AI Risk Management: EC-Council Whitepaper on Threats

Organizations are increasingly integrating artificial intelligence, but this introduces new risks beyond traditional cybersecurity. AI models operate probabilistically and rely on complex data, creating unique attack paths like prompt injection and data poisoning. What's interesting is that AI security needs to be an enterprise governance, risk, and assurance discipline. A whitepaper explores how to identify, assess, and manage AI-specific threats throughout its lifecycle. This includes a governance-centric framework integrating enterprise risk management principles with industry guidance. The paper also looks at AI risk taxonomy, threat modeling, and adversarial testing. There's a focus on using threat intelligence to evaluate model behavior and assess resilience. The growing importance of AI supply chain security is also examined, highlighting risks with third-party models and data. Emerging practices like AI Software Bills of Materials are discussed for improved transparency. The bottom line: AI incidents can have significant consequences, so the paper addresses AI-specific incident response and crisis management. This information helps organizations understand and mitigate the evolving risks of AI adoption.