What Is Zero Trust?

There are four key weaknesses of traditional security models from a security perspective:

• They expand the attack surface: Traditional tools like firewalls and VPNs expose IP addresses to the public internet. These IPs can be found not just by legitimate users, but also by cybercriminals looking for an attack surface.
• They struggle to stop compromise: Yesterday’s security is appliance based, and whether security tools are deployed as hardware or virtual appliances, they struggle to scale as needed to inspect encrypted traffic, where most threats hide. Most attacks pass through defenses undetected as a result.
• They enable lateral threat movement: Traditional approaches connect entities to the network in order to give them app access. But this entails implicit trust and excessive permissions that can be abused, enabling access to everything connected to that network, and fueling bigger breaches.
• They fail to stop data loss: Criminals attempt to exfiltrate sensitive data after scouring the network for it. This is accomplished more and more through encrypted traffic, because attackers know that most organizations rely on appliance-based security that will fail to secure said traffic. 

Zero trust is a unique architecture that brings a highly differentiated paradigm and methodology to cybersecurity. Here are five core pillars that outline what zero trust protects:

• Identity: Verify who is accessing the system
• Device: Confirm the device is compliant and trusted
• Network: Segment and isolate network traffic
• Application: Control access to specific applications
• Data: Protect sensitive information at rest and in transit

By adhering to these principles, zero trust enables organizations to minimize risk, reduce complexity, and better secure their distributed environments.

Zero trust is unique framework whereby organizations effectively have an intelligent switchboard that provides secure any-to-any connectivity, without extending the network to anyone or anything. In essence, the internet becomes the new corporate network.

Here’s how the architecture works at a high level: 

• Access requests begin with verification: Providing least-privileged access requires knowing who or what is attempting access. As such, every user or entity attempting to connect to an IT resource has its identity verified.
• Next, the destination is identified: Ultimately, zero trust means connecting entities directly to their destinations rather than to the network, preventing lateral movement. As such, once the user is verified, the IT resource she or he is trying to reach needs to be identified, as well, and its risk must be understood.
• Risk is calculated based on context: Identity alone is not sufficient to govern access to IT resources (they can be stolen, and even authorized users can do damage). So, as mentioned above, zero trust governs access based on risk, which is determined via AI/ML that assesses access context.
• Policy is enforced: Policy is automatically applied in real time and on a per-session basis, meaning for each access attempt. Several actions can be enforced, including allow, block, isolate, deceive, and more. Even after access is granted, continuous monitoring identifies risk changes in real time and alters policy as necessary.
• The connection is established: Users are connected directly to apps. While the connection is “inbound” to SaaS and the web, private apps require an inside-out connection, which is facilitated by an app connector that reaches out to the zero trust cloud so that it can stitch the full connection together. This eliminates the need for public IPs that expose applications. 

Traditional VPNs rely on a castle-and-moat security model that grants broad network access once users are inside. Zero trust takes a different approach, continuously verifying access and limiting it to only the specific apps and resources users need.

Zero trust provides both security and business benefits by shifting the security model to one founded on least-privileged access, including:

1. Enhanced cybersecurity: Zero trust decreases the likelihood of breaches and minimizes their potential blast radii by eliminating implicit trust in all of its various forms (network connectivity, public IPs, etc.), and enforcing contextual access, direct-to-app segmentation, and continuous monitoring.
2. Reduced complexity and cost: Zero trust cuts costs by consolidating security and networking point products into a single platform, simplifying IT infrastructure, enhancing admin efficiency and minimizing operational overhead. It also prevents breaches and their associated costs, enhances user productivity through improved digital experiences, and more. As a result of all this, zero trust strengthens an organization’s ability to invest in innovation and adapt to future challenges securely.
3. Improved user productivity: Direct-to-app connectivity delivered at the edge eliminates the need to backhaul traffic to a distant data center or cloud. This removes the latency associated with network hops, VPN bottlenecks, and other issues that harm user experiences.
4. Secure AI adoption and security: LLM security, AI agent access control, generative AI data protection, and prompt injection prevention are all simplified with with zero trust architecture underneath. When identity, context, and least-privilege access are at the core of your security framework, securing data, AI or otherwise, becomes less of a chore.

