LLM/GenAI Penetration Testing

Elevate Your Security with DSecured's Expert LLM/GenAI Penetration Testing: Renowned Ethical Hackers Deliver Clear, Actionable Reports Free of False Positives.

Our seasoned ethical hackers employ advanced techniques, including live hacking events, to uncover vulnerabilities in your LLM/GenAI systems. Each comprehensive report not only highlights critical weaknesses but also provides actionable steps for your IT team to swiftly mitigate risks. Trust DSecured for unparalleled precision and unmatched quality in offensive security services.

Penetration testing

What is an LLM penetration test?

Penetration tests against systems from the area of "GenAI" (Generative Artificial Intelligence) are becoming increasingly important, as these systems - primarily LLM (Large Language Models) - are increasingly being integrated into applications. In an LLM pentest, the focus is primarily on protecting the model, its data, manipulability and the security of the agent. A good starting point for an LLM test is the LLM-OWASP Top 10.

In general, the LLM penetration test always takes the form of a black box approach. We are the user who interacts with the LLM. This is usually a chat or voice application. From here we try to manipulate the system, extract data and compromise the integrity of the model.

Should an LLM pentest be combined with a web pentest?

It clearly depends on the focus. Both are closely related, as classic security gaps such as SQL injections or command injections can negatively affect both data and the model in many different ways. Here you should sit down together and decide together what makes sense. Arrange a free consultation with the CEO.

Damian Strobel

"We are facing some challenges in the area of LLM and GenAI!"

Damian Strobel - Founder of DSecured

We are happy to check whether an attacker can steal or manipulate your LLM model.

Costs of an LLM penetration test?

As is always the case in the area of IT security: It depends. Simple systems can be tested with a small four-digit budget. However, as complexity increases, the cost factor often increases. When it comes to systems that are highly complex, perhaps even with various agents, various different models that interact with one another, the price can quickly reach five figures.

The easiest thing you can do is send us a request. The more you can tell us about your system, the better we can give you a better number or make you an offer.

What is special about the LLM area is that it is sometimes necessary to train your own models in order to test certain things. One example of this is TextFooler, which can be used to generate manipulative inputs that can be used to test the LLM. This is particularly effective if you use your own models to generate this content - but these often have to go through what is known as fine tuning.

LLM Pentest

We are happy to check the security and integrity of your LLM model.

What vulnerabilities can LLM systems have?

Red Teaming

The "OWASP Top 10 for Large Language Model Applications" are the best source in the area of LLM pentesting to understand the dangers lurking in this type of application. The most common problems with LLM applications are prompt injections and adversarial inputs. Manipulating the model using your own training data is also problematic, as this can lead to legal problems. However, a lot depends on the context of the application.

Red Teaming

The issue of data leaks is also a major problem. Here, the attacker tries to manipulate the model in such a way that it reveals private data that it may have seen during training. Many vulnerabilities of this kind can be discovered partially automatically using complex applications such as garak. DoS attacks are also common, where the attacker tries to use the model in such a way that the underlying infrastructure is overloaded and/or enormous costs are generated.

Red Teaming

Another important topic is agent control. Very simple LLM applications are often just chatbots. However, if an AI application becomes complex and multi-level, you often see that the AI internally generates commands for an agent, which the agent then executes. Here, the attacker's goal is to execute his own code and ultimately even take over the agent and steal the entire model. It is also possible that outputs are forwarded to other systems or components and can cause problems there.

Some companies we have been able to help

Goldman Sachs
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