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Google Generative AI Leader Bundle

Exam Code: Generative AI Leader

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Google Generative AI Leader Practice Test 75

Question 740

The business case is: A dataset imported for model adaptation has no ownership or retention review. Select TWO: the appropriate design decision and convincing validation evidence. (Select TWO.)

  1. Use Google Cloud IAM and appropriately scoped service identities to enforce least-privilege access for AI applications and their tools.
  2. Use relevant Cloud security posture, threat findings and workload monitoring to detect and investigate AI service misconfigurations alongside application-specific evaluation.
  3. A threat-to-control matrix maps relevant AI risks to implemented mitigations, test evidence and accountable owners.
  4. Apply threat modeling, access controls, data review, testing and monitoring from data acquisition through deployment and retirement.
  5. A lifecycle security review tests unauthorized source access, dangerous tool calls, output handling and operational response.

Explanation

Correct Answers

D:

The intervention for the stated situation A dataset imported for model adaptation has no ownership or retention review is: Apply threat modeling, access controls, data review, testing and monitoring from data acquisition through deployment and retirement. It directly mitigates: Bolting security onto the chatbot interface alone can leave training data, connectors and tool execution exposed.

E:

A separate outcome check for the situation A dataset imported for model adaptation has no ownership or retention review is: A lifecycle security review tests unauthorized source access, dangerous tool calls, output handling and operational response. It measures the effect of the selected intervention rather than relying on the existence of a proposal.

Incorrect Answers

A:

This choice addresses iam least privilege for ai services; its main associated risk is: Shared broad administrative credentials can let a compromised agent read unrelated business data or alter protected systems. However, the situation A dataset imported for model adaptation has no ownership or retention review is primarily about secure ai throughout the lifecycle. The targeted decision is: Apply threat modeling, access controls, data review, testing and monitoring from data acquisition through deployment and retirement.

B:

This choice addresses security command center, monitoring and incident response; its main associated risk is: Infrastructure monitoring cannot by itself prove generated answers are safe or that tool actions are authorized. However, the situation A dataset imported for model adaptation has no ownership or retention review is primarily about secure ai throughout the lifecycle. The targeted decision is: Apply threat modeling, access controls, data review, testing and monitoring from data acquisition through deployment and retirement.

C:

This choice addresses google secure ai framework (saif); its main associated risk is: Claiming SAIF adherence without implementing measurable controls can conceal prompt injection, data exposure and unreviewed changes. However, the situation A dataset imported for model adaptation has no ownership or retention review is primarily about secure ai throughout the lifecycle. The targeted decision is: Apply threat modeling, access controls, data review, testing and monitoring from data acquisition through deployment and retirement.

Question 741

A business team evaluating generative AI encounters this situation: A production AI workflow exposes an admin tool to unverified user requests. It must choose a solution that is useful, secure, properly sourced, and appropriate for its constraints. Which approach is most defensible under these requirements?

  1. Use Google Cloud IAM and appropriately scoped service identities to enforce least-privilege access for AI applications and their tools.
  2. Apply threat modeling, access controls, data review, testing and monitoring from data acquisition through deployment and retirement.
  3. Use relevant Cloud security posture, threat findings and workload monitoring to detect and investigate AI service misconfigurations alongside application-specific evaluation.
  4. Use Google’s Secure AI Framework as a structured lens for threats, security controls and operating governance, not as a product that automatically certifies a system.

Explanation

Correct Answer

B:

The decisive detail is: A production AI workflow exposes an admin tool to unverified user requests. The appropriate business or technical decision is: Apply threat modeling, access controls, data review, testing and monitoring from data acquisition through deployment and retirement. The risk avoided is that bolting security onto the chatbot interface alone can leave training data, connectors and tool execution exposed. Confirm the outcome through: A lifecycle security review tests unauthorized source access, dangerous tool calls, output handling and operational response.

Incorrect Answers

A:

This choice addresses iam least privilege for ai services; its main associated risk is: Shared broad administrative credentials can let a compromised agent read unrelated business data or alter protected systems. However, the situation A production AI workflow exposes an admin tool to unverified user requests is primarily about secure ai throughout the lifecycle. The targeted decision is: Apply threat modeling, access controls, data review, testing and monitoring from data acquisition through deployment and retirement.

C:

This choice addresses security command center, monitoring and incident response; its main associated risk is: Infrastructure monitoring cannot by itself prove generated answers are safe or that tool actions are authorized. However, the situation A production AI workflow exposes an admin tool to unverified user requests is primarily about secure ai throughout the lifecycle. The targeted decision is: Apply threat modeling, access controls, data review, testing and monitoring from data acquisition through deployment and retirement.

