hypogenic
Automated LLM-driven hypothesis generation and testing on tabular datasets. Use when you want to systematically explore hypotheses about patterns in empirical data (e.g., deception detection, content analysis). Combines literature insights with data-driven hypothesis testing. For manual hypothesis formulation use hypothesis-generation; for creative ideation use scientific-brainstorming.
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Low
Low-risk findings worth noting
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tessl review fix ./backend/cli/skills/chemistry/hypogenic/SKILL.mdLow
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
W011: Third-party content exposure detected (indirect prompt injection risk).
What this means
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Why it was flagged
The required workflow ingests outsider-authored free text from user-supplied datasets (e.g., the training/val/test JSON containing `text_features_*` strings) into the LLM via the prompt templates’ variable injection (e.g., `{data_samples}`, `{sample_text}`) and thus can include indirect prompt-injection content authored by anyone other than the operating user.
- Repository
- synthetic-sciences/openscience
- Commit
3a6c3a9
- Audited
- Security analysis
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