Recommendations for Securing Multimodal ModelsThe report urges AI developers and enterprises to act swiftly to mitigate these emerging risks, outlining key best practices: Integrate red teaming datasets into safety alignment processesConduct continuous automated stress testingDeploy context-aware multimodal guardrailsEstablish real-time monitoring and incident responseCreate model risk cards to transparently communicate vulnerabilities "These are not theoretical risks,” added Sahil Agarwal.
Boston, May 08, 2025 (GLOBE NEWSWIRE) -- As generative AI rapidly evolves to process both text and images, a new Multimodal Safety Report released today by Enkrypt AI, a leading provider of AI safety and compliance solutions for agent and multimodal AI, reveals critical risks that threaten the integrity and safety of multimodal systems.
"This research is a wake-up call: the ability to embed harmful textual instructions within seemingly innocuous images has real implications for enterprise liability, public safety, and child protection.” The report reveals two Mistral models are 60X more prone to generate CSEM content and 40X more prone to generate CBRN content than gpt-4.0 and claude-3.7-sonnet.
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