Token Security unveils AI Discovery and AI Agent for secure AI environments
Token Security launches AI Discovery Engine and Token AI Agent to help enterprises govern and secure AI agents and machine identities.
Token Security has announced two groundbreaking innovations designed to help enterprises discover, govern, and secure AI agents and machine identities. The company launched the AI Discovery Engine for Non-Human Identities (NHIs) and the Token AI Agent, a conversational interface for real-time security intelligence.
AI Discovery Engine: Uncovering Hidden AI Agents
The AI Discovery Engine provides organizations with:
- Complete AI visibility: Identifies all NHIs and workloads using AI services, including AI connectors.
- Agent-aware intelligence: Reveals which AI agents leverage specific human or non-human identities, credentials, or resources.
- AI agent insights: Tracks interactions between AI agents across environments, systems, and clouds.
"This isn’t just another discovery tool. We’re enabling secure AI transformation by providing dynamic discovery and agile security," said Itamar Apelblat, CEO of Token Security.
Token AI Agent: Conversational Security Intelligence
Built on Token’s Model Context Protocol (MCP), the Token AI Agent allows security teams to interact with their environment using natural language. Users can ask questions like:
- "Which identities haven’t rotated secrets in 90 days?"
- "What secrets are exposed in my dev environments?"
- "Generate a script to resolve the top 5 riskiest NHIs."
The AI Agent supports dynamic querying across data layers, offering instant insights and remediation recommendations.
A Complete Solution for AI Governance
Together, these tools form a comprehensive solution for managing AI-native security environments. "We’re shifting from fragmented visibility to real-time, agent-driven intelligence," said Nissim Pariente, CPO at Token Security. The platform helps teams identify AI application usage, shadow AI, and enforce security policies.
Token Security’s innovations address the growing need for visibility and control in the age of Agentic AI, where traditional tools fall short. Learn more at Token Security.
Related News
AI Agents Fuel Identity Debt Risks Across APAC
Organizations must adopt secure authorization flows for AI environments rather than relying on outdated authentication methods to mitigate identity debt and stay ahead of attackers.
Dynamic Context Firewall Enhances AI Security for MCP
A Dynamic Context Firewall for Model Context Protocol offers adaptive security for AI agent interactions, addressing risks like data exfiltration and malicious tool execution.
About the Author
Dr. Lisa Kim
AI Ethics Researcher
Leading expert in AI ethics and responsible AI development with 13 years of research experience. Former member of Microsoft AI Ethics Committee, now provides consulting for multiple international AI governance organizations. Regularly contributes AI ethics articles to top-tier journals like Nature and Science.