The Security Layer for AI Agents

Your AI Agents Have Keys to Everything. Who's Watching?

The real-time security gateway for Model Context Protocol. Detect prompt injection, block PII leakage, and audit every action your AI agents take before damage is done.

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Invitation only. Limited spots available.

300+
Threat Patterns
20
Secret Types Detected
4
Policy Actions
99.9%
Uptime SLA
INS MCP Security Gateway Dashboard — real-time threat monitoring for AI agents

Built for the MCP Threat Surface

Every connection between your AI agents and enterprise tools is a potential attack vector. We close them all.

Prompt Injection Detection

Identify and neutralize adversarial prompts before they reach your MCP servers. 300+ threat patterns, continuously updated.

300+ Patterns Real-Time

PII & Secret Protection

Automatically redact API keys, credentials, and personal data from agent context. 21 secret types detected in real time.

21 Secret Types Auto-Redact
Only in INS

Invocation-Level Analysis

We don't just check if an agent can call a tool. We analyze what each specific call will do. Same tool, different parameters, different risk level, different enforcement.

Per-Parameter Risk Runtime Classification
Only in INS

Multi-Step Attack Detection

Attackers spread exfiltration across multiple clean-looking calls. We track data provenance across the entire chain. The sequence is the detection, not the individual call.

Causal Chain Tracking Cross-Invocation Patterns
Only in INS

Day-One Protection

We use the agent's declared task as the baseline, not its history. An agent asked to 'summarize Q3 sales' that tries to send an email is suspicious from the first second. No weeks of learning what 'normal' looks like. The task description defines normal.

Zero Training Period Scope-Aware from Start
New

Compliance Framework Tracking

Automated mapping to EU AI Act, NIST AI RMF, ISO 42001, SOC 2, and OWASP LLM Top 10. Your configuration becomes compliance evidence automatically.

5 Frameworks Auto-Evidence
The Coverage Gap

Every Security Tool Has a Blind Spot for AI Agents

Existing infrastructure was built before autonomous agents existed. It protects against the threats it was designed for, not the ones agents create.

Security Tool What It Does Well Its AI Agent Blind Spot
API Gateways & MCP Proxies Authentication, rate limiting, basic access control Sees which tool was called. Cannot analyze what the specific parameters will cause the tool to do.
WAF / ModSecurity Blocks injection syntax, malformed requests A valid SELECT and a valid DROP TABLE look identical. Syntactic correctness ≠ safe operation.
DLP Systems Detect sensitive data patterns leaving the perimeter Don't know the data was collected 3 invocations ago by an AI agent operating outside its declared scope.
RBAC / ABAC Granular permission policies per role or attribute Grant or deny access to a capability as a whole, not to the specific operation inside each individual invocation.
UEBA / Behavioral Analytics Detect deviations from historical user baselines Baseline requires weeks of behavioral history. A new agent is unprotected until enough data accumulates.
Intelligent Nexus Security This is us Invocation-level parameter analysis, multi-step threat detection, causal data flow tracking Purpose-built for AI agent threat models. No blind spot in this column.
API Gateways & MCP Proxies
Does well

Authentication, rate limiting, basic access control

Blind spot

Sees which tool was called. Cannot analyze what the specific parameters will cause the tool to do.

WAF / ModSecurity
Does well

Blocks injection syntax, malformed requests

Blind spot

A valid SELECT and a valid DROP TABLE look identical. Syntactic correctness ≠ safe operation.

DLP Systems
Does well

Detect sensitive data patterns leaving the perimeter

Blind spot

Don't know the data was collected 3 invocations ago by an AI agent operating outside its declared scope.

RBAC / ABAC
Does well

Granular permission policies per role or attribute

Blind spot

Grant or deny access to a capability as a whole, not to the specific operation inside each individual invocation.

UEBA / Behavioral Analytics
Does well

Detect deviations from historical user baselines

Blind spot

Baseline requires weeks of behavioral history. A new agent is unprotected until enough data accumulates.

Intelligent Nexus Security This is us
Does well

Invocation-level parameter analysis, multi-step threat detection, causal data flow tracking

Purpose-built for AI agent threat models. No blind spot.

Sources: OWASP, NIST SP 800-162, ModSecurity CRS documentation, standard RBAC/ABAC implementations.

