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.
Register now: PQC Update 2026: Standards, Performance, and Migration Reality
Date: June 11 | 9 AM PT
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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