NEW YORK, Jan. 26, 2026 /PRNewswire/ — NeuralTrust is introducing the Generative Application Firewall (GAF) through the publication of a new foundational paper, developed in collaboration with and endorsed by researchers and experts from leading academic institutions and AI governance organizations.
As generative AI moves rapidly from experimentation to production, organizations are embedding large language models into customer-facing systems, internal tools, and autonomous workflows. These systems no longer behave like traditional software. They interpret language, accumulate context, call tools, and make decisions over time. Yet the security models protecting them remain largely unchanged.
Traditional network firewalls and Web Application Firewalls were designed for structured, deterministic traffic. They inspect packets, endpoints, and request formats. Generative AI systems operate at a different layer entirely. Their most critical vulnerabilities do not appear in syntax or protocols, but in meaning, intent, and conversational flow. This mismatch has created a new and poorly understood attack surface.
The Generative Application Firewall is introduced to address this challenge. It defines a unifying architectural layer that sits between users and generative AI systems, enforcing security, governance, and policy across all AI interactions. Much like the Web Application Firewall became essential for securing web applications, GAF establishes a reference model for securing generative ones.
The work reflects collaboration and endorsement from researchers and experts across academia, industry, and AI governance, including the University of Cambridge, MIT CSAIL, the University of Liverpool, the University of the Aegean, OWASP’s GenAI Security Project, the Cloud Security Alliance, the Center for AI and Digital Policy, and Huawei.
What is the Generative Application Firewall?
The Generative Application Firewall is a centralized enforcement layer for applications powered by large language models. It is designed to protect systems that expose natural language interfaces, including chatbots, copilots, and autonomous agents.
Rather than relying on isolated prompt filters or application-specific guardrails, GAF maintains a holistic view of AI behavior across users, sessions, tools, and time. This enables detection and response to threats that only emerge through semantics, context accumulation, and interaction patterns.
The paper defines five complementary protection layers that together form the GAF model:
- Network and access layers, to control abuse, rate limits, identities, and permissions
- Syntactic controls, to validate formats and prevent encoded or structural attacks
- Semantic analysis, to detect meaning-based attacks such as jailbreaks and prompt manipulation
- Context-aware enforcement, to identify multi-turn, behavioral, and escalation-based attacks
These layers enable real-time actions such as blocking, redacting, redirecting, alerting, or terminating responses, while preserving performance, usability, and auditability.
A foundation for trustworthy AI
As generative AI becomes embedded in critical workflows, security and governance can no longer be treated as add-ons. They must be designed into the infrastructure that powers AI systems themselves.
The Generative Application Firewall represents a step toward that foundation.
The full paper, Introducing the Generative Application Firewall (GAF), is now publicly available on arXiv.
About NeuralTrust
NeuralTrust is the leading platform for securing and scaling AI agents and LLM applications. Recognized by Gartner and the European Commission as a champion in AI security, NeuralTrust helps enterprises protect critical AI systems through runtime protection, threat detection, and compliance automation.
Our mission is to make AI adoption measurable, secure, and reliable turning AI Agent Security into a strategic advantage.
Learn more at neuraltrust.ai
SOURCE NeuralTrust
