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Runtime security for AI agents is decided by what happens when the agent acts, not by which cloud app an employee was allowed to open. Agents do not just answer, they execute. They call tools, trigger workflows, and take real actions, and the attacks that matter arrive inside the action itself. The question is whether your security enforces on the agent's own tool calls, wherever that agent runs, or whether it governs access to public AI services and filters data on the way out. Those are two different jobs, and only one of them stops a malicious tool call as it fires.
TrustGuard is NeuralTrust's AI runtime security, and it is the first runtime security built to extend across every AI agent, without a custom integration rebuilt for each tool or framework. Netskope comes to AI from the other direction. It is a cloud-delivered SASE platform whose strength is access governance and data loss prevention, and its AI security extends that heritage: brokering access to public AI apps and public MCP servers, applying DLP to the traffic, and keeping audit trails. This comparison covers both on the terms that decide AI runtime security: whether protection enforces on the agent's tool calls, which agents it reaches, and whether the agent is treated as an identity acting in real time rather than traffic to govern and record.
TL;DR
- NeuralTrust enforces on the agent's tool calls. TrustGuard blocks or transforms the individual tool call in-flight based on injection, behavior, and identity. Netskope's agentic security brokers access to public MCP servers and applies DLP to the traffic.
- NeuralTrust protects every agent, including private and internal ones. Netskope's agentic broker centers on public MCP servers and the employee AI tools that reach them.
- NeuralTrust authenticates the agent to the tool and detects attacks live across the session. Netskope enforces least-privilege access and logs sessions for retrospective investigation.
- NeuralTrust runs in your private environment or the cloud. Netskope's AI security is cloud-delivered only.
NeuralTrust vs Netskope: AI Runtime Security at a Glance
| Capability | NeuralTrust | Netskope |
|---|---|---|
| Enterprise readiness | ✅ | ✅ |
| Flexible deployment (private, cloud) | ✅ | ❌ |
| Secures private and internal agents | ✅ | ❌ |
| Runtime enforcement on the tool call | ✅ | ❌ |
| Agent-to-tool authentication | ✅ | ❌ |
| Real-time session-aware detection | ✅ | ❌ |
NeuralTrust vs. Netskope: Platform Overview
What is NeuralTrust TrustGuard?
TrustGuard is NeuralTrust's AI runtime security. It inspects every interaction and stops attacks at the moment of execution, on every surface where your agents run: gateways, SDKs, browsers, and platforms. It was built for that job, and it enforces the way agents actually behave.
The design rests on one policy model that covers every threat class at once: injections, sensitive data, unsafe actions, and behavioral attacks. Collectors pull agent traffic from gateways, SDKs, browsers, sidecars, and log streams, protocol-typed policies run detection on every request and response, and the decision is enforced in-flight. Allow, block, or transform, before the action reaches your system. TrustGuard reads the session, the identity, and the protocol together, so it catches the indirect prompt injection hidden in a poisoned tool result, the agent reaching for a tool it should never touch, the automated loop burning through tool calls, and the exfiltration buried in a tool input, and it acts before any of it executes.
Because enforcement lands on the agent's own tool calls, TrustGuard protects the action itself, not just the app an employee opened or the data on its way out. It integrates natively with TrustGate, NeuralTrust's own AI gateway, and it extends across SDKs, browsers, and platforms with the same policy model. It runs in your private environment or in the cloud. That is what makes it the first runtime security built to reach every AI agent without a new integration for each one.
What is Netskope?
Netskope is a cloud-delivered SASE platform, known for secure web gateway, cloud access security brokering, and data loss prevention. Its AI security is an extension of that model, and it inherits the shape of a CASB. The through line is access governance and data protection, delivered from Netskope's cloud, rather than runtime enforcement on the agent.
Netskope's AI security spans several products. AI Command Center handles discovery, GenAI Security governs employee use of public AI apps, AI Guardrails moderate prompts and responses, and an AI Gateway inspects API traffic between apps and LLMs. Its agentic piece is the Agentic Broker, a proxy that decodes MCP traffic and centers on public MCP servers: discovering them, risk-scoring them, allowing or blocking access to cataloged public servers, applying DLP to the workflow, and logging sessions for retrospective investigation. It enforces least-privilege access to those servers and closes the gap between employees and the public MCP tools they reach. This is CASB and DLP applied to AI, governing access and protecting data, rather than enforcing on the agent's tool calls wherever that agent runs.