D:

This choice addresses google secure ai framework (saif); its main associated risk is: Claiming SAIF adherence without implementing measurable controls can conceal prompt injection, data exposure and unreviewed changes. However, the situation A production AI workflow exposes an admin tool to unverified user requests is primarily about secure ai throughout the lifecycle. The targeted decision is: Apply threat modeling, access controls, data review, testing and monitoring from data acquisition through deployment and retirement.

Question 742

A gen AI initiative reports: A production AI workflow exposes an admin tool to unverified user requests. What independent evidence would best confirm the solution worked?

  1. A lifecycle security review tests unauthorized source access, dangerous tool calls, output handling and operational response.
  2. A seeded incident produces the intended security alert and an actionable trace without leaking protected prompts.
  3. A cross-role test denies unauthorized data access and confirms the service identity has only required permissions.
  4. A threat-to-control matrix maps relevant AI risks to implemented mitigations, test evidence and accountable owners.

Explanation

Correct Answer

A:

The key acceptance evidence for A production AI workflow exposes an admin tool to unverified user requests is: A lifecycle security review tests unauthorized source access, dangerous tool calls, output handling and operational response. It checks whether the team actually implemented: Apply threat modeling, access controls, data review, testing and monitoring from data acquisition through deployment and retirement. A product configuration, demo, or persuasive response alone is not proof.

Incorrect Answers

B:

This choice addresses security command center, monitoring and incident response; its main associated risk is: Infrastructure monitoring cannot by itself prove generated answers are safe or that tool actions are authorized. However, the situation A production AI workflow exposes an admin tool to unverified user requests is primarily about secure ai throughout the lifecycle. The targeted decision is: Apply threat modeling, access controls, data review, testing and monitoring from data acquisition through deployment and retirement.

C:

This choice addresses iam least privilege for ai services; its main associated risk is: Shared broad administrative credentials can let a compromised agent read unrelated business data or alter protected systems. However, the situation A production AI workflow exposes an admin tool to unverified user requests is primarily about secure ai throughout the lifecycle. The targeted decision is: Apply threat modeling, access controls, data review, testing and monitoring from data acquisition through deployment and retirement.

D:

This choice addresses google secure ai framework (saif); its main associated risk is: Claiming SAIF adherence without implementing measurable controls can conceal prompt injection, data exposure and unreviewed changes. However, the situation A production AI workflow exposes an admin tool to unverified user requests is primarily about secure ai throughout the lifecycle. The targeted decision is: Apply threat modeling, access controls, data review, testing and monitoring from data acquisition through deployment and retirement.

Question 743

A business team evaluating generative AI encounters this situation: A decommissioned model endpoint retains credentials and raw request logs without an owner. It must choose a solution that is useful, secure, properly sourced, and appropriate for its constraints. Which first change most directly addresses the observed failure?

  1. Use Google Cloud IAM and appropriately scoped service identities to enforce least-privilege access for AI applications and their tools.
  2. Apply threat modeling, access controls, data review, testing and monitoring from data acquisition through deployment and retirement.
  3. Use relevant Cloud security posture, threat findings and workload monitoring to detect and investigate AI service misconfigurations alongside application-specific evaluation.
  4. Use Google’s Secure AI Framework as a structured lens for threats, security controls and operating governance, not as a product that automatically certifies a system.

Explanation

Correct Answer

B:

The decisive detail is: A decommissioned model endpoint retains credentials and raw request logs without an owner. The appropriate business or technical decision is: Apply threat modeling, access controls, data review, testing and monitoring from data acquisition through deployment and retirement. The risk avoided is that bolting security onto the chatbot interface alone can leave training data, connectors and tool execution exposed. Confirm the outcome through: A lifecycle security review tests unauthorized source access, dangerous tool calls, output handling and operational response.

Incorrect Answers

A:

This choice addresses iam least privilege for ai services; its main associated risk is: Shared broad administrative credentials can let a compromised agent read unrelated business data or alter protected systems. However, the situation A decommissioned model endpoint retains credentials and raw request logs without an owner is primarily about secure ai throughout the lifecycle. The targeted decision is: Apply threat modeling, access controls, data review, testing and monitoring from data acquisition through deployment and retirement.

