HiddenLayer vs Zscaler
Relationship
HiddenLayer AI Security Platform and Zero Trust Exchange do comparable work on threat detection and response; both also serve buyers who need to detect and respond to security threats; similar scale (public).
Assembled from the recorded fields for this pair, not hand-checked. The comparison below is read from each company’s own profile.
4 of 4 capabilities — Shares data security, evaluation and observability, guardrails and safety and 1 more.
Ludbee capability tags · from the product recordsShared product type — Both ship application and platform.
Ludbee product recordsAligned comparison
Capability overlap
Shared · 4
Identical capability tags — the difference is in execution, not scope.
Products, side by side
Algorithmic pairing — assembled from recorded fields, not hand-checked
HiddenLayer
Application
Protects the orchestration layer connecting AI coding agents to tools, memory, files and enterprise systems, detecting agentic-specific threats like memory poisoning and prompt injection with platform-aware controls for Claude Code, Cursor and GitHub Copilot.
Runs adversarial attacks against a customer's own models to find where they break before an attacker does.
Inventories every model, agent and AI workflow running in an organisation, so security teams know what exists before defending it.
Watches models in production and blocks attacks against them as they happen.
Scans models an organisation builds, buys or borrows for tampering and malicious content before they reach production.
Platform
Security platform purpose-built for AI systems: discovers models and AI supply chains across an organisation, simulates attacks against them, and detects runtime abuse such as model theft, data poisoning and adversarial inputs.
Zscaler
Application
Governance layer for employee use of generative AI that discovers shadow AI applications, applies allow, block or coach policies per user, and monitors prompts and responses against more than 100 data loss prevention dictionaries to stop sensitive data leaving through AI tools.
AI security posture management that auto-discovers and classifies AI models, agents and services across Azure AI Foundry, Amazon Bedrock, Google Vertex AI and unmanaged providers, correlates the sensitive data connected to them, and maps findings to frameworks including NIST AI RMF 600-1 and the EU AI Act.
Runs AI models over the security data flowing through the Zero Trust Exchange, using attack graphs, user risk scoring and threat intelligence to score the probability of a breach, forecast an attacker's next tactics, and recommend policy changes before the attack completes.
AI-driven detection and diagnosis of digital-experience issues across the network and application delivery path.
Platform
Cloud-native security platform that inspects and enforces policy on every connection between users, devices, workloads and AI agents, rather than trusting anything on a corporate network.
No counterpart
Zscaler sells these in a stack layer with no product recorded for HiddenLayer yet — nothing on the other side to compare them against.
API service
Real-time guardrails for LLM traffic that inspect prompts and responses inline to block prompt injection, jailbreaks, sensitive-data leakage and toxic or off-topic output, deployed either as a proxy or as an API-based Detection as a Service.
Inline, AI-powered sandbox that analyzes unknown files in real time to block zero-day and file-based malware before it reaches endpoints, using AI/ML models trained on 600M+ samples.
Developer tool
Automated adversarial testing for AI applications and agents that runs simulated attacks using 25+ predefined and custom probes across text, image, voice and document inputs, scoring results for security, safety, hallucination and business alignment against MITRE ATLAS, NIST AI RMF and the OWASP LLM Top 10.