Santa Clara, Calif. Oct 2, 2025 – Recently, NSFOCUS held the AI New Product Launch in Beijing, comprehensively showcasing the company’s latest technological achievements and practical experience in AI security. With large language model security protection as the core topic, the launch systematically introduced NSFOCUS’s concept and practices in strategy planning, scenario-based protection, technical products, and professional services in the field of AI.

AI-Native Security + Intelligent Operations

Currently, the risks faced by AI applications are constantly evolving and changing. From API interfaces to intelligent agents, AI security risks have shown a significant upward trend in the coverage scope and impact depth. As the autonomy of AI continues to strengthen, the “attack surface” of risks is also expanding, bringing unprecedented challenges to security protection. In response to this situation, NSFOCUS believes that AI security governance must fully draw on and absorb authoritative industry security frameworks and best practices, and systematically invest in LLM security products and services to ensure the effectiveness and comprehensiveness of security protection measures.

Adhering to the concept of “AI-Native Security + Intelligent Operations”, and guided by policies and regulations, national standards, and industry requirements, NSFOCUS first conducts subject identification to clarify the objects and scope of security protection. By means of compliance assessment, security testing, AI Red-teaming, and other methods, it conducts comprehensive security risk assessments and accurately identifies specific scenario-based security risks that require priority handling. On this basis, it orderly builds an in-depth defense capability system covering computing power infrastructure, training corpora, the models themselves, intelligent applications, as well as third-party components and supply chains. This system carries out daily security operation work for the LLM supervision system from multiple dimensions such as “infrastructure management”, “security compliance assessment”, and “security risk disposal”, ensuring that LLMs receive effective security protection in all aspects.

In-Depth Security Defense for Two Key Scenarios of LLMs

The first scenario is independently-deployed LLMs. For this scenario, organizations sort out security risks in phases (training, deployment, and application) based on the lifecycle of LLMs, assign security responsibilities by role, which also facilitates the sequential security framework design.

The second scenario is externally-connected commercial models. For this scenario, it is necessary to distinguish between two calling modes: API external connection and WEB external connection, and quickly deploy security policies, which is more in line with the risk management principles and practical needs of enterprise organizations.

At the same time, in view of the principle that generative AI must first meet compliance requirements, and then realize requirements in phases of content security barriers, prompt engineering, model fine-tuning, model training, and data security. This phased implementation approach not only takes into account the development maturity of LLM technology and related security technologies but also balances engineering costs and implementation difficulties, conforming to the objective reality of enterprise organizations in terms of security budgets and execution.

“Assessment-Protection-Response” Security Closed Loop

Facing the new security challenges brought by LLM applications, NSFOCUS has built a full-lifecycle defense system of “Assessment-Protection-Response”.

• AI-Scan: Think of it as your LLM’s “security health checker.” Leveraging a built-in library of 100,000+ test cases, it simulates 21 attack types to detect vulnerabilities in content compliance, adversarial defense, and supply chain security. It deeply scans 15 model file formats (e.g., .pb, h5) for backdoors, tests 450+ model components (like Ollama, Ray) for flaws, and supports custom enterprise risk library imports. Generate a visual risk report in under 30 minutes to eliminate risks at the training/fine-tuning stage.
• AI-UTM (AI Unified Threat Management): Your LLM’s “security guardian” during deployment and application. It builds a 3-tier content filtering system (300,000+ sensitive word lexical detection, NSFOCUS’s self-developed NSFGPT for semantic analysis, 128K token context window) for millisecond-level response to block illegal content. It also prevents token exhaustion via intelligent computing resource allocation and stops Web attacks while ensuring over 99% accuracy in sensitive info detection.

NSFOCUS AI Red-teaming: Escorting the Path of AI Compliance

As a new type of exposure surface, LLMs have introduced many unprecedented attack methods, such as prompt injection, LLM jailbreaking, and code sandbox execution escape, making them as key breakthrough targets for attackers.

NSFOCUS conducts comprehensive assessments of mainstream risks from multiple perspectives. By simulating bypassing protection mechanisms, inducing models to generate risky content in a controlled environment, breaking through infrastructure isolation boundaries, and even attempting to take over production clusters, it systematically identifies potential security vulnerabilities of LLMs in practical applications.

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*** This is a Security Bloggers Network syndicated blog from NSFOCUS, Inc., a global network and cyber security leader, protects enterprises and carriers from advanced cyber attacks. authored by NSFOCUS. Read the original post at: https://nsfocusglobal.com/building-a-full-lifecycle-defense-system-for-large-language-model-security/