C:

This choice addresses security command center, monitoring and incident response; its main associated risk is: Infrastructure monitoring cannot by itself prove generated answers are safe or that tool actions are authorized. However, the situation A decommissioned model endpoint retains credentials and raw request logs without an owner is primarily about secure ai throughout the lifecycle. The targeted decision is: Apply threat modeling, access controls, data review, testing and monitoring from data acquisition through deployment and retirement.

D:

This choice addresses google secure ai framework (saif); its main associated risk is: Claiming SAIF adherence without implementing measurable controls can conceal prompt injection, data exposure and unreviewed changes. However, the situation A decommissioned model endpoint retains credentials and raw request logs without an owner is primarily about secure ai throughout the lifecycle. The targeted decision is: Apply threat modeling, access controls, data review, testing and monitoring from data acquisition through deployment and retirement.

Question 744

A business case reports: A decommissioned model endpoint retains credentials and raw request logs without an owner. What is the strongest reason the current assumption is unsafe?

  1. Shared broad administrative credentials can let a compromised agent read unrelated business data or alter protected systems.
  2. Infrastructure monitoring cannot by itself prove generated answers are safe or that tool actions are authorized.
  3. Claiming SAIF adherence without implementing measurable controls can conceal prompt injection, data exposure and unreviewed changes.
  4. Bolting security onto the chatbot interface alone can leave training data, connectors and tool execution exposed.

Explanation

Correct Answer

D:

This case exposes a specific failure mode: Bolting security onto the chatbot interface alone can leave training data, connectors and tool execution exposed. In the situation A decommissioned model endpoint retains credentials and raw request logs without an owner, the recommended response is: Apply threat modeling, access controls, data review, testing and monitoring from data acquisition through deployment and retirement. Independent evidence would be: A lifecycle security review tests unauthorized source access, dangerous tool calls, output handling and operational response.

Incorrect Answers

A:

This choice addresses iam least privilege for ai services; its main associated risk is: Shared broad administrative credentials can let a compromised agent read unrelated business data or alter protected systems. However, the situation A decommissioned model endpoint retains credentials and raw request logs without an owner is primarily about secure ai throughout the lifecycle. The targeted decision is: Apply threat modeling, access controls, data review, testing and monitoring from data acquisition through deployment and retirement.

B:

This choice addresses security command center, monitoring and incident response; its main associated risk is: Infrastructure monitoring cannot by itself prove generated answers are safe or that tool actions are authorized. However, the situation A decommissioned model endpoint retains credentials and raw request logs without an owner is primarily about secure ai throughout the lifecycle. The targeted decision is: Apply threat modeling, access controls, data review, testing and monitoring from data acquisition through deployment and retirement.

C:

This choice addresses google secure ai framework (saif); its main associated risk is: Claiming SAIF adherence without implementing measurable controls can conceal prompt injection, data exposure and unreviewed changes. However, the situation A decommissioned model endpoint retains credentials and raw request logs without an owner is primarily about secure ai throughout the lifecycle. The targeted decision is: Apply threat modeling, access controls, data review, testing and monitoring from data acquisition through deployment and retirement.

Question 745

A business team evaluating generative AI encounters this situation: An executive assumes mentioning SAIF in a policy means the application is automatically secure. It must choose a solution that is useful, secure, properly sourced, and appropriate for its constraints. Which response best meets the business need and its stated limits?

  1. Apply threat modeling, access controls, data review, testing and monitoring from data acquisition through deployment and retirement.
  2. Use Google Cloud IAM and appropriately scoped service identities to enforce least-privilege access for AI applications and their tools.
  3. Use relevant Cloud security posture, threat findings and workload monitoring to detect and investigate AI service misconfigurations alongside application-specific evaluation.
  4. Use Google’s Secure AI Framework as a structured lens for threats, security controls and operating governance, not as a product that automatically certifies a system.

Explanation

Correct Answer

D:

The decisive detail is: An executive assumes mentioning SAIF in a policy means the application is automatically secure. The appropriate business or technical decision is: Use Google’s Secure AI Framework as a structured lens for threats, security controls and operating governance, not as a product that automatically certifies a system. The risk avoided is that claiming SAIF adherence without implementing measurable controls can conceal prompt injection, data exposure and unreviewed changes. Confirm the outcome through: A threat-to-control matrix maps relevant AI risks to implemented mitigations, test evidence and accountable owners.

