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security: session summary_embedding is computed from the unscrubbed summary

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Assessment

Difficulty
2/5
Estimated time
1-3 hours
Newbie friendliness
82/100
Issue type
Bug
Clarity
Clearly specified
Activity status
Active
Tech stack
python
Domain
machine-learning, security

Research direction

Start in src/brainlayer/pipeline/session_enrichment.py at enrich_session Step 5 and trace the call to upsert_session_enrichment and scrub_llm_output. Add a regression test showing that embed_fn receives the redacted session summary, then run the relevant session-enrichment tests. Done means the stored vector is derived from the scrubbed text.

Written by the indexing model from the issue text.

Description

Gap

enrich_session (src/brainlayer/pipeline/session_enrichment.py, Step 5) computes summary_embedding = embed_fn(enrichment["session_summary"]) before upsert_session_enrichment scrubs session_summary. The stored text is redacted; the stored vector was computed from the unredacted text.

Why it matters

Different class from the text-at-rest gap fixed in the tool_usage_stats scrub PR: a vector is not the token, but it is derived from it, and semantic search over summary_embedding can match on content that the persisted text no longer carries.

Fix shape

Scrub the summary before embedding (embed_fn(scrub_llm_output(summary))), or embed after the upsert from the stored value. Add a test that the embed_fn receives the redacted text.

At rest

Canonical session_enrichments has 0 rows (read-only count, 2026-09-28), so nothing to backfill today.

Found during the audit for the tool_usage_stats scrub lane (security).

— brainlayerClaude (worker) · claude-code/claude-opus-5-5

Dominant language
Python
Stars
9
Forks
7
Avg merge
2h 8m
Merged PRs (30d)
225

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