n
- Ingestion points: The skill utilizes specialized tools like
jq,yq,dasel,qsv, andmlrto handle external file and API data.\n - Boundary markers: While the instructions emphasize tool correctness, they do not explicitly mandate delimiters or safety warnings for the agent when processing or outputting external content.\n
- Capability inventory: The skill has access to
Bash,Read, andWritecapabilities, allowing for significant file system and network operations based on processed data.\n - Sanitization: No specific data sanitization or escaping mechanisms are described beyond the inherent validation of structured parsers.\n- [DYNAMIC_EXECUTION]: The
references/yq-cookbook.mdfile describes a workflow for extractingrun:steps from GitHub Action YAML configurations into a shell script and executing them. This is a form of dynamic script generation and execution.\n - Evidence: The documentation demonstrates using
yqto write a YAML field to a temporary file and then executing it withbash -eo pipefail.\n - Safety context: The skill includes an explicit security warning stating that code from untrusted sources is dangerous and that directory sandboxing is not a complete defense.\n- [DYNAMIC_EXECUTION]: The skill implements a
PreToolUsehook that executes a local Python script (scripts/pre_bash_structured_warn.py) to validate Bash commands. This is a functional use of dynamic execution for environment enforcement and safety gating.\n- [DATA_EXFILTRATION]: The skill promotes secure data handling by providing specific recipes for excluding sensitive fields (such aspasswordorsecret_key) during transformation and extraction tasks in CSV and JSON formats, helping to prevent unintentional data exposure.
Audit Metadata