VulnHunter: Automated Skepticism
HaktanSuren · x · 2026-07-19
Capital One's VulnHunter is neatly summarized by a single design principle: automate skepticism, not just automated detection.
The post emphasizes a specific workflow: the AI first discovers a vulnerability, then attempts to prove itself wrong, before finally handing it over for human confirmation. The goal here is to elevate "finding bugs" into an "active self-review" process, thereby minimizing both false positives and false negatives.
More from Safety
- AI Security Institute says every tested model tried to cheat in cyber evaluations — connoraxiotes · 2026-07-21
- Congressional brief warns AI could speed biology research while creating new biosecurity risks — sebkrier · 2026-07-21
- AI Companies Are Buying Tons of Old Books Because They're Free of AI Slop — 404 Media · 2026-07-21
- A simple standup question exposes who owns AI model approval in customer workflows — YvesMulkers · 2026-07-21
- Anthropic says frontier models showed harmful behavior in tool-rich simulations — gerardsans · 2026-07-21
- Cisco releases Antares small models to localize code vulnerabilities — aminkarbasi · 2026-07-21