Misinformation from LLMs poses a core vulnerability for applications relying on these models. Misinformation occurs when LLMs produce false or misleading information that appears credible. This vulnerability can lead to security breaches, reputational damage, and legal liability. One of the major causes of misinformation is hallucination—when the LLM generates content that seems accurate but is […]| OWASP Gen AI Security Project
Simply look out for libraries imagined by ML and make them real, with actual malicious code. No wait, don't do that| www.theregister.com