Thales expands AI ecosystem protection with application and RAG security tools

AI is one of the fastest-growing technologies in the history of modern business, with the ability to revolutionize industries, optimize operations, and drive innovation, but it is also introducing security gaps, risks, and vulnerabilities.

According to McKinsey, 78% of organizations are using AI in at least one business function, up from 55% two years ago. As a result, 73% of them are investing in AI-specific security tools, either with new or existing budgets, according to the 2025 Thales Data Threat Report.

Thales is introducing the first foundational capabilities of its AI Security Fabric to protect the core and edge of enterprises’ AI ecosystems.

Safeguarding LLM-powered apps, data, and identities

With Thales AI Security Fabric, organizations will be able to:

• Unlock AI-driven growth securely: Maximize AI’s business value by enabling innovation and expansion while mitigating risks such as prompt injection, data leakage, model manipulation, and exposure of sensitive or regulated data.
• Protect data, applications, and identities end-to-end: Provide Agentic AI and GenAI with controlled dataset access, deploy runtime security across cloud and on-premises environments, and safeguard all AI interactions with minimal integration effort.
• Rely on enterprise-grade, standards-aligned protection: Leverage proven security capabilities that directly address the most critical OWASP Top 10 risks and prevent costly or reputation-damaging incidents before they impact the organization.

The first capabilities available now are:

• AI application security: a security solution designed to protect homegrown applications that use LLMs. Providing real-time protection for AI-specific threats, including prompt injection, jailbreaking, system prompt leakage, model denial-of-service attacks, sensitive information leakage, and content moderation. With flexible and seamless deployment options to fit any architecture, whether cloud-native, on-premises, or hybrid environments.
• AI retrieval-augmented generation (RAG) security: provides the capability to discover and secure sensitive structured and unstructured enterprise data before it is ingested into retrieval-augmented applications with comprehensive data protection solutions, including encryption and key management. Helps secure communication between the LLM and external sources of data.

“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, SVP of Thales’ Cyber Security Products Business.

“Thales AI Security Fabric offers enterprises specialized tools to secure AI applications while minimizing operational complexity. Supported by decades of security expertise, Thales enables businesses to confidently scale their AI adoption, safeguarding sensitive data, applications, and user interactions,” Canoadded.

Thales plans to expand its AI Security Fabric in 2026 with new runtime security capabilities, including data leakage prevention, a Model Context Protocol (MCP) security gateway, and end-to-end runtime access control. These features will strengthen protection across data flows, secure agentic AI data access, and ensure unified, compliant management of interactions between users, models, and data sources.