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July 13, 2025

Seeking Deeper: Assessing China’s AI Security Ecosystem

cetas.turing.ac.uk/ Research Report
As AI increasingly shapes the global economic and security landscape, China’s ambitions for global AI dominance are coming into focus. This CETaS Research Report, co-authored with Adarga and the International Institute for Strategic Studies, explores the mechanisms through which China is strengthening its domestic AI ecosystem and influencing international AI policy discourse. The state, industry and academia all play a part in the process, with China’s various regulatory interventions and AI security research trajectories linked to government priorities. The country’s AI security governance is iterative and is rapidly evolving: it has moved from having almost no AI-specific regulations to developing a layered framework of laws, guidelines and standards in just five years. In this context, the report synthesises open-source research and millions of English- and Chinese-language data points to understand China’s strategic position in global AI competition and its approach to AI security.

This CETaS Research Report, co-authored with the International Institute for Strategic Studies (IISS) and Adarga, examines China’s evolving AI ecosystem. It seeks to understand how interactions between the state, the private sector and academia are shaping the country’s strategic position in global AI competition and its approach to AI security. The report is a synthesis of open-source research conducted by IISS and Adarga, leveraging millions of English- and Chinese-language data points.

Key Judgements
China’s political leadership views AI as one of several technologies that will enable the country to achieve global strategic dominance. This aligns closely with President Xi’s long-term strategy of leveraging technological revolutions to establish geopolitical strength. China has pursued AI leadership through a blend of state intervention and robust private-sector innovation. This nuanced approach challenges narratives of total government control, demonstrating significant autonomy and flexibility within China’s AI ecosystem. Notably, the development and launch of the DeepSeek-R1 model underscored China's ability to overcome significant economic barriers and technological restrictions, and almost certainly caught China’s political leadership by surprise – along with Western chip companies.

While the Chinese government retains ultimate control of the most strategically significant AI policy decisions, it is an oversimplification to describe this model as entirely centrally controlled. Regional authorities also play significant roles, leading to a decentralised landscape featuring multiple hubs and intense private sector competition, which gives rise to new competitors such as DeepSeek. In the coming years, the Chinese government will almost certainly increase its influence over AI development through closer collaboration with industry and academia. This will include shaping regulation, developing technical standards and providing preferential access to funding and resources.

China's AI regulatory model has evolved incrementally, but evidence suggests the country is moving towards more coherent AI legislation. AI governance responsibilities in China remain dispersed across multiple organisations. However, since February 2025, the China AI Safety and Development Association (CnAISDA) has become what China describes as its counterpart to the AI Security Institute. This organisation consolidates several existing institutions but does not appear to carry out independent AI testing and evaluation.

The Chinese government has integrated wider political and social priorities into AI governance frameworks, emphasising what it describes as “controllable AI” – a concept interpreted uniquely within the Chinese context. These broader priorities directly shape China’s technical and regulatory approaches to AI security. Compared to international competitors, China’s AI security policy places particular emphasis on the early stages of AI model development through stringent controls on pre-training data and onerous registration requirements. Close data sharing between the Chinese government and domestic AI champions, such as Alibaba’s City Brain, facilitates rapid innovation but would almost certainly encounter privacy and surveillance concerns if attempted elsewhere.

The geographical distribution of China's AI ecosystem reveals the strategic clustering of resources, talent and institutions. Cities such as Beijing, Hangzhou and Shenzhen have developed unique ecosystems that attract significant investments and foster innovation through supportive local policies, including subsidies, incentives and strategic infrastructure development. This regional specialisation emerged from long-standing Chinese industrial policy rather than short-term incentives.

China has achieved significant improvements in domestic AI education. It is further strengthening its domestic AI talent pool as top-tier AI researchers increasingly choose to remain in or return to China, due to increasingly attractive career opportunities within China and escalating geopolitical tensions between China and the US. Chinese institutions have significantly expanded domestic talent pools, particularly through highly selective undergraduate and postgraduate programmes. These efforts have substantially reduced dependence on international expertise, although many key executives and researchers continue to benefit from an international education.

Senior scientists hold considerable influence over China’s AI policymaking process, frequently serving on government advisory panels. This stands in contrast to the US, where corporate tech executives tend to have greater influence over AI policy decisions.

