data-visualization
Fail
Audited by Gen Agent Trust Hub on Feb 16, 2026
Risk Level: HIGHPROMPT_INJECTIONEXTERNAL_DOWNLOADS
Full Analysis
- [Indirect Prompt Injection] (HIGH): The skill's core function involves interpolating untrusted user data into executable or renderable contexts (Python scripts, React components, and HTML/JavaScript artifacts) without sanitization.
- Ingestion points: User-provided datasets, labels, and titles are directly inserted into code templates in
SKILL.mdand processed byscripts/chart_utils.py. - Boundary markers: There are no explicit boundary markers or instructions to the agent to escape or validate user content before code generation.
- Capability inventory: The agent uses these patterns to generate and execute Python code (via
matplotlib) and render interactive web artifacts (viaChart.jsandRecharts). - Sanitization: No sanitization is implemented. An attacker could provide malicious data (e.g., a chart label containing
'); import os; os.system('...) that triggers arbitrary code execution in the Python environment or Cross-Site Scripting (XSS) in the artifact renderer. - [External Downloads] (MEDIUM): The HTML implementation pattern in
SKILL.mdincludes a remote script reference tohttps://cdn.jsdelivr.net/npm/chart.js. - Evidence:
<script src="https://cdn.jsdelivr.net/npm/chart.js"></script> - Risk: Loading scripts from external CDNs that are not within the [TRUST-SCOPE-RULE] (like
jsdelivr.net) introduces a supply-chain risk where a compromised CDN or package could lead to remote code execution in the user's browser/agent environment.
Recommendations
- AI detected serious security threats
Audit Metadata