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George Miloradovich
Researcher, Copywriter & Usecase Interviewer
February 20, 2025
Max, the CTO of a small but fast-growing company, found himself wondering "is DeepSeek safe to use?" while searching for a cost-effective AI model to automate customer support and internal workflows. With its advanced reasoning capabilities and affordability, DeepSeek seemed like an attractive choice. The model promised seamless integration, high performance, and a budget-friendly alternative to costly competitors like ChatGPT-o3-mini.
However, the question "can DeepSeek be trusted?" soon became paramount. Within weeks of deployment, Max's team started noticing anomalies. The chat logs revealed unexplained surges in data traffic, and employees observed inconsistencies in content moderation – sometimes the AI allowed sensitive or even harmful responses to pass through unchecked. A deeper analysis exposed alarming concerns:
This situation raised a pressing question: Are small IT teams unknowingly exposing themselves to security threats by integrating DeepSeek AI?
Through this article, we will explore the hidden risks and provide actionable recommendations for professionals to adopt AI safely without compromising their data and infrastructure. These would help in a lot of use cases, both in personal use on the official Deepseek launcher and when you build an automation scenario on Latenode.
One of the main questions when evaluating how safe DeepSeek AI is revolves around its vulnerability to jailbreaking. This is a process where users manipulate the model to bypass its built-in restrictions.
Jailbreaking allows attackers to generate harmful, unethical, or even illegal content, making it a severe security risk. A model with weak resistance to jailbreaking can be exploited for cybercrime, misinformation, and malware generation, posing serious threats to businesses and end-users.
Security researchers at Cisco and AI Safety Alliance conducted extensive jailbreaking tests using the HarmBench dataset, which evaluates the robustness of AI models against adversarial prompts. The results highlighted DeepSeek AI’s inability to prevent unauthorized and dangerous responses.
Their findings were alarming:
DeepSeek AI’s lack of robust content moderation raises serious concerns about security. These vulnerabilities make DeepSeek AI particularly dangerous in environments that require strict compliance, data protection, and controlled AI interactions.
DeepSeek AI operates with an aggressive approach to data collection, far exceeding what most enterprises consider acceptable. According to Section 4.2 of its Terms of Use, the platform explicitly reserves the right to analyze and store user queries and responses for service improvement, and it doesn’t provide an opt-out mechanism.Â
This policy means that every interaction with DeepSeek AI is logged, indexed, and potentially used for model retraining. So, DeepSeek safe? The answer is murky at best.
Recent security audits and network traffic analysis tools like Wireshark have revealed that DeepSeek AI collects and processes:
Unlike OpenAI or Anthropic, DeepSeek does not offer a user-accessible interface for managing stored data, nor does it provide any deletion tools. This makes it impossible for users to verify or remove their historical interactions from the system. Because of all that, teams like the one Max leads once more ask a question: Is it safe to use DeepSeek AI, especially if businesses have no control over their own data?
DeepSeek AI’s parent company operates under the jurisdiction of Chinese cybersecurity and national security laws, which enforce strict data-sharing obligations. Under the 2015 National Security Law of China (Article 7), any organization must provide data to authorities without the need for a court order.
For businesses operating in regulated industries (finance, healthcare, legal services, R&D), this raises major compliance issues with data protection frameworks like GDPR, HIPAA, and CCPA.
So, is deepseek secure? Beyond jurisdictional concerns, DeepSeek AI has demonstrated poor security hygiene in its backend architecture:
The combination of aggressive data collection, lack of user control, government-mandated compliance risks, and weak backend security makes DeepSeek AI one of the least privacy-friendly AI models on the market today. Organizations that handle sensitive data should reconsider integrating this model into their workflows.
To mitigate these risks, companies using AI-driven workflows should:
These measures will help ensure your team can leverage AI while maintaining control over security, privacy, and compliance.
Latenode is a low-code automation platform, built to ensure that teams using DeepSeek AI can do so without sacrificing data privacy, compliance, or security. Unlike direct API integrations, which may expose your business to unverified queries and potential data leaks, Latenode provides multiple layers of protection while maintaining the flexibility and power that small teams need.
Every interaction with DeepSeek AI is passed through Latenode’s plug-and-play integration node. It means that the model doesn’t store history, and each request is unique. This drastically reduces the risk of unintentionally exposing private data.
Latenode uses CloudFlare and Microsoft Azure servers to ensure safety and encrypt all information, removing identifying markers before any information is passed to DeepSeek AI, ensuring compliance with GDPR, HIPAA, and other regulatory standards.
Whether you need strict filtering for financial transactions, AI moderation in customer interactions, or compliance-specific workflows, Latenode allows you to configure AI security precisely as they need. Â
For example, in your scenario, DeepSeek might only use its creative capabilities to formulate search queries for article topic research, pass them to a sage model Perplexity to conduct online research, and then ChatGPT would write this article. In this case, you canÂ
So, can Deepseek be trusted, especially in high-stake scenarios? With the right safeguard measures, the answer is probably yes. For Max, the shift to Latenode wasn’t just about fixing security loopholes – it was about making AI a sustainable, scalable tool for automation. The team could now experiment, optimize, and scale their AI-powered processes without fear of regulatory backlash or security breaches.
By integrating DeepSeek AI through Latenode’s secure architecture, Max’s team achieved:
Max knew that AI was an invaluable asset for their business. But he also learned the hard way that without security, AI is not just an innovation – it’s a liability waiting to happen.
The reality is simple: AI is a game-changer, but without security, it’s a ticking time bomb. With Latenode, companies don’t just automate workflows—they future-proof their AI infrastructure in a way that ensures trust, compliance, and control. Join Max now and test your workflows on Latenode!
How can we ensure the secure use of DeepSeek AI in our workflows?
Security requires continuous monitoring, role-based access control, and API filtering. Platforms like Latenode help enforce query validation, anonymization, and real-time AI monitoring, reducing risks without compromising automation efficiency.
What are the main risks of using DeepSeek AI?
DeepSeek AI poses risks such as data leaks, unauthorized data retention, and adversarial manipulation. Its susceptibility to jailbreaking and biased outputs further amplifies security concerns, making AI governance and compliance enforcement essential.
Is integrating third-party platforms with DeepSeek AI complex?
Integration can be risky without structured oversight. Latenode simplifies AI implementation by offering pre-built security modules, automated compliance controls, and seamless API orchestration, ensuring smooth adoption without security trade-offs.
Is DeepSeek AI safe to use?
DeepSeek AI lacks built-in privacy safeguards, requiring strict external protections to mitigate risks. It should only be deployed through secure gateways, ensuring API traffic filtering, encrypted data storage, and compliance-ready workflows to prevent misuse.