Government support provides substantial benefits to China-based tech companies. China’s government actively steers AI development, while the US lets the private sector lead (with the government in a supporting role) and the EU emphasises regulating outcomes and funding research for the public good. This means that China’s AI ventures often have easier access to capital and support for riskier projects, while a tightly controlled information environment mitigates against reputational risk.

US export controls have had a limited impact on China’s AI development. Although export controls have achieved some intended effects, they have also inadvertently stimulated innovation within certain sectors, forcing companies to do more with less and resulting in more efficient models that may even outperform their Western counterparts. Chinese AI companies such as SenseTime and DeepSeek continue to thrive despite their limited access to advanced US semiconductors.

Chinese chipmaker Sophgo adapts compute card for DeepSeek in Beijing’s self-reliance push | South China Morning Post

www.scmp.com - Heightened US chip export controls have prompted Chinese AI and chip companies to collaborate.

Chinese chipmaker Sophgo has adapted its compute card to power DeepSeek’s reasoning model, underscoring growing efforts by local firms to develop home-grown artificial intelligence (AI) infrastructure and reduce dependence on foreign chips amid tightening US export controls.
Sophgo’s SC11 FP300 compute card successfully passed verification, showing stable and effective performance in executing the reasoning tasks of DeepSeek’s R1 model in tests conducted by the China Telecommunication Technology Labs (CTTL), the company said in a statement on Monday.

A compute card is a compact module that integrates a processor, memory and other essential components needed for computing tasks, often used in applications like AI.

CTTL is a research laboratory under the China Academy of Information and Communications Technology, an organisation affiliated with the Ministry of Industry and Information Technology.

TikTok Faces Fresh European Privacy Investigation Over China Data Transfers

The Irish Data Privacy Commission announced that TikTok is facing a new European Union privacy investigation into user data sent to China.

TikTok is facing a fresh European Union privacy investigation into user data sent to China, regulators said Thursday.

The Data Protection Commission opened the inquiry as a follow up to a previous investigation that ended earlier this year with a 530 million euro ($620 million) fine after it found the video sharing app put users at risk of spying by allowing remote access their data from China.

The Irish national watchdog serves as TikTok’s lead data privacy regulator in the 27-nation EU because the company’s European headquarters is based in Dublin.

During an earlier investigation, TikTok initially told the regulator it didn’t store European user data in China, and that data was only accessed remotely by staff in China. However, it later backtracked and said that some data had in fact been stored on Chinese servers. The watchdog responded at the time by saying it would consider further regulatory action.

“As a result of that consideration, the DPC has now decided to open this new inquiry into TikTok,” the watchdog said.

“The purpose of the inquiry is to determine whether TikTok has complied with its relevant obligations under the GDPR in the context of the transfers now at issue, including the lawfulness of the transfers,” the regulator said, referring to the European Union’s strict privacy rules, known as the General Data Protection Regulation.

TikTok, which is owned by China’s ByteDance, has been under scrutiny in Europe over how it handles personal user information amid concerns from Western officials that it poses a security risk.

TikTok noted that it was one that notified the Data Protection Commission, after it embarked on a data localization project called Project Clover that involved building three data centers in Europe to ease security concerns.

“Our teams proactively discovered this issue through the comprehensive monitoring TikTok implemented under Project Clover,” the company said in a statement. “We promptly deleted this minimal amount of data from the servers and informed the DPC. Our proactive report to the DPC underscores our commitment to transparency and data security.”

Under GDPR, European user data can only be transferred outside of the bloc if there are safeguards in place to ensure the same level of protection. Only 15 countries or territories are deemed to have the same data privacy standard as the EU, but China is not one of them.

Nippon Steel Subsidiary Blames Data Breach on Zero-Day Attack

securityweek.com - Nippon Steel Solutions has disclosed a data breach that resulted from the exploitation of a zero-day in network equipment.

Japan-based Nippon Steel Solutions on Tuesday disclosed a data breach that resulted from the exploitation of a zero-day vulnerability.

Nippon Steel Solutions, also called NS Solutions, offers cloud, cybersecurity and other IT solutions. The company is a subsidiary of Japanese steel giant Nippon Steel, which recently acquired US Steel in a controversial deal.

Nippon Steel Solutions said in a statement posted on its Japanese-language website that it detected suspicious activity on some servers on March 7.

An investigation showed that hackers had exploited a zero-day flaw in unspecified network equipment, and gained access to information on customers, partners and employees.

