
Radware Launches âLLMâŊFirewallâ to Secure Enterprise GenerativeâŊAI Use
âĒBy ADMIN
Related Stocks:RDWR
On NovemberâŊ18,âŊ2025, Radware Ltd. (NASDAQ:âŊRDWR), a global leader in cybersecurity and applicationâdelivery solutions, announced the introduction of its new LLMâŊFirewall, a novel addâon for its Cloud Application Protection Services.
The LLMâŊFirewall is designed to act as a protective layer specifically for largeâlanguageâmodel (LLM) integrations within enterprise applications. According to Radware, it intercepts and blocks malicious prompts, jailâbreak attempts, promptâinjection attacks and resourceâabuse risks before they reach the underlying LLM model.
Because the solution is âmodelâagnosticâ and easy to integrate, it works across different platforms and workflows without impeding innovation. Radware positions it as akin to a web application firewall (WAF) but for naturalâlanguage prompt vulnerabilities:
âThink of it as WAF for LLMs âĶ but instead of guarding against HTTPâlevel exploits, it helps mitigate natural language exploits specific to LLM behavior, and enhances protection for LLM models and integration, in real time.â
A key highlight is that the product aims to stop exfiltration of personally identifiable information (PII) before it reaches the LLM, helping enterprises comply with global dataâprotection frameworks such as General Data Protection Regulation (GDPR) and Health Insurance Portability and Accountability Act (HIPAA). Radware also states the product is built to address the â2025âŊOWASP TopâŊ10 Risks and Mitigations for LLMs and GenâŊAI Apps.â
In its corporate background, Radware emphasises that its AIâdriven cloud application, infrastructure and API security solutions support enterprises and carriers worldwide in defending against DDoS attacks, web and application threats, API abuse and badâbots.
The announcement underscores growing enterprise concern around deploying generativeâAI capabilities safely, and Radwareâs move signals a shift in the cybersecurity market toward specialized defenses tuned for LLMâdriven application use.
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