Is It Safe to Use DeepSeek AI? A Comprehensive Analysis for IT Teams

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.

DeepSeek AI’s Vulnerability to Jailbreaking and Malicious Use

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.

AI Model	Jailbreaking Success Rate	Malware Generation	Toxic Output Rate
DeepSeek AI	100%	98.8%	89%
GPT-4o	13%	5.6%	22%
Claude 3.5	7%	2.8%	18%

Their findings were alarming:

• 100% failure rate in blocking harmful queries, including cybercrime instructions and hate speech.
• 98.8% effectiveness in generating malware code, making it a security risk in adversarial environments.
• High toxicity levels (89%), meaning responses frequently included harmful or biased content.

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.

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How Safe is DeepSeek AI When it Comes to Data Handling?

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. 

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.

The Extent of Data Collection

Recent security audits and network traffic analysis tools like Wireshark have revealed that DeepSeek AI collects and processes:

• Text interactions: All inputs are stored indefinitely unless explicitly purged by the platform (which users cannot do themselves).
• User behavior patterns: Keylogging-level detail, including keystroke timing and typing cadence, is monitored.
• Device and network metadata: The system is harvesting information such as IP addresses, MAC addresses of peripherals (printers, external drives), and even Wi-Fi identifiers.
• Session Monitoring: Tracking of session duration, cursor movements, and multi-device session synchronization allows DeepSeek to map user behavior patterns in detail.
• Image Analysis (if applicable): If the AI is used in image-related use cases, DeepSeek might use this data to analyze what data you’re feeding.

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?

Jurisdictional Risks and Government Data Access

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.

What This Means for Users

• Risk of Corporate Espionage: Any company using DeepSeek AI for business purposes could inadvertently expose sensitive proprietary information that might be accessed by third parties.
• Data Export Risks: User data can legally be transmitted outside of the company's country without explicit user consent.
• Historical Data Requests: The law allows for retroactive access to stored user data for up to five years.
• Government Surveillance Potential: If DeepSeek is integrated into critical infrastructure or used for regulatory-sensitive industries, the AI model may be indirectly leveraged for state-backed intelligence gathering.

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.

Comparison of AI Model Data Policies

AI Model	Data Collection	User Control Over Data	Jurisdiction
DeepSeek AI	Extensive (text, keystrokes, metadata, device tracking, etc)	None	China
OpenAI GPT-4	Moderate (anonymized interactions)	Users can request deletion	USA
Claude 3.5	Minimal (no keystroke logging, session-based storage)	Full deletion supported	USA

Technical Risks: Unencrypted Data Storage & API Exposure

So, is deepseek secure? Beyond jurisdictional concerns, DeepSeek AI has demonstrated poor security hygiene in its backend architecture:

• Unencrypted Storage: Independent audits have revealed that DeepSeek stores request logs in plaintext on cloud servers, making them vulnerable to leaks.
• API Key Exposure: Multiple security researchers have identified DeepSeek API vulnerabilities where API keys were transmitted in plaintext over unencrypted channels, increasing the risk of credential theft.
• Weak Cryptographic Standards: The AI's security modules use outdated encryption (OpenSSL 1.1.1w with known vulnerabilities like CVE-2024-2515), making it an easier target for cyberattacks.
• Supply Chain Risks: Third-party dependencies in DeepSeek’s codebase include libraries with publicly disclosed vulnerabilities, making AI-integrated applications prone to indirect attacks.

How to Mitigate These Risks?

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:

1. Route API traffic through an intermediary security layer (such as Latenode) to control outbound data requests.
2. Isolate DeepSeek AI’s interactions from sensitive databases.
3. Implement strict monitoring to detect anomalies in AI interactions that may indicate data siphoning or manipulation.
4. Consider alternatives like Llama 3, Mistral, Claude 3.5, or ChatGPT (all available at Latenode) or even self-host DeepSeek. After all, the answer to ‘is deepseek safe to download?’ is probably yes, because when you run it locally on your computer, you basically isolate it from any other infrastructure and customize it by yourself.

These measures will help ensure your team can leverage AI while maintaining control over security, privacy, and compliance.

How to Use Latenode to Make DeepSeek Safe For Your Workflow?

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.

How Latenode Provides AI Security and Control

Challenge	Risk Impact	How Latenode Solved It
Uncontrolled Data Exposure	Sensitive information processed by AI	Latenode filters and anonymizes all AI inputs
Unverified AI Outputs	Biased or misleading responses reaching users	AI-generated content is validated in real-time
Regulatory Compliance Gaps	GDPR & industry regulations at risk	Compliance rules enforced before AI interaction
Unrestricted API Calls	Potential data siphoning by external AI models	Dynamic access controls prevent overexposure

• Isolated Execution

 

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.

• End-to-End Encryption & Anonymization

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.

• Dynamic Compliance & Custom Security Rules

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.  

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 can 

Future-Proofing AI Workflows with Latenode

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:

• Better AI oversight: Due to plug-and-play integration without history, they could set strict rules on which queries could reach DeepSeek AI. No account credentials were needed as well.
• Stronger compliance: GDPR, HIPAA, and industry standards were enforced automatically.
• Full AI governance: AI outputs were monitored, reducing risk from misinformation.
• Secure innovation: The company could explore AI automation without sacrificing security.

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!

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Frequently Asked Questions

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.

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