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Protect your AI applications and agents from attacks, fakes, unauthorized access, and malicious data inputs.
Control your GenAI applications and agents and assure their alignment with their business purpose.
Proactively test GenAI models, agents, and applications before attackers or users do
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Ensure your app is compliant with changing regulations around the world across industries.
Proactively identify vulnerabilities through red teaming to produce safe, secure, and reliable models.
Detect and prevent malicious prompts, misuse, and data leaks to ensure your conversational AI remains safe, compliant, and trustworthy.
Protect critical AI-powered applications from adversarial attacks, unauthorized access, and model exploitation across environments.
Provide enterprise-wide AI security and governance, enabling teams to innovate safely while meeting internal risk standards.
Safeguard user-facing AI products by blocking harmful content, preserving brand reputation, and maintaining policy compliance.
Secure autonomous agents against malicious instructions, data exfiltration, and regulatory violations across industries.
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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 NVIDIAโs 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 AIโs 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.