Securing AI Agent
Communication
The first protocol-level trust framework preventing autonomous AI cyberattacks. Real-time identity verification and behavioral analysis for enterprise AI systems.
ACTION type="data_analysis"
TARGET resource="customer_insights"
Advanced behavioral analysis and policy enforcement for enterprise AI systems.
The AI Security Crisis is Here
Traditional security tools cannot see inside the opaque execution of autonomous AI agents. We are entering a new era of algorithmic threats.
November 2025 Incident
In the first documented large-scale AI-driven cyberattack, hackers utilized compromised Anthropic Claude instances to orchestrate autonomous attacks against Fortune 500 infrastructure.
80-90% Autonomous
Agents self-healed and adapted attack vectors without human input.
Traditional WAF Failure
Standard firewalls approved the traffic because it looked like valid API calls.
Legacy Security
Static API keys and IP whitelisting. No context awareness.
The AI Gap
Agents execute thousands of decisions per minute. Humans cannot review logs fast enough.
Protocol-Level Trust
Security must move to the communication layer itself.
Real-Time AI Trust Verification
A complete trust layer designed for the speed and complexity of autonomous agents.
Protocol-Level Security
The mtrust:// URI scheme intercepts all AI commands before execution, creating a mandatory security checkpoint.
Behavioral Trust Scoring
Dynamic 0-100 trust scores calculated in real-time based on agent intent, history, and anomaly detection.
Sub-Millisecond Performance
<2ms trust evaluation overhead ensures your AI agents remain responsive and efficient.
Decentralized Architecture
Trust scores are portable across organizations. Verify agents from partners without exposing internal data.
Contextual Policies
Define granular rules that override trust scores. 'Block financial transactions from agents < 3 days old'.
MCP Native Integration
Specifically engineered for the Model Context Protocol (MCP) to secure the next generation of AI apps.
Zero-Trust for AI Agents
The mTrust Protocol acts as an intelligent proxy between your agents and their tools.
Agent Command
mtrust://agent.id/action
Trust Gateway
Verifies identity signatures & calculates real-time trust score.
Policy Engine
Checks score against rules:
"If score > 80 allow DB write"
Approved
Command executes.
Decision logged to immutable ledger.
Request Demo Access
Experience mTrust Protocol in a secure enterprise environment. Contact us for qualified demonstrations.
Live Protocol Demonstration
See real-time trust evaluation, behavioral analysis, and policy enforcement in action.
Request Demo AccessReal-time Trust Scoring
Dynamic trust evaluation based on agent behavior and historical patterns.
Policy Enforcement
Context-aware security policies that adapt to risk levels and operational requirements.
Enterprise Integration
Seamless deployment in enterprise environments with existing security infrastructure.
Innovation Protected
mTrust Protocol is protected by pending patent applications covering our novel approach to decentralized, protocol-level AI trust management and behavioral verification.
A system and method for determining trust scores for autonomous artificial intelligence agents operating within a decentralized network protocol...
- URI-based interception methods
- Real-time behavioral scoring algorithms
- Context-aware policy enforcement engines
Enterprise-Ready Architecture
Built for high-throughput environments where security and performance matter.
Performance
- Trust Evaluation
- Real-time
- Policy Decision
- Instant
- Response Time
- Enterprise-grade
- Architecture
- Scalable
Security Standards
- Trust Scoring
- Behavioral Analysis
- Policy Engine
- Context-Aware
- Risk Assessment
- Multi-Level
- Decision Model
- Enterprise Security
Protecting Critical AI Deployments
Secure AI agents managing infrastructure and deployments. Prevent unauthorized configuration changes by autonomous dev-bots.
AI trading and transaction systems with behavioral oversight. Stop runaway trading agents before they violate risk parameters.
Patient data access with dynamic trust verification. Ensure medical agents only access records relevant to their current task context.