AI-augmented attackers are probing every corner of applications with inexhaustible persistence, forcing defenders to adopt AI-driven security tools, but many vendors mislabel legacy systems as "AI." L…
Xint, an AI-powered penetration testing tool, discovered an insecure direct object reference (IDOR) vulnerability in a healthcare client's system that exposed patients' protected health information. T…
Xint's AI-powered application security testing tool produces results that vary between scans of the same target, with core exploitable vulnerabilities recurring consistently across approximately 60-70…
Xint, an AI-powered autonomous pentesting platform, is not designed to replace human security engineers but to act as a a force multiplier by automating code analysis and vulnerability discovery. The …
Xint, an LLM-based security tool developed by Theori, reports a false positive rate of less than 25% for its highest-severity vulnerability findings, based on manual validation through proof-of-concep…
On May 11, 2026, Apple released security updates for iOS, iPadOS, and macOS to patch two kernel-level vulnerabilities (CVE-2026-28972 and CVE-2026-28986) discovered by Xint researchers. The first flaw…
Zero data retention (ZDR) policies are essential for teams using large language models (LLMs), as default provider practices often log prompts and outputs for extended periods, creating security and c…
Critical evaluation framework for purchasing AI-powered penetration testing tools, warning that the market is fragmented and that vendors often use the same terms to describe different capabilities. I…
Theori, a cybersecurity company led by CEO Brian Pak, announced that its AI hacker solution, Xint, has been adopted by Samsung Electronics to automate security for large-scale IT assets. Xint autonomo…
Focusing solely on frontier AI models for cybersecurity is misguided, as "good enough" reasoning combined with effective scaffolding is more important. It highlights that Xint's autonomous AI auditor …
Xint's article explains that AI-native code scanners face unpredictable costs because linear increases in code lines can cause exponential increases in token consumption, making it difficult for secur…
Business logic vulnerabilities are security flaws that arise not from coding errors, but from the abuse of legitimate system workflows, where each individual request appears normal but violates the in…