AI Evolution Fuels Cyber Attacks: Chinese Open-Source Models Accused of Being Used as Invasion Tools

Overview

Recently, a cyber intrusion incident targeting Japanese logistics giant Sagawa Express has drawn widespread attention. According to reports, its internal cargo tracking system was accessed without authorization, posing a risk of leakage for large volumes of customers' sensitive personal information, including names, addresses, and contact phone numbers.

Analysts point out that a key driver behind the frequent occurrence of such attacks is the rapid evolution of artificial intelligence technology, especially Chinese-made open-source AI models, which are increasingly being weaponized as auxiliary tools for cybercrime.

Security Vulnerabilities and Data Breaches

Sagawa Express recently issued an announcement confirming that its internal system used for querying delivery status was targeted by malicious attacks. Although the company has not disclosed the specific time of the intrusion, preliminary investigations indicate that the attackers successfully bypassed certain security defenses.

The impact of this incident is no small matter. The leaked data not only includes the full addresses of senders and recipients but also involves key identity information such as personal phone numbers. Once this information falls into illegal trade chains, it can easily lead to secondary harms such as targeted fraud or identity theft.

"This is not an isolated cybersecurity incident, but rather reflects the emerging trend of open-source large models being weaponized."

AI Advancements Fuel Cyberattacks

Cybersecurity experts analyze that the reduced difficulty of attacks is closely related to the popularity of AI technology. In particular, open-weight AI models developed in China, due to their lack of high licensing fees and ease of local deployment, are being widely adopted by criminal syndicates.

These models are no longer limited to code generation but are flexibly applied throughout the entire attack process:

• Reconnaissance phase: Using AI to automatically scan system vulnerabilities and identify potential attack entry points.
• Execution phase: Automatically generating complex malicious code or social engineering scripts to increase the success rate of intrusions.
• Evasion phase: By simulating normal user behavior through AI, evading detection systems driven by traditional signature databases.

The Sagawa Express incident is seen as a typical microcosm of this trend. The attackers likely leveraged automation tools based on open-source models to achieve precise penetration of core business systems.

Industry Warning and Response

This incident has sounded the alarm for logistics enterprises relying on digital systems. As generative AI capabilities iterate, traditional security boundaries are facing unprecedented challenges. Relying solely on signature matching or static rules is no longer sufficient to effectively defend against advanced persistent threats (APTs) driven by AI.

Industry insiders are calling for enterprises to accelerate their transition to AI-native security architectures, introducing defensive systems capable of real-time behavioral analysis. At the same time, strengthening employees' awareness of new types of cyber fraud and building a dual defense line of "technology + human" is essential.

For the public, given the potential risk of personal information leakage, it is recommended to closely monitor abnormal account activities recently, remain vigilant regarding calls involving personal information verification, and change key passwords and enable two-factor authentication promptly when necessary.