I need to know how to pass user context correctly when we integrate our internal LLM tool with Slack today to avoid data leaks between different channels.
Download run
Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
I need to know how to pass user context correctly when we integrate our internal LLM tool with Slack today to avoid data leaks between different channels.
1 real search · 1 real-search pass
Slack API security verify request signatures event subscriptions authorization channel access conversations.replies documentation; OWASP LLM prompt injection data leakage multi tenant isolation guidanceGoogle ↗
OBSERVED
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
Classifying 1 queries…
Searches and sources
ChatGPT1 real searches · gpt-6
Slack API security verify request signatures event subscriptions authorization channel access conversations.replies documentation; OWASP LLM prompt injection data leakage multi tenant isolation guidance Google ↗
- MCP-Security-Testing-Guide/04. Secure MCP Development.md at main · OWASP/MCP-Security-Testing-Guide · github.com
- Multi Tenant Security · cheatsheetseries.owasp.org
- Security best practices · docs.slack.dev
- Guide to the Slack AI guardrails · slack.com
- The Events API · docs.slack.dev
Queries
1 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
Slack API security verify request signatures event subscriptions authorization channel access conversations.replies documentation; OWASP LLM prompt injection data leakage multi tenant isolation guidance OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 |