Secure your AI/ML systems and LLM applications against emerging threats. Our specialized AI security testing identifies vulnerabilities in models, training data, and AI-powered applications.
Specialized testing for the unique security challenges of AI and machine learning
Secure your valuable AI models, training data, and intellectual property from theft and manipulation.
Identify and mitigate model extraction attacks that could compromise your proprietary AI systems.
Detect data poisoning attempts and ensure the integrity of your AI training datasets.
Ensure your AI applications meet emerging regulatory requirements and ethical AI guidelines.
Comprehensive testing of your machine learning models against a wide range of attacks:
Test model robustness against crafted inputs designed to cause misclassification
Identify vulnerabilities that could allow attackers to steal your model
Assess susceptibility to training data manipulation attacks
Evaluate privacy risks from model queries revealing training data
Specialized security testing for LLM applications and AI-powered systems:
Test for prompt injection vulnerabilities in LLM applications
Identify ways attackers could bypass safety guardrails and filters
Test for unintended disclosure of sensitive information in responses
Assess vulnerabilities in RAG systems and context handling
Design test vectors
Execute attacks
Evaluate results
Full-scope security testing of your AI infrastructure and applications:
Test security of data ingestion, training, and deployment pipelines
Assess security of AI model APIs and third-party integrations
Evaluate models for unintended bias and discriminatory outputs
Verify adherence to AI regulations and ethical AI frameworks
A specialized approach to identifying vulnerabilities in AI and machine learning systems
We work with your team to understand your AI architecture, models, data sources, and use cases.
Identify AI-specific threats relevant to your models, including adversarial attacks and data poisoning.
Execute comprehensive testing including model robustness, LLM security, and infrastructure assessment.
Receive detailed recommendations and work with our experts to implement AI security best practices.
Protect your AI investments from emerging threats. Schedule your AI security assessment today.
AI security testing is a specialized assessment that identifies vulnerabilities unique to artificial intelligence and machine learning systems. This includes testing for adversarial attacks, prompt injection, model extraction, data poisoning, and other AI-specific threats outlined in OWASP Top 10 for LLMs and MITRE ATLAS.
We follow the OWASP Top 10 for Large Language Model Applications, MITRE ATLAS (Adversarial Threat Landscape for AI Systems), NIST AI Risk Management Framework, and the EU AI Act requirements. Our methodology covers the full AI attack surface from model to infrastructure.
We test for both direct and indirect prompt injection using a comprehensive library of attack techniques. This includes system prompt extraction, jailbreak attempts, context manipulation, instruction override attacks, and testing RAG pipeline vulnerabilities to ensure your LLM applications resist manipulation.
We offer both pre-deployment and production testing. For production AI systems, we use controlled testing methods that assess security without disrupting service. We also test staging environments with the same model configurations to identify vulnerabilities before they reach production.