Flexible Deployment: Private and Cloud vs Cloud-Delivered Only
Where security runs decides which environments it can protect. Some of the most sensitive agents live in environments that will not route their traffic out to a vendor's cloud, and security that only exists as a cloud service cannot follow them there.
TrustGuard runs where you need it, in your own private environment or in the cloud. Runtime enforcement can live inside your perimeter, so the agents that matter most can be protected in place rather than only through an external service.
Netskope is cloud-delivered by design. Its entire platform routes traffic through its own cloud, and its AI security follows the same model, so protection exists only when traffic passes through Netskope. An organization that needs runtime security running inside its own environment, rather than as a service its traffic is sent to, cannot get that from a cloud-only platform. TrustGuard gives you the private option that a cloud-delivered service does not.
Secures Private and Internal Agents: Every Agent vs Public MCP Servers
Agents are not only the public tools employees open. They are the private, internal, and custom agents an organization builds and runs itself, calling internal tools and data. Runtime security has to protect those too, not just govern access to public services.
TrustGuard protects every agent with a single policy model, across gateways, SDKs, browsers, and platforms. Whether the agent is a public tool, a custom internal build, or a private workflow calling internal tools, the same rules on injections, sensitive data, unsafe actions, and behavioral attacks apply. This is the core of NeuralTrust's position. It is the first runtime security built to extend across every AI agent, without a custom integration rebuilt for each one.
Netskope's agentic security centers on public MCP servers and the employee AI tools that reach them. Its Agentic Broker discovers public MCP servers, risk-scores them, and controls access to cataloged public servers, which is protection scoped to the human-adjacent use of public agentic tools. The private, internal, and custom agents an organization runs on its own, and the tool calls they make, sit outside that public-server model. Governing which public MCP servers an employee's tool may reach is not the same as protecting every agent your organization actually runs. TrustGuard protects all of them.
Runtime Enforcement on the Tool Call: Blocking the Action vs Brokering Access and Filtering Data
The unit of enforcement decides which attacks it can stop. Controlling which server an agent may reach, and scanning the data that flows, does not decide whether a specific tool call is safe to execute.
TrustGuard enforces on the tool call itself. It reads the call, the response, the input, the session, and the identity together, and it blocks or transforms the individual action in-flight when it carries an indirect injection, an unsafe operation, or an exfiltration attempt. The dangerous moment is the call, and that is the unit TrustGuard acts on.
Netskope's agentic enforcement works at the access and data layers. Its Agentic Broker allows or blocks access to public MCP servers and applies DLP to the workflow, and it logs the session for later review. That governs whether an agent may talk to a given server and whether sensitive data leaves, but it does not judge each tool call on its own merits and stop the malicious one as it fires. An injection arriving inside an allowed tool response, or a harmful action sent to a permitted server, passes an access-and-DLP model that was never deciding the safety of the call itself. TrustGuard decides exactly that, on every call.
Agent-to-Tool Authentication: Identity at Runtime vs Least-Privilege Access
Least-privilege for agents starts with a question access rules alone do not answer: is this really the agent it claims to be, and is it entitled to use this tool right now? Restricting which servers a tool may reach is not the same as verifying the identity making the call.
TrustGuard controls how an agent authenticates to MCP tools at runtime. It ties the tool call to the agent's identity and enforces authentication and authorization together at the moment of execution, so an agent reaches only the tools it is entitled to, as the identity it actually is. Identity and permission are verified inline, in the same step as the action.
Netskope enforces least-privilege access to public MCP servers, deciding which cataloged servers may be reached, which is authorization applied at the access layer. It does not authenticate the agent to the tool as a runtime identity. Allowing or denying access to a server does not establish who the agent is when it makes the call, and an access rule cannot answer the identity question that agent-to-tool authentication is built for. TrustGuard closes that gap by making authentication part of the runtime decision.
Real-Time Session-Aware Detection: Catching It Live vs Retrospective Audit Trails
Attacks on agents rarely fit in one message. They build across turns, split an injection over a sequence, or escalate slowly. Whether you catch that depends on watching the session as it happens, not reading it afterward.
TrustGuard sees the conversation, not just the request. It tracks context across turns and factors identity, protocol, and metadata into every decision, so it catches multi-turn attacks while they are unfolding and blocks them before they complete. Session awareness is live, and it drives enforcement in the moment.
