AI Security

Our AI Security services are designed to secure your AI and machine learning models against adversarial attacks, data manipulation, and exploitation risks. Leveraging the OWASP LLM Top 10 guidelines, we address vulnerabilities such as insecure model APIs, data poisoning, and overprivileged access. Our approach also incorporates frameworks like NIST AI Risk Management Framework and ISO/IEC 23894, ensuring compliance with international AI security standards. We protect AI systems at every stage, from training data integrity to model deployment, by utilizing advanced tools for threat detection, anomaly analysis, and real-time monitoring. This end-to-end approach ensures the reliability and resilience of your AI-powered processes, minimizing risks and maximizing efficiency.

5-Step Methodology for AI Security Testing

Threat Assessment
Evaluate AI systems for vulnerabilities like adversarial attacks, biased models, and data integrity risks.
Model Validation
Test AI models against simulated attacks to assess robustness and accuracy under stress.
Data Analysis
Verify the security of training datasets to eliminate risks of poisoning or unauthorized manipulation.
Access Control Testing
Review and strengthen authentication mechanisms for AI model APIs and datasets.
Continuous Monitoring
Deploy AI-based monitoring tools to detect and respond to threats in real-time.
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