Agent Security Center:AI Red Teaming

Overview

AI Red Teaming is a security assessment capability under Security Center Agent Security. It evaluates connected AI models and AI agents for security vulnerabilities such as prompt injection, jailbreak attacks, obfuscation and smuggling attacks, and data leakage. Add detection objects to run assessments and generate compliance test reports for pre-filing self-testing, helping enterprises strengthen AI defenses through offensive testing.

• Supported detection objects:

  • AI Model: Detects AI model services that use OpenAI-compatible or Anthropic-compatible APIs. Checks for security risks such as prompt injection and data leakage in large language models accessed via API.

  • AI Agent: Evaluates the security of agent applications deployed on platforms such as Alibaba Cloud Model Studio, Dify, and PAI.

• Detection results are available for download only. They are not auto-processed or synchronized to the Agent Threat list.

Prerequisites

A paid instance of Agent Security Center is activated. For more information, see Purchase and unsubscribe from Agent Security Center.

Add a detection object

1. Log on to the Security Center console.

2. In the left navigation pane, choose Agent Security > AI Red Teaming.

3. On the AI Red Teaming page, click Add Detection Target.

4. On the Target Information page, configure the following parameters. Then click Next to proceed to connection parameter configuration.

   Parameter	Description
   Target Name	A custom name used to identify and manage the detection object.
   Description	Optional. Enter a description for the detection object.
   Target Type	AI Model: For model services that use OpenAI-compatible or Anthropic-compatible APIs. AI Agent: For agent applications deployed on platforms such as Alibaba Cloud Model Studio and Dify. Note The parameters available in subsequent steps vary depending on the selected target type.
   Access Method	Displayed only when Target Type is set to AI Model. OpenAI Compatible: For model services that use the OpenAI Chat Completions API format, such as Alibaba Cloud Model Studio, Azure OpenAI, and various open-source model deployments. Anthropic Compatible: For model services that use the Anthropic Messages API format.
   Quick Access	Displayed only when Target Type is set to AI Agent. Supported platforms include Alibaba Cloud Model Studio, Dify, Agent Run, PAI, and AgentKit.

5. On the Connection Parameters tab, configure the connection parameters based on the target type. Then click Next to proceed to connection verification.

   AI model parameters

   Parameter	Description
   Streaming Output	Specifies whether to enable streaming output. Default value: Enabled.
   API Address	The API endpoint of the AI model. For example, the OpenAI-compatible API endpoint for Alibaba Cloud Model Studio is https://dashscope.aliyuncs.com/compatible-mode/v1.
   API Key	The access key used for authentication. For example, Alibaba Cloud Model Studio users can create an API key on the API Key Management page in the Model Studio console.
   Model Name	The name of the model to test. Examples for Alibaba Cloud Model Studio: qwen-plus, qwen-max.
   Platform	Select the platform to which the AI model belongs from the drop-down list, such as Alibaba Cloud Model Studio.

   AI agent parameters

   Basic parameters

   Parameter	Description
   Streaming Output	Specifies whether to enable streaming output. Important Streaming output is enabled by default for PAI and cannot be disabled.
   API Address	The API endpoint of the agent. PAI: Format: http://{uid}.{region}.pai-eas.aliyuncs.com/api/predict/{serviceName}/v1/chat/completions. Replace {uid}, {region}, and {serviceName} with the actual PAI-EAS service configurations. Alibaba Cloud Model Studio: https://dashscope.aliyuncs.com/api/v1/apps/{appId}/completion, where {appId} is the Model Studio application ID. Dify: Format: http://{host}/v1/chat-messages. Replace {host} with the actual Dify service endpoint. Agent Run: Format: https://{workspaceId}.agentrun-data.{region}.aliyuncs.com/agent-runtimes/{agentName}/endpoints/Default/invocations/openai/v1/chat/completions. Replace {workspaceId}, {region}, and {agentName} with the actual Agent Run configurations. AgentKit: Format: https://{id}.apigateway-{region}.volceapi.com/invoke. Replace {id} and {region} with the actual Agent Kit gateway configurations.
   API Key	The access key used for authentication. For example, Alibaba Cloud Model Studio users can create an API key on the API Key Management page in the Model Studio console.
   Model Name	Displayed only for the PAI platform. Enter the model name.

