Unleashing havoc on AI creativity: mapping risks to business outcomes

In recent months, there has been an increased focus on securing AI models, with generative AI being a particularly important area to address. However, many organizations are not yet developing consistent, enterprise-wide approaches to generative AI, despite concerns about potential cybersecurity attacks. To better understand the risks associated with generative AI, IBM X-Force Red has been testing models to determine the types of attacks that are most likely to occur. This article outlines some of these attacks, including prompt injection, data poisoning, model evasion, model extraction, inversion, and supply chain attacks. Each attack poses unique risks to businesses, such as reputational damage, service degradation, intellectual property theft, and compromised business processes. To address these risks, organizations need to establish effective defense strategies and prioritize the security of their AI initiatives. IBM has introduced the IBM Framework for Securing AI to guide organizations in securing their generative AI models and enhancing their cyber preparedness.