HiddenLayer
by HiddenLayer
Security for AI models and agents — discovery, supply chain, runtime defence and attack simulation
HiddenLayer is an AI security platform that protects machine learning models and agentic systems across their lifecycle. It discovers shadow AI, scans model artifacts for malware and backdoors before deployment, defends running models against prompt injection and data leakage, and red-teams them continuously — all without needing access to training data or model internals.
HiddenLayer secures AI systems the way an endpoint or application security product secures conventional software, across four modules. AI Discovery inventories models, agents and AI services across an organisation's environments to eliminate shadow AI. AI Supply Chain Security scans model artifacts before deployment, validating integrity and detecting malware, backdoors and known vulnerabilities in serialised weights — a real attack surface, because common model formats can execute code on load. AI Runtime Security monitors production inference for prompt injection, data leakage and adversarial input, enforcing policy-aligned guardrails and extending to agentic and Model Context Protocol systems. AI Attack Simulation continuously red-teams deployed models to surface weaknesses before an adversary does. The architectural choice that defines the product is that it is model-agnostic, agentless and requires no training data: the platform observes the inputs and outputs of an algorithm rather than needing access to the raw data or the algorithm itself, which is what makes it deployable against third-party and vendor-supplied models a customer cannot inspect. Native connectors cover cloud platforms, CI/CD pipelines, data platforms, SIEM and SOAR tools, API gateways and MLOps stacks, so findings route into the security operations tooling a customer already runs. HiddenLayer was founded in March 2022 in Austin, Texas by Chris Sestito, Tanner Burns and James Ballard, and raised a $50 million Series A on 19 September 2023 co-led by M12, Microsoft's venture fund, and Moore Strategic Ventures, with Booz Allen Ventures, IBM Ventures, Capital One Ventures and Ten Eleven Ventures participating. At that round it described defending Fortune 100 models across finance, government and defence, and cybersecurity. It holds SOC 2 certification, and Microsoft has partnered with the company to deploy its Model Scanner within Azure AI.
A CISO whose organisation has already deployed AI models and agents faster than the security team can inventory them, and who has no existing control covering model artifacts or inference traffic.
A single control plane covering shadow-AI discovery, pre-deployment model scanning, runtime defence and continuous red-teaming, deployed agentlessly against models you may not own or be able to inspect.
At a Glance
- Category
- Governance & Security
- Pricing
- Contact for pricing, Subscription
- Target Market
- CISOs, CIOs, Security Architects, ML Engineers, Compliance Officers
- Deployment
- Cloud-first, Hybrid, Self-hosted
- Founded
- 2022
- Headquarters
- Austin, United States
- Customers
- Defends Fortune 100 models across finance, government and defence, and cybersecurity
Key Features
- ✓AI Discovery
Inventories models, agents and AI services across environments so security teams can see the shadow AI they are not currently governing.
- ✓AI Supply Chain Security
Scans model artifacts for malware, backdoors and vulnerabilities before deployment, closing a real code-execution risk in serialised weights.
- ✓AI Runtime Security
Detects and responds to prompt injection, data leakage and adversarial input in production without degrading inference performance.
- ✓AI Attack Simulation
Continuously red-teams deployed models against real-world attack techniques so weaknesses surface before an adversary finds them.
- ✓Agentless, model-agnostic design
Requires no training data or model internals, so it can protect third-party and vendor models a customer cannot inspect.
- ✓Agentic and MCP protection
Extends guardrails to autonomous agent execution and Model Context Protocol systems, added as agentic deployment moved into production.
- ✓Security ecosystem connectors
Native integrations for cloud, CI/CD, data platforms, SIEM, SOAR, API gateways and MLOps route findings into existing security workflows.
Capabilities
Use Cases
- •Vetting open-source models before deployment
Scan a model pulled from a public hub for embedded malware or backdoors before it reaches a production environment.
- •Eliminating shadow AI
Discover models and agents that business units deployed without security review, then bring them under policy.
- •Guardrailing customer-facing assistants
Detect prompt injection and block sensitive data leakage in live inference traffic on public-facing AI applications.
- •CI/CD gate for model releases
Wire model scanning into the deployment pipeline so an unsafe artifact fails the build rather than reaching production.
- •Continuous AI red-teaming for compliance
Run standing adversarial simulation to evidence ongoing AI risk testing for auditors and regulators.
Ideal For
Best For
- ✓Regulated enterprises in finance, government, defence and healthcare deploying AI under audit requirements
- ✓Scanning third-party and open-source model artifacts for malware and backdoors before they enter production
- ✓Discovering shadow AI where business units have deployed models and agents without security review
- ✓Adding runtime guardrails and prompt-injection detection to agentic and MCP-based systems
- ✓Continuous adversarial red-teaming of deployed models as a standing control rather than a one-off engagement
Not Ideal For
- ✗Organisations that only consume a hosted LLM API and deploy no models of their own, where the vendor's own controls already cover most of this surface
- ✗Small teams without a security operations function to triage findings — the SIEM and SOAR connectors assume someone is on the other end
- ✗Buyers expecting model scanning to be a complete defence, since automated scanners inherit the known limits of signature-based malware detection and independent evaluation of model-hub scanners has found both false positives and false negatives
- ✗Teams needing transparent budgeting up front, as HiddenLayer publishes no pricing
Integrations
Deployment
Market & Ratings
Defends Fortune 100 models across finance, government and defence, and cybersecurity
Market Analysis
Pros
- ✓Covers the whole AI lifecycle in one platform rather than only guardrails or only model scanning
- ✓Agentless and model-agnostic, so it works on third-party models a customer cannot open up — the common case in enterprise AI
- ✓Findings route into SIEM, SOAR and CI/CD through native connectors, so it fits existing security operations rather than adding another console to watch
- ✓Backed by M12, IBM Ventures, Booz Allen Ventures and Capital One Ventures, and Microsoft embeds its Model Scanner in Azure AI
Cons
- ✗Automated model scanning has structural limits: published research notes such scanners inherit the well-known weaknesses of signature-based malware detection, are often framework-specific in what formats they support, and sometimes duplicate safeguards the ML frameworks already implement
- ✗Independent evaluation of model-hub scanners has found both false positives and false negatives, so scan results are a signal rather than a verdict and still need human triage
- ✗No published pricing, no free tier and no self-serve trial, so evaluation requires a sales process before a buyer can size the spend
- ✗The market is young and crowded with Protect AI, Lakera, Robust Intelligence and CalypsoAI competing, and buyers have little independent benchmark data to compare detection quality across them
- ✗Independent practitioner discussion is thin — Hacker News returned no substantive threads on the product, so there is little unfiltered production feedback to weigh against vendor claims
Pricing
AISec Platform (enterprise)
Contact for pricing
- ✓AI Discovery
- ✓AI Supply Chain Security with Model Scanner
- ✓AI Runtime Security and guardrails
- ✓AI Attack Simulation
- ✓SIEM, SOAR, CI/CD and MLOps connectors
- ✓Agentless deployment
HiddenLayer publishes no pricing of any kind — there is no free tier, no self-serve trial and no list rate for any module, and every route on the site leads to a demo request. Expect an enterprise annual contract scoped by number of models, environments or scan volume, negotiated per deal. Because the four modules are separable capabilities, confirm at quote time which of Discovery, Supply Chain, Runtime and Attack Simulation are included rather than assuming the platform price covers all four.
Security & Compliance
Connect
Sources
This page was written from 6 sources, 4 on domains other than hiddenlayer.com.
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