   Advanced settings (optional)

   Parameter	Description
   HTTP Method	The request method: GET, POST, or PUT. Default value: POST.
   Authentication Method	Select an authentication method: None, Bearer Token, or Custom Header.
   Authentication Header Name	Displayed only when Authentication Method is set to Custom Header. Enter a custom authentication header name.
   Timeout Period	The request timeout period, in milliseconds. Default value: 30000.
   Request Template	The request body template, preset by platform.
   JSONPath	The response parsing path, preset by platform.
   Request Header	Custom request headers in JSON format.

6. On the Test Connection tab, review the target details and click Connectivity Test to verify that the configured parameters can connect to the AI service.

   Important

   • Click Save only after the connectivity test passes. If the test fails, verify that the API endpoint, API key, and model name are correct.

   • The connectivity test verifies only network connectivity, the API key, and the API Address. It does not run an actual detection task.

   • Testing: The button displays a loading animation.

   • Test passed: The button changes to a success state, and the Save button becomes available.

   • Test failed: The failure reason is displayed in the Connection test failed. prompt area. If the failure is caused by network issues, click Retry to run the test again.

Configure Detection Task

1. Click the icon in the Actions column of the target detection object, and select Configure Detection Task.

2. In the Configure Detection Task panel, select a scan mode:

   Scan Mode	Description	Applicable Scenario
   Security Detection (default)	AI Red Teaming intelligent agent security adversarial testing based on red team experience.	For security adversarial testing.
   Compliance	Based on TC260 keywords and question banks to meet filing compliance assessment requirements.	For filing compliance self-testing.

3. Click OK to save the configuration.

Run detection

1. Select detection objects:

   • Single detection: Click Check in the Actions column next to the target detection object.

   • Batch detection: Select multiple detection objects, and then click Check below the AI Red Teaming list.

2. In the confirmation dialog box, click OK.

3. After the detection task is created, the list automatically refreshes and the detection status updates.

View detection tasks and reports

1. Click the icon next to the target detection object, and choose Test Records from the Actions menu. Alternatively, click the number in the Scan Count column.

2. In the Detection Records panel, view detection details. Filter by Scan Mode and Scan Progress.

   Column	Description
   Scan Task ID	The unique identifier of the detection task.
   Scan Mode	Security Detection or Compliance.
   Scan Start Time	The start time of the detection task.
   Scan End Time	The completion time of the detection task.
   Scan Task Progress	The task execution progress. Displays the completion percentage while running.
   Risk Level	The risk level detected in this scan.

3. View Report: After detection completes, click View Report in the Actions column to view the security assessment report for the agent or model. The report includes an overview, security score, attack distribution, risk matrix, attack technique analysis, attack intent analysis, attack case details, and security recommendations.

4. Download Report: After detection completes, click Actions in the menu, and then click Download Report to download the security report to your local device.

5. Download Hit Data: After detection completes, click Actions in the menu, and then click Download Hit Data to download the hit sample data in CSV format.

Stop or delete detection tasks

1. Click the icon next to the target detection object, and choose Test Records from the Actions menu. Alternatively, click the number in the Scan Count column.

2. In the Detection Records panel, click Stop or Delete in the Actions column next to the target task.

   Action	Applicable To	Effect
   Stop	Incomplete tasks only	Terminates the scan and retains the detection record.
   Delete	Tasks in all states	Terminates the scan and deletes the detection record.

Manage detection objects

Billing

• Billing unit: Billed by scan count. Each detection counts as 1 instance.

• Accumulation method: If the same object is detected multiple times, billing is accumulated based on the actual number of executions.

  Example: If you perform detection 10 times on an AI agent in Bailian, it will be counted as 10 instances.

• Billing condition: Charges are incurred only when the detection task is successfully completed. If the detection task fails or is aborted, no charge is incurred.

• Pricing: $138/instance.

FAQ