October 16, 2023 at 07:59PM
GenAI will revolutionize business, driving productivity gains across all sectors. Enterprises are racing to build AI-powered apps, but security teams must act now to ensure their robustness. The rapid development of these apps using various frameworks poses security challenges. Advanced security organizations are creating centers to inventory, assess, and secure these apps. Overcoming these challenges requires adapting processes and acquiring technical skills. Nonetheless, addressing these issues is crucial to capturing the benefits of AI.
From the meeting notes, it is clear that GenAI is expected to have a significant impact on business operations, with research firms estimating substantial productivity gains in all sectors. This potential has led many enterprises to prioritize the development of AI-powered applications. However, security teams must take action now to ensure the resilience and security of these applications.
Several organizations have already built numerous AI-powered apps, with Microsoft’s Copilot applications being a notable example of rapid development. Due to the immaturity of the frameworks and tools used in AI app development, these applications are being built using a wide range of technologies. It is not uncommon to find multiple frameworks being used within a single enterprise.
The first organizations that successfully leverage AI for productivity gains will have a significant advantage. As such, it is important to work with the available frameworks and tools, as waiting for standardization would mean falling behind competitors.
The rapid development of new applications within a short timeframe has significant security implications. These applications face similar security risks as any other application and require appropriate identity management, dataflow controls, and secret management. Additionally, GenAI introduces unique security challenges, which frameworks like the OWASP LLM Top 10 help to address.
To address these security challenges, advanced security organizations are collaborating with IT to establish dedicated centers. These centers will inventory, assess, and secure AI applications, providing threat modeling and design review services to ensure secure standards are met. However, creating these centralized resources is not without challenges. Identifying all AI-powered projects across the enterprise and developing the necessary technical skills to audit them pose significant difficulties. Furthermore, monitoring these applications in production requires obtaining the right data from the evolving development frameworks and analyzing it for potential security issues.
Nevertheless, these challenges can be overcome by following the typical application security problem-solving approach of inventorying applications, conducting security assessments, and implementing runtime protection measures. Taking action in these areas will enable the business to seize the opportunities presented by the AI revolution.
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