As AI agents become increasingly prevalent in enterprise environments, organizations face a new challenge: how do you manage identities that can autonomously access systems, make API calls, and interact with sensitive data?
Today, we're excited to announce AI Agent Management — a comprehensive solution for securing and controlling AI agent identities within your organization.
The Challenge of AI Agent Identity
Traditional identity management was designed for humans. Users authenticate, receive credentials, and operate within defined access boundaries. But AI agents are fundamentally different:
- Autonomous operation: AI agents can make thousands of API calls without human intervention
- Dynamic behavior: Their actions depend on prompts that can change at runtime
- Scaling concerns: A single agent can spawn multiple instances, each requiring access control
- Cost implications: Uncontrolled API usage can result in unexpected bills
- MCP servers: Agents connecting to Model Context Protocol servers introduce new attack vectors
Introducing AI Agent Identities
VeraID now supports a dedicated identity type specifically designed for AI agents. When you create an AI agent identity, you get a complete security and governance framework.
Token & Cost Budget Controls
Set granular spending limits at multiple levels:
- Daily token budget: Limit tokens consumed per day
- Monthly token budget: Cap total monthly token usage
- Per-request limits: Prevent single requests from consuming excessive resources
- Cost budgets: Set dollar-amount limits for daily and monthly spend
When an agent approaches its budget threshold (80%), you'll receive alerts. If it exceeds the limit, access is automatically restricted until manual review.
Provider & Model Controls
Control which AI providers and models your agents can access:
- Provider selection: Choose from OpenAI, Anthropic, Google, Mistral, Cohere, or custom providers
- Model allowlists: Specify exactly which models each agent can use (e.g., only gpt-4o-mini, not gpt-4)
- Capability controls: Define what actions agents are permitted to perform
Prompt Injection Detection
Our monitoring layer analyzes prompts in real-time to detect potential injection attacks:
- Configurable thresholds: Set sensitivity levels (0-1) for injection detection
- Automatic blocking: Suspicious patterns can automatically block requests
- Alert integration: Get notified via PagerDuty, Slack, or webhooks
- Audit trail: All flagged requests are logged for investigation
MCP Server Security
Model Context Protocol (MCP) servers are becoming essential infrastructure for AI agents. VeraID provides:
- Server registry: Maintain an inventory of all MCP servers in your organization
- Security scanning: Automatically scan servers for vulnerabilities and misconfigurations
- Verification status: Track which servers are verified, pending, or blocked
- Tool inventory: Know exactly what tools each MCP server exposes
AI Platform Integrations
Connect directly to AI platforms for unified visibility:
- OpenAI: Monitor API usage, costs, and model access
- Anthropic: Track Claude usage across your organization
- Google AI: Manage Gemini and Vertex AI access
- Custom platforms: Integrate with internal AI infrastructure
AI-Specific Risk Scoring
Our risk scoring engine includes factors specific to AI agent behavior:
- Prompt injection detected: +30 points when injection attempts are identified
- Capability abuse: +25 points for repeated denied capability requests
- Budget exceeded: +20 points when usage exceeds 80% of limits
- Unusual model usage: +15 points when agents use unexpected models
- High cost rate: +15 points for cost spikes above normal patterns
Comprehensive Audit Logging
Every action taken by an AI agent is logged with full context:
- The prompt that triggered it
- The model and provider used
- Resources accessed
- Tokens consumed and cost incurred
- Response metadata
This creates a complete audit trail for compliance, debugging, and security investigations.
Getting Started
AI Agent Management is available today for all VeraID customers. To create your first AI agent identity:
- Navigate to Identities in your VeraID dashboard
- Click Create Identity and select AI Agent as the type
- Choose your AI provider (OpenAI, Anthropic, Google, etc.)
- Configure allowed models and capabilities
- Set token and cost budget limits
- Enable prompt injection detection with your preferred threshold
- Generate credentials and integrate with your AI framework
We've published comprehensive documentation and SDK examples for popular AI frameworks including LangChain, CrewAI, AutoGPT, and custom implementations.
What's Next
This is just the beginning. We're actively developing:
- Agent-to-agent communication controls
- Multi-agent workflow orchestration
- Automated agent discovery across your infrastructure
- Real-time cost optimization recommendations
The future of enterprise AI requires purpose-built identity infrastructure. We're building it.