Thales has launched new AI Security Fabric, which is a significant move in AI runtime security for enterprise systems. The solution is capable of defending agentic AI, LLM-powered applications, corporate data, & identities against the maverick threats of the future. Besides, the platform addresses the most important issues of AI, as prompt injection, data leakage, model tampering, & unsafe RAG pipelines. These features give the organisation the freedom to safely go forward with its innovation process and at the requirements.
“As AI reshapes business operations, organizations require security solutions tailored to. The specific risks posed by Agentic AI and Gen AI applications,” Sebastien Cano, Senior Vice President of Thales’ Cyber Security Products Business, said. “Thales AI Security Fabric offers enterprises specialized tools to secure AI applications while minimizing operational complexity. Backed by decades of security expertise, Thales helps businesses confidently scale AI adoption while protecting sensitive data, applications, & user interactions.“
Thales Launches AI Security Fabric to Safeguard Enterprise AI Systems
Using the Thales AI Security Fabric, companies will be able to implement AI solutions while maintaining security standards. The tool is capable of providing protection that is comprehensive protection for the three most vital areas of AI. Namely, data, identities, and applications regardless of the fact that the deployment is in the cloud, on-premises, or hybrid. This solution also delivers enterprise-level security, adhering to the highest industry standards to ensure protection and compliance for large organizations. Organizations must utilize existing security measures to prevent costly breaches and safeguard their reputation while ensuring compliance and data protection.
The first bundle of features comprises AI Application Security that protects real-time in-house LLM-powered apps from cyber-attacks. It includes defence against prompt injection, system leakage, denial-of-service attacks, and sensitive data exposure. Similarly, AI Retrieval-Augmented Generation (RAG) Security identifies and protects sensitive structured & unstructured data before it is integrated into AI systems. The need for security designed specifically for agentic AI and generative models is what organisations realise the most. Thales has plans to broaden this platform with more runtime security tools in 2026. Some of these tools include data leakage prevention, Model Context Protocol gateways, and stricter access controls across AI data flows.
To explore how Security Operations Centers (SOC) play a crucial role in defending against modern cyber threats, read our latest SOC News.
Source: Businesswire
