Mindgard platform

Continuous Automated Red Teaming for AI

We empower enterprise security teams to deploy AI and GenAI securely. Leverage the world's most advanced Red Teaming platform to swiftly identify and remediate security vulnerabilities within AI. Minimize AI cyber risk, accelerate AI adoption, and unlock AI/GenAI value to your business.

Secure your AI, GenAI, and LLMs

AI/GenAI is increasingly deployed into enterprise applications. Mindgard enables you to continuously test and minimize security threats to your AI models and applications.

AI Comprehensive Testing

Comprehensive Testing

Developed and rigorously tested against a diverse range of AI systems over the past 6+ years to uncover risks within any model or application using neural networks. This includes multi-modal Generative AI and Large Language Models (LLMs), as well as audio, vision, chatbots, and agent applications.

Automated AI Red Teaming

Automated Efficiency

Automatically Red Team your AI/GenAI in minutes and receive instant feedback for security risk mitigation. Seamlessly integrate continuous testing into your MLOps pipeline to detect changes in AI security posture from prompt engineering, retrieval-augmented generation (RAG), fine-tuning, and pre-training.

Advanced Threat Library

Advanced Threat Library

We offer a market-leading AI attack library, continuously enriched by our team of PhD AI security researchers. Supported by Mindgard's dedicated team, you can test for requirements unique to your business.

Cyber security is a barrier to AI/GenAI adoption. Let's unlock it.

In-depth Security Testing of AI/GenAI

Created by award-winning UK scientists in AI security, the Mindgard platform allows you to rapidly security test AI across an expansive set of threats:

Jailbreak LLM


Clever use of inputs or commands to prompt a system to perform tasks or generate responses that go beyond its intended functions.

Extract AI Model


Attackers extract/reconstruct AI models, compromising security and exposing sensitive information.

Evasion attack to AI model


Occurs when an attacker alters a machine learning model's input or decision logic to generate incorrect or deceptive outputs.

Machine learning models reverse engineer


Aims to reverse-engineer a machine learning model to uncover sensitive information about its training data.

AI training data set manipulation


Deliberate tampering with a training dataset used by an AI model to manipulate its behavior and outcomes.

malicious prompt to trick AI

Prompt Injection

Malicious input added to a prompt, tricking an AI system into actions or responses beyond its intended capabilities.

Membership inference

Membership Inference

Tries to reveal if a particular data point was included within the training data of the model.

Red Teaming can reduce your LLM violation rate by 84%.

Secure Your AI

Whether building, buying or adopting, Mindgard gets AI and GenAI deployed securely.

Enterprise Grade Protection

Serve any AI model as needed,while keeping your platformsafe and secure. 

Help your Customers use Secure AI

Report and improve on AI security posturewith runtime protection for your customers.

Leading Threat Research

Built by expert AI security researchers. Our market-leading AI threat library contains hundreds of attacks, continuously updated against the latest threats. Lightning-fast and automated security testing of unique AI attack scenarios completed in minutes.

Having set the standard in the worlds’ intelligence and defence communities, we are now securing the Enterprise across the AI/ML pipeline.

Mindgard AI Models Pipeline protection
  • OWASP and Mindgard
  • Mitre Atlas and Mindgard
  • NIST and Mindgard
  • NCSC and Mindgard

Mindgard in the news

  • Mindgard’s Dr. Peter Garraghan on TNW.com Podcast / May 2024

    "We discussed the questions of security of generative AI, potential attacks on it, and what businesses can do today to be safe."

    Listen to the full episode at TNW.COM
  • Mindgard’s Dr. Peter Garraghan in Businessage.com / May 2024

    "Even the most advanced AI foundation models are not immune to vulnerabilities. In 2023, ChatGPT itself experienced a significant data breach caused by a bug in an open-source library."

    READ FULL ARTICLE AT businessage.com
  • Mindgard’s Dr. Peter Garraghan in Finance.Yahoo.com / April 2024

    "AI is not magic. It's still software, data and hardware. Therefore, all the cybersecurity threats that you can envision also apply to AI."

    READ FULL ARTICLE AT finance.yahoo.com
  • Mindgard’s Dr. Peter Garraghan in Verdict.co.uk / April 2024

    "There are cybersecurity attacks with AI whereby it can leak data, the model can actually give it to me if I just ask it very politely to do so."

    Read full article at verdict.co.uk
  • Mindgard in Sifted.eu / March 2024

    "Mindgard is one of 11 AI startups to watch, according to investors."

    Read full article at sifted.eu
  • Mindgard’s Dr. Peter Garraghan in Maddyness.com / March 2024

    "You don’t need to throw out your existing cyber security processes, playbooks, and tooling, you just need to update it or re-armor it for AI/GenAI/LLMs."

    Read full article at maddyness.com
  • Mindgard’s Dr. Peter Garraghan in TechTimes.com / October 2023

    "While LLM technology is potentially transformative, businesses and scientists alike will have to think very carefully on measuring the cyber risks associated with adopting and deploying LLMs."

    Read full article at Techtimes.com
  • Mindgard in Tech.eu / September 2023

    "We are defining and driving the security for AI space, and believe that Mindgard will quickly become a must-have for any enterprise with AI assets."

    Read full article at tech.EU
  • Mindgard in Fintech.global / September 2023

    "With Mindgard’s platform, the complexity of model assessment is made easy and actionable through integrations into common MLOps and SecOps tools and an ever-growing attack library."

    READ FULL ARTICLE AT fintech.global

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