Generative AI: Exploring the Risks and Risk Mitigation Best Practices

Oh boy, here we go. Those fancy words known as Generative AI.

Generative AI (GenAI) technologies are revolutionizing every aspect of modern business operations. While your organization may have defenses in place to fight against today’s threats, many are unprepared for GenAI-based threats.?

However, inappropriate or unauthorized usage can lead to the amplification of existing?

cyber risks as well.?

For example, employees using GenAI applications can unknowingly share confidential? data with the application itself, leading to potential sensitive data and intellectual property (IP) leaks.???

Unfortunately, many organizations don’t have monitoring to put appropriate governance, risk and compliance? policies in place around GenAI utilization.?

This lack of visibility can also lead to creating ill-informed policies? and making governance decisions on GenAI usage based more around assumptions rather than data.?

To address these challenges, you must understand how your employees are using GenAI and have complete? visibility over their user interactions.

Generative AI Risks

When it comes to using Generative AI (GenAI), there are several security risks that organizations should be aware of:

Data-Related Risks: The primary risk stems from the data users send to GenAI applications. This includes:

Data Loss: Users might inadvertently lose sensitive information.

Unintentional Sharing: Confidential data could be shared unintentionally.

Inappropriate Use: Legal rights associated with information from GenAI services may be violated1.

Malware and Cyber Threats: Through generative AI, attackers can create new and complex types of:

Malware: Malicious software that can evade conventional protection measures.

Phishing Schemes: Deceptive attempts to steal sensitive information.

Other cyber dangers that may lead to data breaches, financial losses, and reputational risks.

Content Misuse and Misapplication: Organizations need to detect, identify, and prevent the spread of potentially misleading content generated by GenAI. This includes accidental misapplication and deliberate malpractices3.

Authentication Bypass: GenAI-created audio could potentially bypass voice-based authentication systems, reducing their effectiveness4.

To mitigate these risks, organizations should develop robust capabilities for monitoring, governance, and responsible usage of GenAI applications.?

Responsible usage of Generative AI (GenAI) is crucial to ensure ethical and secure deployment.?

Risk Mitigation Best Practices

Remember that responsible GenAI usage benefits both organizations and society by fostering trust, innovation, and positive impact.

Visibility into GenAI Usage: Managed Detection and Response for example,? provides comprehensive visibility into your organization’s Generative AI (GenAI) usage, including applications, user prompts, and shared files, helping to identify potential risks and unauthorized use1.

Risk Monitoring: The solution helps monitor GenAI application user activity to observe usage surges and identify risky interactions, ensuring data security and compliance.

Threat Intelligence: Stay updated with the latest GenAI-focused threat intelligence to develop policies that promote responsible AI usage and address emerging security concerns.

Policy Development: Support the creation of informed governance policies by providing metric-driven insights into workforce GenAI usage, reducing blind spots and enhancing overall security.

Conclusion

To mitigate risks, organizations should develop robust capabilities for monitoring, governance, and responsible usage of GenAI applications.?

Responsible usage of Generative AI (GenAI) is crucial to ensure ethical and secure deployment.?

Stay tuned for future updates and a webinar series exploring Generative AI and best practices for mitigating risks.

For more information contact me at [email protected]