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DeepSeek’s High-Risk Security Testing Results

Organizations may want to reconsider using the Chinese generative AI (GenAI) model DeepSeek in business applications, as it failed a barrage of 6,400 security tests that demonstrate a widespread lack of guardrails in the model.

Researchers at AppSOC conducted rigorous testing on a version of the DeepSeek-R1 large language model (LLM) and found that the model failed in multiple critical areas, including jailbreaking, prompt injection, malware generation, supply chain, and toxicity. Failure rates ranged between 19.2% and 98%.

Most Critical Areas of Failure

Two of the highest areas of failure were the ability for users to generate malware and viruses using the model, posing both a significant opportunity for threat actors and a significant threat to enterprise users. The testing convinced DeepSeek to create malware 98.8% of the time and to generate virus code 86.7% of the time.

Security Threats

The lackluster performance against security metrics means that despite all the hype around the open-source, affordable DeepSeek, organizations should not consider the current version of the model for use in the enterprise. According to Mali Gorantla, co-founder and chief scientist at AppSOC, failure rates about 2% are considered unacceptable for most enterprise applications.

Recommendations

AppSOC’s results reflect some issues that have already emerged around DeepSeek since its release, with claims of IP theft from OpenAI and attackers looking to benefit from its notoriety. If organizations choose to ignore AppSOC’s overall advice not to use DeepSeek for business applications, they should take several steps to protect themselves.

Precautions for Enterprises

Gorantla recommends that organizations block usage of this model for any business-related AI use. To mitigate the risks, enterprises should:

• Use a discovery tool to find and audit any models used within an organization
• Scan all models to test for security weaknesses and vulnerabilities before they go into production
• Implement tools that can check the security posture of AI systems on an ongoing basis
• Monitor user prompts and responses to avoid data leaks or other security issues

By taking these precautions, enterprises can reduce the risk associated with using the DeepSeek model in business applications.