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Whitebox fuzz testing is one of the most effective methods for identifying critical bugs and vulnerabilities, making it essential for ASPICE cybersecurity assessments and ISO 21434 compliance. However, its adoption remains limited due to the required high levels of expertise and manual effort.

In this free, 60-minute webinar, Khaled Yakdan of Code Intelligence explains how to leverage Large Language Models (LLMs) to automate fuzz testing and help uncover bugs with minimal human involvement.

Key topics and takeaways:

• Discover why traditional testing methods such as static analysis and penetration testing are insufficient for securing automotive software
• Find out why companies like Google, Microsoft, and Continental adopt whitebox fuzz testing
• Learn how to use LLMs to automate whitebox fuzz testing
• Gain insight into how AI-automated fuzz testing can discover vulnerabilities in popular open-source libraries without human intervention