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signals-scout-ingestion-warnings

Signals scout for ingestion warnings — events and person/group updates that were dropped, mangled, or partially rejected during ingestion. Watches the warnings stream for new warning types, bursts above a type's own baseline, and error-severity clusters with broad reach, and files each actionable root cause as a report with the affected events and the fix.

60

Quality

72%

Does it follow best practices?

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SecuritybySnyk

High

Do not use without reviewing

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tessl review fix ./products/signals/skills/signals-scout-ingestion-warnings/SKILL.md
SKILL.md
Quality
Evals
Security

Security

1 high severity finding. You should review these findings carefully before considering using this skill.

High

W007: Insecure credential handling detected in skill instructions.

What this means

The skill handles credentials insecurely by requiring the agent to include secret values verbatim in its generated output. This exposes credentials in the agent’s context and conversation history, creating a risk of data exfiltration.

Why it was flagged

The prompt explicitly tells the agent to quote short snippets of untrusted, event-supplied "details" in reports (and notes that sample details may be arbitrary project-supplied values), which can force the LLM to echo secrets or API tokens verbatim if they appear in event data.

Report incorrect finding

Low

Low-risk findings.

1 low severity finding. Worth noting, but not necessarily harmful.

Low

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 calls `ingestion-warnings-list` and then reasons over “recent samples” including untrusted event-supplied fields like `details` (free text), which can be outsider-authored, and that text is ingested into the agent’s LLM context via the tool output used for reporting.

Repository
PostHog/posthog
Audited
Security analysis
Snyk

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