Thales has launched its AI Security Fabric, introducing what it describes as the first runtime security capabilities specifically designed to protect Agentic AI and LLM-powered applications. The new offering addresses the unique security gaps emerging from rapid AI adoption, helping organizations mitigate threats like prompt injection, data leakage, and model manipulation while maintaining compliance as they scale AI initiatives.
Thales launches AI Security Fabric for runtime security of AI applications.
It addresses AI-specific threats like prompt injection, data leakage, and model manipulation.
Initial capabilities secure homegrown LLM apps and RAG (Retrieval-Augmented Generation) pipelines.
The solution aims to protect data, applications, and identities across cloud and on-premises environments.
Planned 2026 enhancements include data leakage prevention and an MCP security gateway.
It enables enterprises to scale AI adoption securely by mitigating critical OWASP Top 10 risks.
With a vast majority of organizations now using AI in business functions, investment in AI-specific security tools has become a priority. Thales' AI Security Fabric responds to this need by providing specialized protection for the core and edge of enterprise AI ecosystems. The solution is engineered to allow businesses to unlock AI-driven growth and innovation while controlling the associated risks, such as exposure of sensitive data or manipulation of AI models.
"As AI reshapes business operations, organizations require security solutions tailored to the specific risks posed by Agentic AI and Gen AI applications," said Sebastien Cano, Senior Vice President of Thales’ Cyber Security Products Business. "Thales AI Security Fabric offers enterprises specialized tools to secure AI applications while minimizing operational complexity."
The first available capabilities focus on two critical areas: AI Application Security and AI RAG Security. The Application Security component provides real-time protection for homegrown LLM applications against threats like jailbreaking, system prompt leakage, and denial-of-service attacks. The RAG Security capability is designed to discover and secure sensitive enterprise data before it is ingested into retrieval-augmented generation pipelines, using encryption and key management to protect data flows between LLMs and external sources.
These tools offer flexible deployment across cloud-native, on-premises, or hybrid architectures, aligning with Thales' promise of enterprise-grade, standards-aligned protection that addresses critical OWASP Top 10 risks for AI.
Thales has outlined plans to expand the AI Security Fabric in 2026 with additional runtime security features. These planned enhancements include data leakage prevention, a Model Context Protocol (MCP) security gateway for securing agentic AI data access, and end-to-end runtime access control. The overarching goal is to build a comprehensive security layer that safeguards all interactions between users, AI models, and data sources, enabling unified and compliant management as AI adoption scales.
This launch positions Thales to be a key player in the emerging market for AI-native security, leveraging its deep expertise in critical environments to help enterprises deploy AI with greater confidence.
About Thales
Thales (Euronext Paris: HO) is a global leader in advanced technologies for the Defence, Aerospace, and Cyber & Digital sectors. Its portfolio of innovative products and services addresses several major challenges: sovereignty, security, sustainability, and inclusion.
The Group invests more than €4 billion per year in Research & Development in key areas, particularly for critical environments, such as Artificial Intelligence, cybersecurity, quantum, and cloud technologies.
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