AI Agent Privacy Notice#21
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AI Agent Privacy Risk
This PR adds a short README notice about a possible privacy pattern found in this project.
The concern is not an API key leak. The concern is that sensitive user, customer, or patient data may be passed directly into an AI agent / LLM context.
When this happens, the agent may see data it does not need to know in order to complete the task.
Safer pattern:
John Smith -> [CVT:NAME:user_name]
john@email.com -> [CVT:EMAIL:user_email]
04/12/1988 -> [CVT:DOB:user_dob]
The agent can still reason and perform the workflow, while the real values stay protected and are only re-injected during approved execution.
File scanned:
crewai_supabase/main.pyFindings:
[ { "type": "unblinded_ai_call", "evidence": "agent(role='supabase agent', goal='you will perform executions on the supabase database.', backstory=f\"\"\"\\n you are a master at performing executions on the supabase database.\\n you are able to perform the following operations:\\n - get a row from the database.\\n - get all rows from the database.\\n - insert a row into the database.\\n - delete a row from the database.\\n - update a row in the database.\\n \\n for insert operations, the input should be a string containing the input to insert, all columns data should be in a data dict field in the string.\\n \\n for delete operations, try to get the row you are deleting firs" }, { "type": "unblinded_ai_call", "evidence": "task(description='answer the following questions about the database: {question}.', expected_output='you are to return the result of the operation you performed.', agent=agent)" }, { "type": "unblinded_ai_call", "evidence": "crew(agents=[agent], tasks=[task], verbose=true, process=process.sequential)" } ]Please review before merging. If this is not applicable, feel free to close this PR.
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