AI & Security

At Stobaugh Group, We also specialize in researching and identifying potential security vulnerabilities in artificial intelligence (AI) systems & LLMs. As AI technology continues to evolve and become more integrated into our daily lives, it's crucial to ensure that these systems are secure and can be trusted to perform their intended functions without compromising the privacy or safety of individuals or organizations.

We use unique and ever evolving techniques to analyze and test LLM & AI systems, identify potential weaknesses, and develop solutions to mitigate any security risks. We also work closely with clients to understand their specific security needs and provide customized recommendations and solutions to ensure the integrity and safety of their AI systems.

By partnering with Stobaugh Group for your AI security needs, you can rest assured that you have an expert team dedicated to ensuring the security and privacy of your data and systems.


why security research into a.i. is critical


Continued Research into AI, natural language processing technologies/LLM's is crucial because they are becoming increasingly integrated into our daily lives. These technologies have the potential to revolutionize industries and improve our quality of life, but they also come with new security risks and vulnerabilities.

Hackers and cybercriminals are constantly looking for ways to exploit these vulnerabilities and gain unauthorized access to sensitive information. Without proper security measures and ongoing research, these technologies can be used to spread disinformation, launch cyber attacks, violate privacy among much more.

By conducting security research on these developing technologies, we can identify and mitigate potential vulnerabilities and protect against emerging threats. This helps to ensure that these technologies are used safely and responsibly, and that they continue to benefit society without putting individuals or organizations at risk.


Here are a few xamples of HOW AI systems can be hacked or manipulated:

These examples highlight the importance of researching and addressing security vulnerabilities in AI systems, as well as the need for transparency and timely disclosure of these vulnerabilities to prevent exploitation by malicious actors.