langfuse-observability
Set up comprehensive observability for Langfuse with metrics, dashboards, and alerts. Use when implementing monitoring for LLM operations, setting up dashboards, or configuring alerting for Langfuse integration health. Trigger with phrases like "langfuse monitoring", "langfuse metrics", "langfuse observability", "monitor langfuse", "langfuse alerts", "langfuse dashboard".
72
90%
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Low
Low-risk findings worth noting
Low
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 skill’s required workflow feeds **outsider-authored free text** into the agent LLM context via `updateActiveObservation({ input: messages })` where `messages` are runtime chat inputs (which can include user/third-party text) and are sent to Langfuse instrumentation/output (`output: response.choices[0].message.content`), so any such text can be ingested into the LLM-relevant tracing context.
- Commit
c47c3f5
- Audited
- Security analysis
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