AI Penetration Testing

We evaluate your AI systems to uncover vulnerabilities and ensure your organization’s use of AI is robust, secure, and compliant.

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LET US HELP: Our AI penetration testing transforms complex AI security concerns into actionable insights. We offer specialized testing for internal AI models, external AI interfaces, and even physical interactions with AI systems. With experience spanning the private sector, public sector, and military applications, our methodology is built on a foundation of thorough, real-world testing. Our comprehensive reports go beyond identifying vulnerabilities — they help you understand the potential impact of those issues on your operations.

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EXTERNAL AI PENETRATION TESTING: External AI testing is conducted from the viewpoint of an outsider attempting to compromise your AI systems from outside your network.

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Our external AI testing objectives include:

  • Identifying vulnerabilities in AI interfaces, APIs, and machine learning models accessible to external users.
  • Evaluating the resilience of AI-driven systems against adversarial attacks, such as data poisoning and model inversion.
  • Assessing the effectiveness of security measures that protect AI systems from unauthorized external access.

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INTERNAL AI PENETRATION TESTING: Internal AI testing assumes an attacker has gained access to your internal network and aims to exploit AI systems from within.

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The goals of internal AI penetration testing are to:

  • Assess the robustness of internal controls safeguarding AI model training, data integrity, and system outputs.
  • Simulate insider threat scenarios, including unauthorized access to training data and inference model parameters.
  • Ensure data protection mechanisms are in place to prevent unauthorized data extraction from sensitive AI processes.

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PHYSICAL AI PENETRATION TESTING: Physical AI security testing evaluates the physical and environmental protections surrounding AI hardware, such as edge devices, on-premises servers, and IoT-connected AI units.

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Our physical AI security testing objectives include:

  • Identifying security gaps in physical infrastructure that houses critical AI systems (e.g., security cameras, access systems, environmental controls).
  • Testing physical protocols related to AI hardware (keycards, access points, and on-site security personnel).
  • Conducting on-site, real-world testing with our experts to simulate attempted physical compromises on AI equipment and hardware.

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Our AI penetration testing services empower you to navigate the complexities of AI security with confidence, ensuring your systems are safeguarded against today’s rapidly evolving threat landscape.

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