Identify and mitigate risks to AI solutions, building secure systems against data exfiltration, malicious prompting, and sensitive-data leakage using tools such as regular expressions, safety filters, and Model Armor, aligning with responsible AI practices including bias monitoring, and applying model explainability on the Agent Platform.

A logistics company runs a Gemini-backed support agent on the Agent Platform. The agent can call an internal tool that returns full shipment records, and a security review shows that a crafted user message can make the agent paste a customer's saved card number and email straight into its reply. Card numbers follow a fixed 16-digit pattern, but the team also worries about novel social-engineering prompts that try to coax the model into leaking data in ways no fixed pattern anticipates. Which TWO controls should the team combine to reduce sensitive-data leakage in the model's responses? (Select TWO.)

• ALower the model's temperature setting so that generated responses become more deterministic and therefore less likely to include any sensitive customer values.
• BApply a regular-expression filter to the generated output to detect and redact strings matching the fixed 16-digit card-number format before the reply reaches the user.check_circle Correct
• CIncrease the model's context window so it can hold the full shipment record and reason more carefully about which fields are safe to return to the user.
• DGrant the agent's service account broader read access to the shipment database so it can verify records faster and avoid returning stale or partial customer data.
• EPlace Model Armor on the response path to screen generated output for sensitive-data leakage and prompt-driven exfiltration patterns that no single fixed regex anticipates.check_circle Correct

Why A is wrong: Tempting because lower temperature feels like a safety lever, but temperature only changes output randomness and does nothing to detect or strip sensitive data, so leakage continues.

Why B is correct: Correct because a regex reliably catches values with a known fixed structure such as a 16-digit card number, redacting them from the response cheaply and deterministically.

Why C is wrong: Tempting since a larger context seems to give the model more awareness, but window size does not enforce any data-protection rule and the model can still echo card numbers verbatim.

Why D is wrong: Tempting as a reliability tweak, but widening data access increases exfiltration exposure rather than reducing leakage and addresses none of the security concern.

Why E is correct: Correct because Model Armor is a managed control that inspects model responses for sensitive-data leakage and novel threat patterns, covering cases a fixed regex cannot enumerate.