AI risk discovery
Map models, knowledge bases, applications and tools, including data and permission boundaries.
AI Security
Lifecycle security for LLM, AIGC, RAG and agent applications across data, model, application and operations layers.
AI application security
Protect LLM, AIGC, RAG and agent applications across input data, model interaction, generated content and tool execution. Combine assessments and products for the environment.
Discuss this approachInputs & knowledgeModels & contentPolicy & risk decisionsAgents & toolsReview · Authorize · Audit
Key risks
- Prompt injection and knowledge-base access abuse
- Sensitive data reaching external models
- Agent tool actions exceeding authorization
Service scope
Model and application assessment
Design assessments for prompt injection, unauthorized access, harmful content and leakage.
Data egress protection
Use Xingshu and AI DLP approaches to govern data exchanged with models.
Agent execution control
Use AgentArbiter for authorization, policy decisions and execution audit.
Generated content governance
Use JuHeng to connect content checks, policy decisions, review and feedback.
Monitoring and improvement
Review incidents, policy matches and assessment results to refine controls.
Delivery process
Map applications
Identify model access, data inputs and tool calls.
Test risks
Define tests and control objectives for business scenarios.
Integrate controls
Apply data, content and execution policies at critical points.
Review and refine
Validate policy suitability using incident and audit records.
Deliverables
Scope, schedule and acceptance criteria are agreed following assessment.
Discuss this approachDeliverables to scope together
- AI application risk and test records
- Data, content and execution controls
- Integration and audit validation notes
Relevant environments
- Enterprise AI-assisted work and development
- Knowledge bases and assistants
- Agents and automation tools
Scope of services
- LLM application security architecture and gateway
- Model red teaming, supply-chain review and hardening
- AIGC content, RAG and Agent security
- AI DLP, monitoring, audit and continuous operations
Explore further
LLM Application Security
A unified security control point for prompt-injection defense, input/output inspection, sensitive-data protection, access control and model-call audit.
AI Agent Security
Control autonomous tool use through agent identity, least privilege, instruction isolation, allowlists, human approval and complete action audit.
AI Security
Project capabilities for AI security.