Deploy in Minutes, Not Months

One config change. No code modifications, no SDK.

1

Point Your Agents to the Gateway

Replace your MCP server URLs with the Intelligent Nexus endpoint. One config change. No code modifications, no SDK.

2

Define Your Security Policies

Set rules for PII handling, allowed tool calls, rate limits, and escalation paths. Use templates or build custom policies.

3

Monitor, Enforce, Adapt

Every agent action flows through the gateway. Review audit logs, respond to threats in real time, and refine policies as your AI infrastructure scales.

How It Works

Intelligent Nexus sits between your AI agents and MCP servers as a transparent security proxy.

INS MCP security gateway architecture diagram showing transparent proxy between AI clients and MCP servers

Defense in Depth for AI Security

Intelligent Nexus Security employs multiple security layers that work together to provide comprehensive protection against known and emerging threats.

Prompt Injection Detection

9 specialized patterns detect jailbreaks, instruction overrides, and role manipulation attempts.

Tool Poisoning Prevention

23 patterns detect hidden instructions, secrecy directives, and covert execution commands in tool descriptions and parameter schemas.

Secret & Credential Detection

20 patterns detect leaked API keys and tokens from AWS, GitHub, Slack, Azure, Stripe, OpenAI, MS Teams, and more.

Shadowing & Rug Pull Detection

Detects tool name conflicts across servers and tracks description changes via SHA-256 hashing to catch post-approval modifications.

Semantic Correlation

Tracks data flow across requests to detect exfiltration attempts and causal attack chains.

MCP threat detection dashboard with tool poisoning, prompt injection, and rug pull attack alerts for AI agents

Powerful Dashboard & Analytics

Get complete visibility into your AI agent security posture with real-time dashboards and detailed analytics.

MCP policy management interface for AI agent access control with deny, mask, notify, and require approval actions

Policy Management

Create and manage security policies with flexible rules and conditions.

AI agent session correlation tracking multi-step tool calls and data exfiltration chains across MCP requests

Session Correlation

Track request chains and identify attack patterns across sessions.

PII detection and secret leak prevention dashboard showing real-time data masking for AI agent workflows

Data Protection

Monitor sensitive data flows and enforce PII masking across all MCP tools.

MCP audit log with full traceability of AI agent tool calls for SOC 2 and GDPR compliance

Audit & Compliance

Complete audit trail for compliance with automated reporting.

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Frequently Asked Questions

What is MCP and why does it need security?
Model Context Protocol (MCP) is an open standard for AI agents to interact with external tools and data sources. MCP introduces new attack surfaces such as tool poisoning, rug pull attacks, and data exfiltration through tool responses. Intelligent Nexus Security sits between AI clients and MCP servers to detect and prevent these threats.
How does Intelligent Nexus Security integrate with existing MCP setups?
Intelligent Nexus Security deploys as a transparent proxy between your AI clients and MCP servers. Simply point your MCP clients to Intelligent Nexus Security instead of directly to your MCP servers. No code changes required on either the client or server side.
What MCP-specific threats does Intelligent Nexus Security detect?
Intelligent Nexus Security detects tool poisoning (malicious instructions hidden in tool descriptions and parameter schemas), rug pull attacks (tool descriptions silently modified after approval, tracked via SHA-256 hashing), tool shadowing (same tool name registered across different servers), secret and credential leaks (API keys, tokens, and webhooks from 20+ platforms), PII leakage through tool responses, data exfiltration attempts, and unauthorized tool access. Both requests and responses are scanned bidirectionally with 300+ specialized detection patterns.
Does Intelligent Nexus Security support policy-based access control?
Yes. You can define granular policies based on agent identity, tool name, MCP server, time of day, and request parameters. Policies support multiple actions including allow, deny, require approval, rate limiting, and response masking.
How can I join the waitlist?
Join the waitlist with your email. We're onboarding teams in batches and prioritizing organizations actively using MCP in production. You'll get access to the full platform including all security features, dashboard, and API.
How is INS different from other MCP security tools?
Most security tools check whether an agent is allowed to call a tool. We go deeper: we analyze what each specific call will actually do at runtime, track how data moves across multiple tool invocations, and detect threats from the very first interaction without needing a training period. This means we catch attacks that look perfectly normal at the individual request level.