In the case of customers, the attackers may have stolen information such as name, company name and address, job title, affiliation, business email address, and phone number.

The exposed information in the case of partners includes names and business email addresses, while in the case of employees the attackers may have obtained names, business email addresses, job titles, and affiliation.

Nippon Steel Solutions said the information may have been exfiltrated, but to date it has found no evidence of a data leak on the dark web or elsewhere.

The notorious ransomware group BianLian claimed to have stolen hundreds of gigabytes of data from Nippon Steel USA in mid-February, including files related to finances, employees, and production.

The cybercriminals at the time threatened to leak all of the stolen data, but the group went dark a few weeks later.

Nippon Steel does not appear to have confirmed a data breach in response to BianLian’s claims and it’s unclear if the two incidents are related.

SecurityWeek has reached out to NS Solutions for clarifications and will update this

Bitcoin Depot breach exposes data of nearly 27,000 crypto users

Bitcoin Depot, an operator of Bitcoin ATMs, is notifying customers of a data breach incident that has exposed their sensitive information.
In the letter sent to affected individuals, the company informs that it first detected suspicious activity on its network last year on June 23.

Although the internal investigation was completed on July 18, 2024, a parallel investigation by federal agencies dictated that public disclosure of the incident should be withheld until it was completed.

“On July 18, 2024, the investigation was complete, and we identified your personal information contained within documents related to certain of our customers that the unauthorized individual obtained,” explains Bitcoin Depot in the letter.

“Unfortunately, we were not able to inform you sooner due to an ongoing investigation. Federal law enforcement requested that Bitcoin Depot wait to provide you notice until after they completed the investigation.”

The type of data that has been exposed in this incident varies from individual to individual and may include:

Full name
Phone number
Driver’s license number
Address
Date of birth
Email address
Bitcoin Depot is one of the largest Bitcoin ATM networks in the United States, operating 8,800 machines in the U.S., Canada, and Australia.

Critical-Vulnerabilities-in-Network Detective

Two vulnerabilities have been identified in RapidFire Tools Network Detective, a system assessment and reporting tool developed by Kaseya (RapidFire Tools). These issues significantly compromise the confidentiality and integrity of credentials gathered and processed during routine network scans, exposing sensitive data to both local attackers and potentially malicious insiders.

Vulnerability 1: Passwords in Cleartext
During its normal operation, Network Detective saves usernames and passwords in plain, readable text across several temporary files. These files are stored locally on the device and are not protected or hidden. In many cases, the credentials collected include privileged or administrative accounts, such as those used for VMware.

An attacker who gains access to the machine running the scan—whether physically, remotely, or through malware—can easily retrieve these passwords without needing to decrypt anything. This presents a serious risk to client infrastructure, especially when those credentials are reused or provide broad system access.

Vulnerability 2: Reversible Encryption
RapidFire Tools Network Detective uses a flawed method to encrypt passwords and other sensitive data during network scans. The encryption process is based on static, built-in values, which means it produces the same result every time for the same input. This makes it possible for anyone with access to the tool or encrypted data to easily reverse the encryption and retrieve original passwords.

This weakness puts client environments at risk, especially since the encrypted data often includes administrative credentials. The encryption does not follow modern security standards, and attackers do not need special tools or expertise to break it—only access to the files or application.

Analysis and Background
Network Detective, a product developed by RapidFire Tools (a Kaseya company), is designed to scan networks for vulnerabilities, misconfigurations, and compliance issues. It is used by managed service providers (MSPs), IT consultants, and internal IT departments to assess network health and generate reports. While commonly deployed as a standalone binary for one-off scans—often during sales or onboarding—Network Detective also supports scheduled, recurring scans in installed environments.

The application is typically configured via a step-by-step wizard, prompting users to define targets (e.g., IP ranges), scan types (e.g., HIPAA, PCI), and credentials for services such as Active Directory or VMware. This configuration is stored locally and reused for automated scans. Notably, the same binaries are used for both ad hoc and scheduled executions, meaning any vulnerabilities affect both deployment models equally.

Due to its ease of use and deep network visibility, the tool is often run with elevated privileges across production systems. Users implicitly trust the application to securely handle credentials and sensitive data. However, the issues discovered occur under default conditions, without requiring misuse or advanced manipulation—highlighting a significant risk for environments relying on the tool for security posture validation.