marketing-analytics-lab-engine
Fail
Audited by Gen Agent Trust Hub on Oct 8, 2026
Risk Level: HIGHEXTERNAL_DOWNLOADSREMOTE_CODE_EXECUTIONCOMMAND_EXECUTIONINDIRECT_PROMPT_INJECTION
Full Analysis
- [EXTERNAL_DOWNLOADS]: The skill instructions direct the agent to clone a repository from an untrusted GitHub account.
- Evidence:
git clone https://github.com/shayantimes/marketing-analytics-lab.gitin the Installation section of SKILL.md. - [REMOTE_CODE_EXECUTION]: The skill requires the agent to install dependencies from a downloaded requirements file, which can result in the execution of arbitrary code during the installation process.
- Evidence:
pip install -r requirements.txtfollowing the repository clone. - [COMMAND_EXECUTION]: The skill provides shell commands for repository cloning, dependency installation, and running tests, which require the agent to have shell access.
- Evidence:
git clone,pip install, andpytestcommands provided in the documentation. - [INDIRECT_PROMPT_INJECTION]: The skill ingests campaign data from external CSV files, which is a common vector for indirect prompt injection if the data contains malicious instructions that the agent might later interpret.
- Ingestion points:
UnifiedLoader.load(source, filepath)callspd.read_csv(filepath)to ingest marketing data. - Boundary markers: None identified; data is processed directly after loading.
- Capability inventory: The skill performs file reading and provides instructions for shell command execution (git/pip/pytest).
- Sanitization: The skill uses Pydantic for schema and type validation (e.g.,
CampaignRecord), which enforces data structure but does not sanitize string fields against natural language instructions targeted at the LLM.
Recommendations
- AI detected serious security threats
Audit Metadata