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Because AI-powered systems introduce risks beyond traditional security testing
Secure your AI systems with comprehensive security validation
With the rapid adoption of AI/ML across critical business functions, new attack vectors are emerging, ranging from prompt injection to model manipulation. CyRAACS’ AI Security Assessment offerings are designed to identify, validate, and mitigate these risks, ensuring your AI systems are secure, resilient, and trustworthy. The target audience for these AI security assessment services includes AI product companies, enterprises using LLMs, and BFSI organizations with LLM integrations.
AI Security Assessment Offerings
AI/ML Penetration Testing (pentesting)
Evaluate the resilience of your AI/ML systems through real-world attack simulations, uncovering vulnerabilities across models, data flows, and processing layers to ensure secure and reliable performance.
What we do:
AI Red Teaming
Simulate real-world adversaries to test how your AI systems withstand complex, multistage attacks—ensuring robust security across models, data, and decision-making
processes
What we do:
Our AI Security Assessments are designed to deliver real security outcomes for AI-driven systems
Risk-driven, real-world testing that validates actual AI exploitability
Coverage of AI-specific threats including prompt injection, model manipulation, and data leakage
Practitioner-led assessments combining adversarial testing, red teaming, and model-level analysis
Aligned with OWASP LLM Top 10, MITRE ATLAS, and NIST AI RMF security frameworks
Frequently Asked Questions
An AI Security Assessment is a specialized evaluation of AI/ML systems to identify vulnerabilities that traditional security testing often misses. With AI systems introducing risks like prompt injection, model manipulation, and data leakage, these assessments ensure your systems remain secure, reliable, and trustworthy.
Unlike traditional pentesting, AI/ML penetration testing focuses on model behavior, data pipelines, and inference mechanisms. It includes adversarial input simulation, testing model exploitation, and evaluating how AI systems respond to malicious or unexpected inputs.
AI Security Assessments uncover vulnerabilities such as:
AI Red Teaming simulates sophisticated, real-world adversaries to test AI systems against multi-stage attack scenarios. It helps identify deep-rooted security gaps by targeting safeguards, exploiting model behavior, and evaluating resilience against adversarial tactics
Adversarial inputs are carefully crafted inputs designed to mislead AI models into generating incorrect or harmful outputs. These can exploit weaknesses in training or inference, potentially compromising system accuracy and security
These assessments are aligned with globally recognized frameworks, including:
This ensures a structured and comprehensive approach to evaluating AI security risks.
CyRAACS delivers:
This holistic approach ensures comprehensive coverage of AI-specific threats and
actionable security outcomes.
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