AI Security
Enhance the resilience of AI in your environment. Whether you are fine-tuning off-the-shelf models, building your own, or integrating LLM capabilities into your applications, our security experts assess and strengthen your AI security posture.
Schedule an AI Security AssessmentAI and Large Language Models introduce new attack surfaces that traditional security testing does not cover. Prompt injection, jailbreaking, data leakage, adversarial manipulation, and model extraction are real threats that require specialist testing expertise.
Our AI/ML penetration testing goes beyond automated scanning to uncover vulnerabilities specific to how your models process input, generate output, and interact with your application stack. We test for real-world attack scenarios that could expose sensitive data, generate unauthorised content, or allow actions on behalf of other users.
Our Services
Security testing for applications that integrate LLM capabilities. We identify vulnerabilities specific to LLM functionality that are not found by traditional static and dynamic web application testing. Testing covers any LLM (GPT, Llama, Mistral, Claude, Titan) in any framework (Azure OpenAI, AWS Bedrock, GCP Vertex AI, and others).
Detailed benchmarking and analysis of potential jailbreak consequences of your LLM. We identify real-world attack scenarios that adversaries deploy to extract sensitive data, generate unauthorised content, and bypass safety guardrails. Covers data leakage, adversarial attacks, content moderation bypass, bias detection, and data drift.
Advanced evaluation for applications with custom models beyond standard third-party LLM integrations. We review training data collection, cleaning, and selection processes. Our experts conduct interviews and review pipeline configurations to produce threat models highlighting core weaknesses and recommending mitigating controls.
Systematic testing for direct and indirect prompt injection vulnerabilities. We attempt to manipulate your LLM into ignoring system prompts, accessing restricted data, executing unintended actions, and bypassing input/output filtering mechanisms.
Testing whether your AI systems can be manipulated into revealing training data, system prompts, internal configurations, PII, or other sensitive information through carefully crafted queries and adversarial techniques.
Review of your AI implementation architecture including access controls, rate limiting, input validation, output filtering, monitoring, and the integration points between your LLM and backend systems. Recommendations aligned to OWASP Top 10 for LLM Applications.
Direct and indirect injection attacks that manipulate model behaviour, bypass safety controls, or execute unintended actions through crafted inputs.
Attempts to extract training data, system prompts, API keys, PII, or other sensitive information embedded in or accessible through the model.
Techniques to bypass content filters, safety guardrails, and usage policies to generate restricted or harmful outputs.
Testing whether AI agents or tool-using LLMs can be manipulated into performing actions beyond their intended scope or permission level.
Assessment of third-party model dependencies, plugin ecosystems, and integration points that could introduce vulnerabilities.
Testing for resource exhaustion attacks, infinite loops, and crafted inputs that could degrade model performance or availability.
AI introduces new risks that traditional pentesting doesn't cover. Let our specialists assess your LLM implementation and identify vulnerabilities before they are exploited.
Get an AI Security Assessment