AI is quickly becoming part of everyday business applications. Companies are using LLMs for customer support, internal assistants, document search, automation and decision-making. But once these systems are connected to company data, APIs and internal applications, they also create security risks that traditional penetration testing may not fully cover.
Nathan Labs Advisory provides AI Security Testing to help businesses understand how their AI applications could be attacked, manipulated or misused.
Our testing looks at the complete AI application, not just the underlying model.
We test whether specially crafted inputs can override system instructions, bypass restrictions, reveal hidden prompts or make the application behave in ways it was not designed to.
Our consultants simulate realistic attacks against LLM-powered applications to identify weaknesses such as jailbreaks, information disclosure, insecure access controls and unintended model behaviour.
For applications using Retrieval-Augmented Generation (RAG), we assess how information is retrieved from internal documents, databases, vector stores and knowledge bases. Testing includes unauthorized information retrieval, access-control weaknesses, retrieval manipulation and data poisoning scenarios.
We check whether the AI can expose confidential information, customer data, internal documents, credentials, system prompts or other information that users should not be able to access.
AI agents can interact with APIs, databases, applications and external tools. We test whether those capabilities can be abused to perform unauthorized actions or access information outside the user's intended permissions.
We assess the APIs supporting the AI application, including authentication, authorization, input handling, rate limiting and other API security weaknesses.
The risk with an AI application is not limited to getting an incorrect answer. A successful attack could allow someone to manipulate the application’s instructions, retrieve sensitive business information, bypass access restrictions or misuse systems connected to the AI.
These issues are often difficult to identify through automated vulnerability scanning alone because the outcome depends on how the model, application, data and integrations work together.
AI Security Testing provides a practical way to understand these risks before an application is widely deployed.
Nathan Labs Advisory combines AI security testing, penetration testing, API security and application security to assess the complete AI environment.
Our consultants approach the application from an attacker’s perspective and test realistic misuse scenarios rather than relying only on automated scanning. We identify vulnerabilities, demonstrate their potential impact and provide practical recommendations for remediation.
Our testing can support organisations developing or deploying:
Whether the AI solution is still under development or already in production, Nathan Labs
Advisory can help identify where it is exposed and what needs to be strengthened.
AI Security Testing | LLM Penetration Testing | Prompt Injection Testing | RAG Security Assessment | AI Red Teaming | Generative AI Security | AI Application Security | AI API Security Testing
We’re not here to drown you in technical jargon or hand you a report that nobody uses.
We help businesses find and fix security gaps through expert VAPT services
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We help businesses find and fix security gaps through expert VAPT services
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Copyright © 2026 All Rights Reserved.
Powerd by Edatic.in
We help businesses find and fix security gaps through expert VAPT services
Copyright © 2026 All Rights Reserved.
Powerd by Edatic.in