Incorrect Answers

A:

This choice addresses secure ai throughout the lifecycle; its main associated risk is: Bolting security onto the chatbot interface alone can leave training data, connectors and tool execution exposed. However, the situation An executive assumes mentioning SAIF in a policy means the application is automatically secure is primarily about google secure ai framework (saif). The targeted decision is: Use Google’s Secure AI Framework as a structured lens for threats, security controls and operating governance, not as a product that automatically certifies a system.

B:

This choice addresses iam least privilege for ai services; its main associated risk is: Shared broad administrative credentials can let a compromised agent read unrelated business data or alter protected systems. However, the situation An executive assumes mentioning SAIF in a policy means the application is automatically secure is primarily about google secure ai framework (saif). The targeted decision is: Use Google’s Secure AI Framework as a structured lens for threats, security controls and operating governance, not as a product that automatically certifies a system.

C:

This choice addresses security command center, monitoring and incident response; its main associated risk is: Infrastructure monitoring cannot by itself prove generated answers are safe or that tool actions are authorized. However, the situation An executive assumes mentioning SAIF in a policy means the application is automatically secure is primarily about google secure ai framework (saif). The targeted decision is: Use Google’s Secure AI Framework as a structured lens for threats, security controls and operating governance, not as a product that automatically certifies a system.

Question 746

A gen AI initiative reports: An executive assumes mentioning SAIF in a policy means the application is automatically secure. Which acceptance test most directly validates the correction?

  1. A threat-to-control matrix maps relevant AI risks to implemented mitigations, test evidence and accountable owners.
  2. A cross-role test denies unauthorized data access and confirms the service identity has only required permissions.
  3. A seeded incident produces the intended security alert and an actionable trace without leaking protected prompts.
  4. A lifecycle security review tests unauthorized source access, dangerous tool calls, output handling and operational response.

Explanation

Correct Answer

A:

The key acceptance evidence for An executive assumes mentioning SAIF in a policy means the application is automatically secure is: A threat-to-control matrix maps relevant AI risks to implemented mitigations, test evidence and accountable owners. It checks whether the team actually implemented: Use Google’s Secure AI Framework as a structured lens for threats, security controls and operating governance, not as a product that automatically certifies a system. A product configuration, demo, or persuasive response alone is not proof.

Incorrect Answers

B:

This choice addresses iam least privilege for ai services; its main associated risk is: Shared broad administrative credentials can let a compromised agent read unrelated business data or alter protected systems. However, the situation An executive assumes mentioning SAIF in a policy means the application is automatically secure is primarily about google secure ai framework (saif). The targeted decision is: Use Google’s Secure AI Framework as a structured lens for threats, security controls and operating governance, not as a product that automatically certifies a system.

C:

This choice addresses security command center, monitoring and incident response; its main associated risk is: Infrastructure monitoring cannot by itself prove generated answers are safe or that tool actions are authorized. However, the situation An executive assumes mentioning SAIF in a policy means the application is automatically secure is primarily about google secure ai framework (saif). The targeted decision is: Use Google’s Secure AI Framework as a structured lens for threats, security controls and operating governance, not as a product that automatically certifies a system.

D:

This choice addresses secure ai throughout the lifecycle; its main associated risk is: Bolting security onto the chatbot interface alone can leave training data, connectors and tool execution exposed. However, the situation An executive assumes mentioning SAIF in a policy means the application is automatically secure is primarily about google secure ai framework (saif). The targeted decision is: Use Google’s Secure AI Framework as a structured lens for threats, security controls and operating governance, not as a product that automatically certifies a system.

Question 747

A business team evaluating generative AI encounters this situation: A team uses a security framework to evaluate data poisoning and model misuse risks. It must choose a solution that is useful, secure, properly sourced, and appropriate for its constraints. What should the initiative prioritize to address the primary issue?

  1. Use Google’s Secure AI Framework as a structured lens for threats, security controls and operating governance, not as a product that automatically certifies a system.
  2. Apply threat modeling, access controls, data review, testing and monitoring from data acquisition through deployment and retirement.
  3. Use Google Cloud IAM and appropriately scoped service identities to enforce least-privilege access for AI applications and their tools.
  4. Use relevant Cloud security posture, threat findings and workload monitoring to detect and investigate AI service misconfigurations alongside application-specific evaluation.

Explanation

Correct Answer

A:

The decisive detail is: A team uses a security framework to evaluate data poisoning and model misuse risks. The appropriate business or technical decision is: Use Google’s Secure AI Framework as a structured lens for threats, security controls and operating governance, not as a product that automatically certifies a system. The risk avoided is that claiming SAIF adherence without implementing measurable controls can conceal prompt injection, data exposure and unreviewed changes. Confirm the outcome through: A threat-to-control matrix maps relevant AI risks to implemented mitigations, test evidence and accountable owners.