Netskope records the session for later. Its Agentic Broker logs detailed session information, tool requests, and responses to provide transparency for governance and retrospective investigations, which is an audit trail you read after the fact. A log that supports investigation after an incident is not the same as detection that stops a multi-turn attack while it is happening. Reconstructing what an agent did yesterday does not block what it is doing right now. TrustGuard acts in real time, on the live session.
Final Verdict
AI runtime security is decided inside the action, and inside the identity behind it. Security built to enforce on the agent's tool calls behaves differently from a cloud platform that governs access to AI services and filters the data that flows through it.
NeuralTrust built TrustGuard as runtime security from the start. It is the first runtime security built to extend across every AI agent, without a custom integration for each one. It enforces on the agent's own tool calls, it protects private and internal agents as well as public ones, it authenticates the agent to the tool at runtime, it detects multi-turn attacks live across the session, and it runs in your private environment or in the cloud. NeuralTrust is an independent company focused on AI runtime security, and TrustGuard is the product, not one module inside a sprawling SASE suite.
Netskope comes to AI from CASB and data loss prevention, and its AI security carries that shape. It governs access to public AI apps and public MCP servers, applies DLP to the traffic, and keeps audit trails, all delivered from its cloud. Its agentic broker centers on public MCP servers rather than every agent an organization runs, its enforcement works at the access and data layers rather than on the tool call, it enforces least-privilege access rather than authenticating the agent to the tool, and it logs sessions for review rather than catching multi-turn attacks live.
Both bring strong enterprise credentials, so enterprise readiness is not the deciding factor. The decision is whether you want runtime security that enforces on the agent's actions and runs in your own environment, or a cloud-delivered platform that governs access and protects data around those agents. If you are building on agents and you want protection that spans every one of them, enforces on the tool call, verifies the identity behind it, and catches attacks as they happen, NeuralTrust is built for exactly that.
Frequently Asked Questions about NeuralTrust vs. Netskope
1. What is the main difference between NeuralTrust and Netskope?
NeuralTrust TrustGuard is AI runtime security that enforces on the agent's own tool calls and extends across every agent with one policy model. Netskope is a cloud-delivered SASE platform whose AI security governs access to public AI apps and public MCP servers and applies DLP to the traffic. One enforces on the agent's actions, the other governs access and protects data around them.
2. Does Netskope protect private and internal agents the way NeuralTrust does?
Netskope's agentic security centers on public MCP servers and the employee AI tools that reach them, discovering, risk-scoring, and controlling access to cataloged public servers. The private, internal, and custom agents an organization runs itself, and the tool calls they make, sit outside that public-server model. NeuralTrust protects every agent, public, private, internal, and custom, from one policy model.
3. Does Netskope enforce on individual agent tool calls?
Netskope's Agentic Broker allows or blocks access to public MCP servers and applies DLP to the workflow, which governs which servers an agent may reach and whether sensitive data leaves. It does not judge each tool call on its own merits and block the malicious one as it fires. NeuralTrust enforces on the tool call itself, blocking or transforming the individual action based on injection, behavior, and identity.
4. Does Netskope authenticate agents to tools the way NeuralTrust does?
Netskope enforces least-privilege access to cataloged public MCP servers, which is authorization at the access layer. It does not authenticate the agent to the tool as a runtime identity. NeuralTrust ties the tool call to the agent's identity and enforces authentication and authorization together at the moment of execution.
5. Can both products run in a private environment?
NeuralTrust runs in your private environment or in the cloud, so runtime enforcement can live inside your perimeter. Netskope's AI security is cloud-delivered only, so protection exists when traffic passes through its cloud rather than running inside your own environment. That difference matters most for the agents you are least willing to route out to an external service.
About the Author
Alessandro Pignati is Lead AI Security Researcher at NeuralTrust, where he leads research on AI and agentic security, advancing techniques to evaluate and secure large language models and autonomous AI systems. He specializes in adversarial machine learning, AI red teaming, LLM security, and AI safety, contributing to the development of secure and trustworthy AI.
NeuralTrust is an AI agent security platform, recognized in the Gartner 2025 Market Guide for AI Gateways and Guardian Agents, and the KuppingerCole 2025 Leadership Compass for Generative AI Defense. Headquartered in Barcelona with ISO 27001 certification.
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