Navigating the Pitfalls of Generative AI

Generative AI has become one of the key technological innovations of the past few years, capturing the interest of both the technical and non-technical audiences alike. However, the unpredictable nature of these systems raises concerns, necessitating careful monitoring within corporate environments to safeguard data privacy.

Incident Example:

A notable instance highlighting this unpredictability is the breach in Nvidia’s NEMO framework. Despite the built-in safeguards of Generative AI tools, researchers managed to exploit vulnerabilities, emphasising the need for robust monitoring. In this case, simple instructions such as swapping the letter ‘I’ with ‘J’ altered the information and led to the tool releasing personally identifiable information (PII) from an internal database.

Importance of Policies:

These incidents highlight the urgency of implementing comprehensive policies on Generative AI usage. Such policies act as a guiding framework for employees (both technical and non-technical) in leveraging such technologies responsibly. This guidance will begin to mitigate risks associated with biases, misuse, and data leakage. This proactive approach aims to secure corporate data while aligning with ethical and legal objectives. Cyberseer and Darktrace complement these policies by monitoring the use of these services to ensure adherence.

Successful Deployment Case Study:

Cyberseer has successfully deployed monitoring measures within the environment of a leading UK transport and logistics provider, involving the following:

• Providing daily reporting on users connecting to generative AI services,
• The development of bespoke models assessing data transfer volumes to AI services – aiming to identify any uploads of large amounts of data,
• Models detecting potential beaconing to these services.

This thorough monitoring allows the company to engage with users, ensuring adherence to their Generative AI policies and investigating when necessary. This coincides with the monitoring of data transferred, all in all coming together to mitigate the risks of corporate data exposure, as evidenced by the NEMO incident. 

Utilising Reporting Insights:

This reporting can provide insights into internal departments’ reliance on Generative AI. This information helps assess the need for handling private data via these services, enabling the replacement of tools when deemed necessary with other internal solutions.

Conclusion:

In conclusion, Generative AI has revolutionised technology, attracting widespread interest. Despite its advancements, the unpredictable nature of these systems necessitates careful monitoring to protect data privacy. The breach in Nvidia’s NEMO framework highlights vulnerabilities, stressing the importance of robust monitoring.

Comprehensive policies are crucial in guiding all employees, ensuring responsible Generative AI usage. Cyberseer’s monitoring solutions, exemplified in the case study above, play a pivotal role in mitigating the risk of corporate data exposure. Insights gained from monitoring inform strategic decisions, allowing for the replacement of tools when deemed necessary.

In navigating Generative AI pitfalls, the key lies in a blend of comprehensive policies and proactive monitoring solutions. This approach positions organisations to responsibly harness the potential of Generative AI in an ever-evolving landscape.

For further assistance and discussions on how Cyberseer’s SOC service can enhance your Generative AI security, feel free to get in touch with us.