Incorrect Answers

B:

This choice addresses secure ai throughout the lifecycle; its main associated risk is: Bolting security onto the chatbot interface alone can leave training data, connectors and tool execution exposed. However, the situation A team uses a security framework to evaluate data poisoning and model misuse risks is primarily about google secure ai framework (saif). The targeted decision is: Use Google’s Secure AI Framework as a structured lens for threats, security controls and operating governance, not as a product that automatically certifies a system.

C:

This choice addresses iam least privilege for ai services; its main associated risk is: Shared broad administrative credentials can let a compromised agent read unrelated business data or alter protected systems. However, the situation A team uses a security framework to evaluate data poisoning and model misuse risks is primarily about google secure ai framework (saif). The targeted decision is: Use Google’s Secure AI Framework as a structured lens for threats, security controls and operating governance, not as a product that automatically certifies a system.

D:

This choice addresses security command center, monitoring and incident response; its main associated risk is: Infrastructure monitoring cannot by itself prove generated answers are safe or that tool actions are authorized. However, the situation A team uses a security framework to evaluate data poisoning and model misuse risks is primarily about google secure ai framework (saif). The targeted decision is: Use Google’s Secure AI Framework as a structured lens for threats, security controls and operating governance, not as a product that automatically certifies a system.

Question 748

A business case reports: A team uses a security framework to evaluate data poisoning and model misuse risks. Which failure mode makes this approach unsuitable?

  1. Shared broad administrative credentials can let a compromised agent read unrelated business data or alter protected systems.
  2. Bolting security onto the chatbot interface alone can leave training data, connectors and tool execution exposed.
  3. Claiming SAIF adherence without implementing measurable controls can conceal prompt injection, data exposure and unreviewed changes.
  4. Infrastructure monitoring cannot by itself prove generated answers are safe or that tool actions are authorized.

Explanation

Correct Answer

C:

This case exposes a specific failure mode: Claiming SAIF adherence without implementing measurable controls can conceal prompt injection, data exposure and unreviewed changes. In the situation A team uses a security framework to evaluate data poisoning and model misuse risks, the recommended response is: Use Google’s Secure AI Framework as a structured lens for threats, security controls and operating governance, not as a product that automatically certifies a system. Independent evidence would be: A threat-to-control matrix maps relevant AI risks to implemented mitigations, test evidence and accountable owners.

Incorrect Answers

A:

This choice addresses iam least privilege for ai services; its main associated risk is: Shared broad administrative credentials can let a compromised agent read unrelated business data or alter protected systems. However, the situation A team uses a security framework to evaluate data poisoning and model misuse risks is primarily about google secure ai framework (saif). The targeted decision is: Use Google’s Secure AI Framework as a structured lens for threats, security controls and operating governance, not as a product that automatically certifies a system.

B:

This choice addresses secure ai throughout the lifecycle; its main associated risk is: Bolting security onto the chatbot interface alone can leave training data, connectors and tool execution exposed. However, the situation A team uses a security framework to evaluate data poisoning and model misuse risks is primarily about google secure ai framework (saif). The targeted decision is: Use Google’s Secure AI Framework as a structured lens for threats, security controls and operating governance, not as a product that automatically certifies a system.

D:

This choice addresses security command center, monitoring and incident response; its main associated risk is: Infrastructure monitoring cannot by itself prove generated answers are safe or that tool actions are authorized. However, the situation A team uses a security framework to evaluate data poisoning and model misuse risks is primarily about google secure ai framework (saif). The targeted decision is: Use Google’s Secure AI Framework as a structured lens for threats, security controls and operating governance, not as a product that automatically certifies a system.

Question 749

A business team evaluating generative AI encounters this situation: A program needs a consistent vocabulary for model, application and infrastructure risks. It must choose a solution that is useful, secure, properly sourced, and appropriate for its constraints. Which approach is most defensible under these requirements?

  1. Apply threat modeling, access controls, data review, testing and monitoring from data acquisition through deployment and retirement.
  2. Use relevant Cloud security posture, threat findings and workload monitoring to detect and investigate AI service misconfigurations alongside application-specific evaluation.
  3. Use Google’s Secure AI Framework as a structured lens for threats, security controls and operating governance, not as a product that automatically certifies a system.
  4. Use Google Cloud IAM and appropriately scoped service identities to enforce least-privilege access for AI applications and their tools.

