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Real-time visibility, safety, and security for your GenAI-powered agents and applications
Proactively test GenAI models, agents, and applications before attackers or users do
Deploy generative AI applications and agents in a safe, secure, and scalable way with guardrails.
Proactively identify vulnerabilities through red teaming to produce safe, secure, and reliable models.
A federal judge has ruled that AI-generated content is not protected under free speech laws, expanding legal exposure across the AI ecosystem. What does it mean for AI platforms, infrastructure providers, and the future of GenAI safety?
The Take It Down Act explained: all you need to know about this new federal law targeting AI-generated intimate content, to stay compliant and prepared.
ActiveFence is expanding its partnership with NVIDIA to bring real-time safety to a new generation of AI agents built with NVIDIA’s Enterprise AI Factory and NIM. Together, we now secure not just prompts and outputs, but full agentic workflows across enterprise environments.
Discover how ISIS’s media arm is analyzing and adapting advanced AI tools for propaganda, recruitment, and cyber tactics in a newly released guide detailing AI’s dual-use potential.
Explore why generative AI continues to reflect harmful stereotypes, the real-world risks of biased systems, and how teams can mitigate them with practical tools and strategies.
Innovation without safety can backfire. This blog breaks down how to build GenAI systems that are not only powerful, but also secure, nuanced, and truly responsible. Learn how to move from principles to practice with red-teaming, adaptive guardrails, and real-world safeguards.
Discover how threat actors abuse fake emergency data requests to access sensitive user information, and what platforms can do to stop them.
Learn how online cartels recruit hitmen, traffic women, and exploit UGC platforms – and how proactive detection can stop them in their digital tracks.
See why AI safety teams must apply rigorous testing and training with diverse organic and synthetic datasets.