Zero trust principles can be applied across various scenarios to meet the diverse security needs of today’s organizations. Popular use cases include:

• Remote access without VPN: Enable users to securely and directly access private applications without exposing the network or relying on complex VPN connections.
• Protecting sensitive data: Zero trust platforms can provide data loss prevention (DLP) functionality that finds and secures sensitive information in motion to the web, at rest in the cloud, and in use on endpoints. 
• Securing workloads across multicloud environments: Workloads frequently interact with the web and with other workloads. Zero trust can secure these workload communications to stop threat infections and data leaks.
• IoT and OT security: Extend zero trust principles to branch sites, manufacturing plants, and other industrial environments, protecting IoT and OT devices by enforcing least-privileged policy controls.
• Third-party and partner access: Provide contractors, vendors, and technology partners with secure, zero trust access to IT resources without exposing your broader network and without using endpoint agents.
• AI security: Securely embrace AI models as your organization grows while preventing shadow AI and securing AI data with ease, reducing SOC burden and pressure on executive teams.

Zero trust for AI extends the "never trust, always verify" principle to artificial intelligence systems—including large language models (LLMs), AI agents, training data pipelines, and inference workloads. As the foundation of modern AI security, this approach ensures that as enterprises adopt GenAI copilots, autonomous agents, and AI-powered automation, each AI component becomes a new identity that must be continuously verified, authorized, and monitored.

Why AI Needs Zero Trust

• AI expands the attack surface: Every model, agent, and data pipeline is a potential entry point for adversarial manipulation, data exfiltration, or unauthorized access.
• Models and agents are new identities: Just as users and devices require verification, AI models and autonomous agents must be authenticated and authorized before accessing enterprise data or executing actions.
• Least-privilege applies to data access: AI systems should only access the minimum data required for a specific task—not entire datasets or unrestricted knowledge bases.
• Least agency limits autonomous actions: AI agents must operate within tightly scoped permission boundaries, preventing excessive or unintended actions that could impact critical systems.
• Continuous monitoring detects AI-specific threats: Zero trust requires real-time behavioral analysis to identify prompt injection, model drift, data poisoning, shadow AI usage, and adversarial evasion attempts.
• AI data pipelines must be secured end-to-end: From training data ingestion to model inference output, every stage of the AI lifecycle requires inline inspection, access governance, and policy enforcement.

By applying zero trust principles to AI, organizations prevent sensitive data from being exposed to unauthorized models, stop adversarial attacks before they manipulate outputs, and maintain governance over rapidly scaling AI deployments.

The Zscaler Zero Trust Exchange platform empowers organizations to fully embrace a zero trust security model by offering a cloud native architecture that securely connects users, workloads, devices, third parties, clouds, applications, and branch sites. Acting as an intelligent switchboard, the Zero Trust Exchange ensures that every transaction and every component of an organization’s IT ecosystem adheres to strict zero trust principles to:

• Minimize the attack surface: Eliminate firewalls and hide apps behind the Zero Trust Exchange, removing entry points for attackers.
• Stop compromise: A high-performance cloud inspects all traffic (including encrypted TLS/SSL traffic at scale) to enforce real-time threat detection capabilities and policies that stop threats.
• Prevent lateral movement: Zero trust segmentation keeps everyone and everything off the network, preventing lateral movement across network-connected resources.
• Block data loss: Data, AI or not, is protected wherever it goes, inline in encrypted traffic, at rest in SaaS and cloud apps, and on user devices, while AI Auto Data Classification minimizes the administrative burden.
• Improve user experience: Users enjoy fast, seamless, and direct access to the applications and data they need, without the friction of legacy VPNs.
• Simplify IT infrastructure and security operations: A unified, cloud native platform consolidates security functions and reduces complexity while lowering costs.

Zscaler Zero Trust for AI

Our Zero Trust Exchange is at the core of all of our AI Security capabilities:

• AI Asset Management: Get end-to-end visibility into your data and AI models to proactively protect against AI risks
• AI Access Security: Control access and content across popular GenAI apps, AI SaaS, embedded AI, and dev tools.
• Continuous Automated Red Teaming: Test, secure, and deploy enterprise AI with speed and confidence.
• AI Guardrails: Mitigate threats, prevent data loss, and moderate content with high-performance AI inspection.

Want to experience how the Zscaler Zero Trust Exchange can transform your organization’s security and operational efficiency? Request a demo of our platform today.