AI Penetration Testing Services

At the very beginning, we define the scope of the pentest and identify the specific AI systems to be tested. In this phase, we perform a threat modeling exercise to map potential attack vectors and determine the security goals. This ensures that the test is adapted to your unique AI systems and prioritizes areas that pose the highest risk.

Next, we conduct a detailed review of all AI-related assets and models within your organization. This includes a catalog of all machine learning models, datasets, APIs, and integrations that interact with the AI system. Comprehension of the full inventory helps us focus on the most critical areas that require protection and secure handling.

We use the OWASP AI Security Guide as a framework for identifying and mapping vulnerabilities within your AI systems. This comprehensive guide helps us assess security risks specific to machine learning models, training data, APIs, and deployment environments. We rely on the guide to ensure that we follow best practices and industry standards in security testing for AI-specific threats.

We simulate adversarial attacks on your models to test how they respond to manipulated inputs designed to trick or confuse them. Thus, we evaluate the model’s ability to detect and withstand input changes that could bypass security filters or cause incorrect outputs. We also test the model’s resilience to evasion tactics that may be used by attackers to avoid detection.

At this stage, we review your data pipelines and training processes to check for weaknesses that could lead to training data poisoning or manipulation. This includes verifying data sources, checking for biases, and ensuring that data integrity is maintained throughout the AI lifecycle. We assess if attackers could inject malicious data into the pipeline to influence model behavior.

Here, we test the security of all APIs and integrations that interact with the AI system. This includes checking for vulnerabilities such as poor authentication, unprotected endpoints, or misconfigured settings that could expose the model to unauthorized access or data leakage. We also assess how external systems that integrate with your AI might introduce additional security risks.

At this point, we evaluate the security configurations of your AI environment, including user access controls, permissions, and system settings. This review ensures that the AI models and related systems are not exposed to unnecessary risks due to misconfigurations. We check for improper access controls, such as excessive privileges or weak authentication methods, that could allow unauthorized users to gain access to sensitive components.

After completing the penetration test, we provide a detailed report outlining the detected vulnerabilities, the potential impact of each issue, and prioritized remediation steps. We offer actionable guidance on how to fix the problems and secure your AI systems.