How AI Finds Vulnerabilities in Cryptographic Libraries

Can AI help uncover security issues that traditional testing, fuzzing, and code review miss?

AI-based code analysis tools are advancing rapidly, but questions remain about their effectiveness when applied to highly reviewed security-critical software.

Join wolfSSL and AISLE on June 11 at 9 AM PT for a technical discussion on AI-assisted vulnerability discovery. AISLE will share results from applying AI-assisted analysis to curl, followed by a technical review of findings identified within the wolfSSL codebase and discussion of how those results were evaluated.

This webinar will cover:

Applying AI-assisted analysis to security-critical open source software

Findings identified within the wolfSSL codebase

Technical review and evaluation of selected findings

Lessons learned from applying AI to vulnerability discovery

Ask the Experts: Answer Key Questions

Q: Can AI find issues in software that has already undergone extensive security review? A: Results generated from applying AI-assisted analysis to curl provide a practical example of how these tools perform on widely used security-critical software. Q: What findings were identified within the wolfSSL codebase? A: Findings identified through AI-assisted analysis, along with the technical evaluation used to assess their significance. Q: How should AI-generated security findings be interpreted? A: The process of investigating AI-generated results, distinguishing meaningful findings from noise, and understanding where human expertise remains essential.

See what AI analysis uncovered when applied to real-world security-critical software.

If you have questions about any of the above, please contact us at facts@wolfssl.com or call us at +1 425 245 8247.

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