Alibaba Cloud Agent Security Center (referred to as "Agent Security Center") is a cloud-native integrated security product designed for the AI Agent era. As large model-driven agents are widely adopted in enterprises, agents face new security challenges in autonomous decision-making, tool invocation, and external interaction. Agent Security Center integrates multi-dimensional security capabilities to provide defense-in-depth protection for the entire lifecycle of agents.
Product overview
Agent Security Center is a native security infrastructure designed specifically for AI Agents. It builds an end-to-end security closed loop around the input and output, runtime behavior, data access, identity authentication, and network communication of agents. After agents acquire autonomous decision-making and action capabilities, Agent Security Center ensures that their behavior is controllable, data is compliant, identities are traceable, and runtime is protected.
Core architecture
Capability matrix
Capability module | Core features | Typical Scenarios |
AI guardrails | Input and output content detection, covering 6 major security dimensions | Preventing prompt injection, harmful content generation, and sensitive information leakage |
Runtime security | Process anomaly detection, high-risk behavior interception | Agent invoking malicious tools, unauthorized execution of system commands |
Data security | Data classification and grading, leakage prevention | Compliance control when agents process customer PII data |
Host security | Runtime detection, vulnerability protection | Security baseline and intrusion detection for the host machine where agents run |
Identity security | Unified identity management for humans, vehicles, and agents | Identity tracing and permission control in multi-agent collaboration scenarios |
Network control | Agent network access compliance | Security auditing and interception when agents access external APIs/URLs |
Configuration check | Agent deployment configuration security baseline detection | Pre-launch security configuration review, compliance verification |
Skills detection | Agent skill/plugin security scanning | Skills file security detection, malicious code identification |
AI Red Teaming | Adversarial security testing for agents | Pre-launch red team exercises, security boundary verification |
Detailed core capabilities
AI guardrails
AI guardrails are the first line of defense for agent interaction with the outside world, performing real-time detection on agent input and output, covering the following security dimensions:
Prompt injection protection: Identifies and intercepts adversarial prompt attacks targeting agents
Content safety: Filters harmful, non-compliant, and value-violating output content
Data leakage prevention: Detects whether output contains sensitive data or customer privacy information
Hallucination detection: Identifies factual errors in agent-generated content
Compliance verification: Ensures output complies with industry regulations and enterprise policies
Tool invocation security: Audits agent calls to external tools/APIs
Runtime security
Provides process-level security protection at the agent runtime layer, monitoring the agent behavior chain, and performing real-time alerting or blocking when anomalous operations are detected (such as unauthorized execution, malicious tool invocation, and high-risk system commands).
Data security
Performs classification and grading management of data processed by agents, implements leakage prevention policies across the entire data pipeline of input, processing, and output, ensuring that agents meet compliance requirements when processing customer data and business data.
Identity security
Builds a unified identity system integrating humans (human users), vehicles (vehicles/devices), and agents, enabling precise identity authentication, permission control, and behavior tracing in complex scenarios such as multi-agent collaboration and human-machine cooperation.
Configuration check
Performs security baseline detection on agent deployment configurations, automatically reviewing security configuration items before agent launch, including permission settings, network policies, log auditing, and other key configurations, ensuring that deployment complies with enterprise security standards and compliance requirements.
Skills detection
Performs security scanning on agent skill files (Skills), detecting malicious code, insecure configurations, and sensitive information leakage risks in Skills files. Supports static analysis of skill definition files such as Skill.md to identify potential security risks.
AI Red Teaming
Provides adversarial security testing capabilities for agents, simulating real attack scenarios to conduct red team exercises against agents, verifying the security boundaries of agents when facing threats such as prompt injection, jailbreak attacks, and tool abuse, helping enterprises discover and fix security vulnerabilities before launch.
Use cases
Scenario 1: Enterprise-level agent secure launch
Before deploying AI Agents in the production environment, enterprises use Agent Security Center to perform security baseline configuration, guardrail rule settings, and identity permission management, ensuring that agents are controllable from the moment they go live.
Scenario 2: Multi-agent collaboration security management
In scenarios where multiple agents collaborate to complete complex tasks, unified identity systems and network controls ensure trusted communication between agents, permission isolation, and auditable behavior.
Scenario 3: Agent external interaction protection
When agents need to invoke external APIs or access internet resources, the dual protection of network controls and AI guardrails prevents agents from being induced to access malicious resources or leak internal information.
Supported agent platforms
Agent Security Center supports integration with the following mainstream agent platforms. After activation, asset inventory and risk detection can be performed:
Agent platform | Integration method |
Dify | Supports public and private networks, integrated through endpoint and credentials. |
Alibaba Cloud Model Studio | Configure a RAM role within the Model Studio business workspace. Each business workspace requires separate configuration. |
Alibaba Cloud PAI | STS role-based service authorization integration. |
Alibaba Cloud AgentRun | STS role-based service authorization integration. |
Volcengine AgentKit | Multi-cloud AK authorization integration. |
OpenClaw | Additionally supports vulnerability scanning, configuration risk detection, and in-depth Skills detection, automatically integrated through the Security Center agent with no additional deployment required. |