Penetration Testing for Generative AI, Machine Learning, and Large Language Models (LLM)
In today’s rapidly evolving technological landscape, organizations are increasingly adopting Generative AI, Machine Learning, and Large Language Models to drive innovation. However, these powerful tools introduce unique security challenges that traditional cybersecurity approaches fail to address.
We specialize in comprehensive security testing for AI systems, helping organizations identify and mitigate risks before they become vulnerabilities.
Our AI Security Testing focuses on key areas of AI, ML, and LLM Testing:
- Model Adversarial Attacks
We simulate adversarial attacks to test the robustness of your ML models. By feeding specially crafted inputs, we assess whether the model can be manipulated into making incorrect predictions or classifications. - Data Poisoning and Model Manipulation
We perform data poisoning attacks that manipulate the training data, compromising the model’s ability to make accurate predictions. We also explore ways to manipulate the model’s behavior through this technique. - Model Inversion and Data Leakage
Our testing includes attempts to invert machine learning models, revealing sensitive training data or proprietary algorithms. We also assess the risk of unintended data leakage that could expose user or organizational data through model outputs. - API and Endpoint Security for AI Services
Many AI and ML models are exposed via APIs. Our penetration testing includes assessing the security of these APIs, looking for vulnerabilities such as unauthorized access, denial of service, or improper validation of input data. - LLM Prompt Injection and Exploitation
For Large Language Models (LLMs), we test for vulnerabilities such as prompt injection, where an attacker could manipulate model responses or gain unauthorized access to sensitive data through crafted inputs. - Bias and Ethical Vulnerabilities
We evaluate AI models for biases in decision-making and the potential ethical risks posed by automated systems, ensuring your AI products align with ethical standards and fairness principles. - Secure Model Deployment
We test the deployment process of AI systems to ensure that they are securely implemented in your environment, with proper access controls, encryption, and monitoring. - Model Robustness Against Reverse Engineering
We evaluate the strength of your ML models against reverse-engineering attempts, ensuring that attackers cannot easily reproduce or steal your intellectual property.
Why Choose Our AI Security Testing
SPECIALIZED EXPERTISE
Our team combines deep cybersecurity knowledge with AI development experience, bringing a unique perspective to identifying vulnerabilities in complex AI systems.
TAILORED SECURITY SOLUTIONS
We understand that every AI model is different, and so is every business. Our penetration testing services are customized to address the specific risks associated with your application and the type of data you handle.
METHODOLOGY-DRIVEN APPROACH
We employ a structured, comprehensive methodology specifically developed for AI systems testing, ensuring no vulnerability goes undetected.
END-TO-END PROTECTION
Our services go beyond penetration testing. We provide actionable insights, remediation recommendations, and best practices to help you secure your AI infrastructure throughout its lifecycle—from design and development to deployment and maintenance.
Our Process
THE STORY AND TEAM
BEHIND ORENDA SECURITY ®
Orenda Security ® is an elite information security firm founded on a spirit of integrity and partnership with our staff, and most importantly, our clients.