DeepSeek AI Model Faces Security Concerns After AppSOC Testing
A recent investigation by cybersecurity firm AppSOC has highlighted significant security vulnerabilities in the AI model developed by DeepSeek. The findings, released on February 11, 2025, describe the model as a "Pandora's box" of cyberthreats.
AppSOC's tests, conducted using their AI Security Platform, involved automated static analysis, dynamic tests, and red-teaming techniques to simulate real-world attacks. The results showed that the DeepSeek-R1 model had a 98.8% failure rate in generating malware and an 86.7% failure rate in producing virus code. Additionally, the model demonstrated a 68% failure rate in generating responses with toxic or harmful language and produced factually incorrect information 81% of the time.
Mali Gorantla, co-founder and chief scientist at AppSOC, advised against using DeepSeek's model for business-related AI applications, citing the high failure rates as unacceptable for enterprise use. Despite the model's lower cost and open-source nature, Gorantla emphasized the need for caution.
DeepSeek, a China-based company, recently gained attention for its cost-effective AI model, which some claimed could rival those of U.S. tech giants. However, the model has faced criticism in the U.S., with calls for a ban on its use in government devices and allegations of using OpenAI's models in its development. DeepSeek has yet to respond to these concerns.
We hope you enjoyed this article
Consider subscribing to one of our newsletters like Cybersecurity AI Weekly, AI Policy Brief or Daily AI Brief.
Also, consider following us on social media:
More from Cybersecurity
Oct 31 Orange Cyberdefense Gets Early Access to Cyber Version of Mistral Large 4 Oct 31 Google Sees Attackers Using ARTEX and Other Agentic Frameworks in Intrusions Oct 30 Ransomware Operator n0n Spent Over $7,200 on AI Tools in Extortion Attacks Oct 30 AvalonX launches penetration testing platform with up to $10 million Oct 30 GLM 5.3 exploits Firefox patch gap to steal local filesMore from AI Safety
Oct 31 Anthropic Automates Search for Training Data That Evades Safety Monitors Oct 31 AI Workers, Led by Anthropic Staff, Give Tens of Thousands to Minnesota Candidates Oct 30 House Democrats Press OpenAI Over Safety Researcher Firings Oct 30 OpenAI Tightens ChatGPT Weapons Rules for Teens Oct 30 OpenAI Will Honor Shared robots.txt Signal for AI Training PreferencesCybersecurity AI Weekly
Weekly newsletter about AI in Cybersecurity.
Whitepaper
Tensordyne Napier: What If One Rack Could Do the Work of Nine?
Tensordyne
This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.
Read moreYou may also like
DeepSeek Reportedly Raises $15 Billion After US Restrictions
Tests Find DeepSeek Model Disabled Shutdown Software in 39% of Cases
DeepSeek Releases V4.1 Flash 1017 for Coding and Agent Tasks
China Approves DeepSeek and MiniMax Models for Overseas Use
DeepSeek Reportedly Agrees to Lead Winverse AI Seed Round
Daily AI Brief: the AI news that matters, in your inbox.