The Escalating AI Security Threat in the Cloud: NSFOCUS Protection Recommendations

As AI applications fully embrace the cloud, emerging components and complex supply chains—while offering convenience—have also led to a sharp rise in risks from configuration flaws and vulnerability exploitation, making the AI security landscape in the cloud increasingly severe. In response to this trend, NSFOCUS conducted analysis of 48 typical...

NSFOCUS AI-Scan Gains Recognition from Authoritative Institution

SANTA CLARA, Calif., Jan 22, 2026 – Recently, International Data Corporation (IDC) released the report "China Large Language Model (LLM) Security Assessment Platform Vendor Technology Evaluation" (Doc#CHC53839325, October 2025). NSFOCUS was selected for this report based on its proven product performance and LLM security assessment methodology. With a comprehensive capability matrix...

Building a Full-Lifecycle Defense System for Large Language Model Security

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,...

Dive into NSFOCUS LLM Security Solution

Overview NSFOCUS LLM security solution consists of two products and services: the LLM security assessment system (AI-SCAN) and the AI unified threat management (AI-UTM), forming a security assessment and protection system covering the entire life cycle of LLM. In the model training and fine-tuning stage, the large language model security...

Prompt Injection: An Analysis of Recent LLM Security Incidents

Overview With the widespread application of LLM technology, data leakage incidents caused by prompt word injections are increasing. Many emerging attack methods, such as inducing AI models to execute malicious instructions through prompt words, and even rendering sensitive information into pictures to evade traditional detection, are posing serious challenges to...

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