01 / DISCOVER
Which agents are running?
AI agent security
See your agents.
Control the behavior chain.
Discover the agents in your environment and understand their behavior chains. Monitor runtime activity, assess and block risks as they emerge, and combine pre-deployment assessment with runtime protection to reduce the risk of sensitive data leakage.
Risk visibility
Agent permissions keep expanding.
Security needs a new approach.
AI agents are evolving from question-answering tools into systems that plan tasks and call models, tools, skills, and external services. As these interactions grow more complex, organizations need answers to four basic questions.
02 / OBSERVE
What have they called and done?03 / TRACE
What data have they transmitted?04 / ASSESS
Do these actions pose a risk?Core capabilities
From agent discovery to risk control
Agent discovery and profiling
Automatically discover agents, identify their runtime environments, and map the models, tools, skills, MCP services, and related services they use.
Continuous behavior-chain visibility
Collect session context, task plans, tool calls, network requests, file operations, and other behavior data. Record agent inputs, outputs, and call relationships.
Runtime monitoring and risk blocking
Identify runtime risks from agent behavior. Intervene at decision and execution points with parameter constraints, action blocking, and human approval.
Sensitive data leakage detection and protection
Before deployment, assess configurations, permissions, and risky calls that could expose data. During operation, monitor unusual data and file activity and intervene in high-risk actions.
Two complementary products
Assess before deployment. Govern during operation.
Pre-deployment proactive security scan
Agent Security Assessment System
Proactively assess security before agent deployment, tool admission, and version changes.
Examine environments, models, configurations, tools, and other dimensions to identify risks. Produce a risk list, evidence, remediation recommendations, retesting results, and a security testing report.
Explore the assessment system →
Continuous governance after deployment
Agent Runtime Security Governance System
Continuously monitor and analyze agent behavior and related environment data after deployment.
Support agent profiling, runtime security monitoring, risk assessment, immediate controls, decision intervention, and agent security profiles.
Explore runtime security governance →
Governance loop
The path to AI agent security governance
01
Discover your agents
Identify which agents exist, where they run, and which models, tools, and skills they use.
02
Check security risks
Assess configuration, tool, skill, and environment risks at deployment, admission, and version-change points.
03
Monitor runtime behavior
Continuously observe task plans, tool calls, network requests, file operations, and data activity.
04
Assess and control risks
Identify ongoing risk events and apply constraints, blocking, or human approval at decision and execution points.
05
Build security profiles
Record each agent's risks and responses, and use continuous monitoring to establish a security baseline.
Start building security governance by understanding your agents
Tell us which agents you use, their application stage, and the security issues you care about. We can discuss a suitable approach to AI agent security governance.
Request a trialcontact@zhihuizhanxing.com