Configure check items

更新时间:
复制 MD 格式

Detection item configuration is used to manage detection services and protection dimensions for AI Guardrails. This topic describes how to view the Service list, enable protection dimensions, and configure detection rules and vocabularies in the console.

Procedure

  1. Log on to the AI Guardrails console.

  2. In the left-side navigation pane, choose Protection Configuration > Model Protection.

    The detection item configuration list displays the available Services:

    • AI Input Content Safety Detection (Pro edition) (query_security_check_pro): detects text content submitted to the large model.

    • AI Output Content Safety Detection (Pro edition) (response_security_check_pro): detects text content generated by the large model.

    • AIGC Input Image Security Detection (img_query_security_check): detects image content submitted by users.

    • AIGC Image Security Detection (img_response_security_check): detects image content generated by the large model.

  3. In the Actions column of the target Service, click Management to go to the Service management page.

  4. In the Protection Dimension area, view the detection capabilities supported by the current Service. Each protection dimension is displayed as a card with a toggle to enable or disable the feature.

    Text-based Services support the following protection dimensions:

    • Content compliance: detects pornographic, violent, political, and other undesirable content. Enabled by default.

    • Sensitive content detection: detects personal information or enterprise sensitive data that may be leaked.

    • Prompt injection detection: detects malicious prompts designed to bypass the safety limits of large models.

    • Malicious URL (public preview): scans content from large models for malicious links.

    • Model Hallucination (public preview): detects false or inaccurate information generated by large models.

    Note

    Enabling Sensitive content detection or Prompt injection detection incurs separate charges. For details, see Activation and billing.

  5. Vocabulary settings: In the detection item configuration list, configure a vocabulary for a text-based Service to add blocklist or allowlist entries. For details, see Vocabulary management.

Configuration management

On the Service management page, click Configuration Management on a Protection Dimension card to configure the detection toggles and detailed rules for each risk tag under that dimension.

Take AI Input Content Safety Detection (Pro edition) (query_security_check_pro) as an example. In the detection item configuration list, click Management in the Actions column.

  1. In the Protection Dimension area, click Configuration Management on the target dimension card (for example, Content compliance).

  2. Select the detection type to adjust, click Edit to enter edit mode, and modify the detection status.

    Note

    Difference between baseline rules and independent rules update mechanism

    • Using baseline rules directly: Detection capabilities automatically sync to the latest version as official updates are released. No manual adjustment is required.

    • Independent rules created by copying a Service: Updates to baseline rules do NOT automatically sync to copied independent rules. The independent rules retain their original configuration. To use the latest strategy on an independent rule, you must manually edit and synchronize the configuration. When you copy a Service, the new Service's configuration (including billing method, configurable items, and custom vocabulary settings) is the same as the source Service.

  3. Click Save. Changes take effect in approximately 2 to 5 minutes.

    Important

    Policy adjustment delay notice

    Due to the delay in policy propagation, testing immediately after a configuration change may produce inconsistent results or false positives (for example, phone numbers being incorrectly blocked). Wait for a period of time after modifying a policy before re-sending requests to verify that the latest policy has taken effect.

FAQ

What is the difference between desensitization, blocking, and observation for sensitive data detection?

In sensitive data detection configuration, you can configure the following three handling methods for each sensitive data tag:

  • Desensitization (Masking): Applies masking to detected sensitive data before outputting it. For example, a phone number 13812345678 is displayed as 1**********8, preserving the format without exposing the complete information.

  • Blocking: Directly intercepts the request. No original content is returned; instead, a block message is displayed. Suitable for scenarios with zero tolerance for sensitive data exposure.

  • Observation: Only performs detection logging without any interception. The content is output normally without modification or blocking. Suitable for the testing phase or when you need to understand the distribution of sensitive data before enabling active protection.

Can RAM users independently manage AI Guardrails configurations?

AI Guardrails configurations (such as detection rules and vocabularies) are managed centrally by the primary Alibaba Cloud account. RAM users cannot configure them independently.

All RAM users share the same set of mitigation policies and quotas. Configuration changes must be performed by the primary account (or a RAM user with the corresponding permissions) in the console. Each RAM user can only call APIs with authorized permissions.

How do I disable the logging feature to stop billing?

On the Configure check items page, set the Log Service toggle to No to disable the logging feature and stop incurring related charges.

Operation path: Log on to the AI Guardrails console. In the left-side navigation pane, choose Protection Configuration > Model Protection (or Agent Real-Time Protection) > Configure check items. On the target Service, click Management in the Actions column to go to the Service management page. Locate the Log Service toggle in the protection dimension area and set it to No.

What should I do if QR codes and watermarked content are correctly identified but I want to allow them?

If QR codes and watermarked content are correctly identified by AI Guardrails but you want to allow them in certain scenarios, you can disable the related risk tags in the configuration management of the corresponding protection dimension in the console.

If disabling the tags still does not meet your business requirements, you can submit a ticket to request backend adjustments.

Do I need to adjust the risk threshold after a model false-negative fix?

Model false-negative fixes are independent of score thresholds. You do not need to adjust thresholds or restore high-risk settings. The system automatically applies the improved detection capabilities after the fix is deployed. No additional action is required.