AI + a16z

What DeepSeek Means for Cybersecurity

Feb 28, 2025

Ian Webster, founder of PromptFoo, discusses vulnerabilities in AI models and user protection, emphasizing the need for caution with DeepSeek's backdoors. Dylan Ayrey from Truffle Security highlights the security risks of AI-generated code, urging developers to ensure safety through robust training alignments. Brian Long of Adaptive focuses on the threats posed by deepfakes and social engineering, stressing the importance of vigilance as generative AI evolves. Together, they navigate the complex landscape of AI security, calling for proactive measures against emerging risks.

52:13

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Episode guests

Brian Long

Dylan Ayrey

Ian Webster

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Episode notes

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Quick takeaways

The DeepSeek model presents significant vulnerabilities, necessitating users to implement protective measures against potential backdoors and jailbreaks.

AI-generated code poses similar security risks as inexperienced developers produce, emphasizing the need for rigorous code review and human oversight.

As deepfakes evolve, organizations must prioritize engaging training and robust security measures to combat sophisticated social engineering threats.

Deep dives

Caution with Open Source AI Models

The release of the DeepSeq R1 model has raised concerns about its stability and security, particularly in enterprise applications. It is recommended to avoid using this model in end-user facing situations due to its susceptibility to jailbreaks and lack of robust security measures. Analysis highlights that while DeepSeq may offer advanced reasoning capabilities, the infrastructure supporting it is seen as insecure and poorly hardened against common vulnerabilities. Companies should prioritize waiting for more stable open-source alternatives before deploying such technology in sensitive environments.

Intro

2min

DeepSeek: Advancements and Concerns

4min

Exploring Security Vulnerabilities in DeepSeq Models

2min

Censorship in AI: A Global Comparison

5min

Navigating AI in Enterprise: Challenges and Security

20min

The Rising Threat of Social Engineering and Deepfakes

2min

Protecting Yourself from Voice Replication Risks in a Deepfake Era

2min

Navigating the Cybersecurity Landscape

15min

In this episode of AI + a16z, a trio of security experts join a16z partner Joel de la Garza to discuss the security implications of the DeepSeek reasoning model that made waves recently. It's three separate discussions, focusing on different aspects of DeepSeek and the fast-moving world of generative AI.

The first segment, with Ian Webster of Promptfoo, focuses on vulnerabilities within DeepSeek itself, and how users can protect themselves against backdoors, jailbreaks, and censorship.

The second segment, with Dylan Ayrey of Truffle Security, focuses on the advent of AI-generated code and how developers and security teams can ensure it's safe. As Dylan explains, many problem lie in how the underlying models were trained and how their security alignment was carried out.

The final segment features Brian Long of Adaptive, who highlights a growing list of risk vectors for deepfakes and other threats that generative AI can exacerbate. In his view, it's up to individuals and organizations to keep sharp about what's possible — while the the arms race between hackers and white-hat AI agents kicks into gear.

Learn more:

What Are the Security Risks of Deploying DeepSeek-R1?

Research finds 12,000 ‘Live’ API Keys and Passwords in DeepSeek's Training Data

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