Explanation

Correct Answer

C:

The decisive detail is: A program needs a consistent vocabulary for model, application and infrastructure risks. The appropriate business or technical decision is: Use Google’s Secure AI Framework as a structured lens for threats, security controls and operating governance, not as a product that automatically certifies a system. The risk avoided is that claiming SAIF adherence without implementing measurable controls can conceal prompt injection, data exposure and unreviewed changes. Confirm the outcome through: A threat-to-control matrix maps relevant AI risks to implemented mitigations, test evidence and accountable owners.

Incorrect Answers

A:

This choice addresses secure ai throughout the lifecycle; its main associated risk is: Bolting security onto the chatbot interface alone can leave training data, connectors and tool execution exposed. However, the situation A program needs a consistent vocabulary for model, application and infrastructure risks is primarily about google secure ai framework (saif). The targeted decision is: Use Google’s Secure AI Framework as a structured lens for threats, security controls and operating governance, not as a product that automatically certifies a system.

B:

This choice addresses security command center, monitoring and incident response; its main associated risk is: Infrastructure monitoring cannot by itself prove generated answers are safe or that tool actions are authorized. However, the situation A program needs a consistent vocabulary for model, application and infrastructure risks is primarily about google secure ai framework (saif). The targeted decision is: Use Google’s Secure AI Framework as a structured lens for threats, security controls and operating governance, not as a product that automatically certifies a system.

D:

This choice addresses iam least privilege for ai services; its main associated risk is: Shared broad administrative credentials can let a compromised agent read unrelated business data or alter protected systems. However, the situation A program needs a consistent vocabulary for model, application and infrastructure risks is primarily about google secure ai framework (saif). The targeted decision is: Use Google’s Secure AI Framework as a structured lens for threats, security controls and operating governance, not as a product that automatically certifies a system.

Question 750

The business case is: A program needs a consistent vocabulary for model, application and infrastructure risks. Which TWO options together provide a suitable intervention and an independent acceptance check? (Select TWO.)

  1. Use Google’s Secure AI Framework as a structured lens for threats, security controls and operating governance, not as a product that automatically certifies a system.
  2. Apply threat modeling, access controls, data review, testing and monitoring from data acquisition through deployment and retirement.
  3. Use relevant Cloud security posture, threat findings and workload monitoring to detect and investigate AI service misconfigurations alongside application-specific evaluation.
  4. A cross-role test denies unauthorized data access and confirms the service identity has only required permissions.
  5. A threat-to-control matrix maps relevant AI risks to implemented mitigations, test evidence and accountable owners.

Explanation

Correct Answers

A:

The intervention for the stated situation A program needs a consistent vocabulary for model, application and infrastructure risks is: Use Google’s Secure AI Framework as a structured lens for threats, security controls and operating governance, not as a product that automatically certifies a system. It directly mitigates: Claiming SAIF adherence without implementing measurable controls can conceal prompt injection, data exposure and unreviewed changes.

E:

A separate outcome check for the situation A program needs a consistent vocabulary for model, application and infrastructure risks is: A threat-to-control matrix maps relevant AI risks to implemented mitigations, test evidence and accountable owners. It measures the effect of the selected intervention rather than relying on the existence of a proposal.

Incorrect Answers

B:

This choice addresses secure ai throughout the lifecycle; its main associated risk is: Bolting security onto the chatbot interface alone can leave training data, connectors and tool execution exposed. However, the situation A program needs a consistent vocabulary for model, application and infrastructure risks is primarily about google secure ai framework (saif). The targeted decision is: Use Google’s Secure AI Framework as a structured lens for threats, security controls and operating governance, not as a product that automatically certifies a system.

C:

This choice addresses security command center, monitoring and incident response; its main associated risk is: Infrastructure monitoring cannot by itself prove generated answers are safe or that tool actions are authorized. However, the situation A program needs a consistent vocabulary for model, application and infrastructure risks is primarily about google secure ai framework (saif). The targeted decision is: Use Google’s Secure AI Framework as a structured lens for threats, security controls and operating governance, not as a product that automatically certifies a system.

D:

This choice addresses iam least privilege for ai services; its main associated risk is: Shared broad administrative credentials can let a compromised agent read unrelated business data or alter protected systems. However, the situation A program needs a consistent vocabulary for model, application and infrastructure risks is primarily about google secure ai framework (saif). The targeted decision is: Use Google’s Secure AI Framework as a structured lens for threats, security controls and operating governance, not as a product that automatically certifies a system.