November 27, 2024 at 08:16AM
Generative AI is rapidly learning to code, mirroring human development but also inheriting flaws from open-source models. Chris Wysopal highlights the challenge of increasing code volume leading to more vulnerabilities. He proposes using AI to identify and fix these issues, emphasizing ongoing work on specialized language models for enhanced security.
**Meeting Takeaways:**
1. **Faster Coding with GenAI:** Generative artificial intelligence (GenAI) is significantly quicker at coding, akin to human developers, but picks up flaws along the way.
2. **Learning from Flawed Models:** GenAI and large language models (LLMs) learn to code from open source models, which are not without their own flaws, leading to the creation of more code and consequently, more vulnerabilities.
3. **Challenge of Vulnerability Management:** The increase in code production means a heightened focus on identifying and rectifying vulnerabilities at a comparable speed.
4. **Proposed Solutions:** Chris Wysopal emphasizes the importance of using AI to help identify and fix vulnerabilities in AI-generated code, though this capability is still under development.
5. **StarCoder and Other Models:** Research indicates that StarCoder is currently the best LLM for writing code, despite not being completely free of vulnerabilities. ChatGPT 4.0 and ChatGPT 2.5 are also somewhat effective in generating secure code.
6. **Limitations of General-purpose LLMs:** While general-purpose LLMs can fix some security bugs, they are not particularly effective, highlighting the need for specialized LLMs focused on code security.
7. **Ongoing Efforts in Security Development:** Wysopal and his team at Veracode, along with other companies, are actively working on developing specialized LLMs for secure coding.