Patrick Kuo

TXOne Networks Inc. / Senior Threat Researcher, Threat Reasearch

Currently working at TXOne Networks Inc. in vulnerability research and technical development. The main tasks include building vulnerability assessment services, analyzing network traffic, malware, and developing Hunting System, Hunting Agent, Threat Atlas and Vulnerability Assessment to obtain the most up-to-date attack intelligence. Additionally, I have previously served as a speaker at BlackHat Europe, FIRST, CYBERSEC, and HITCON.

SPEECH
4/17 (Thu.) 10:15 - 10:45 1F 1B AI Security & Safety Forum Live Translation Session
Leveraging AI for Automated Attack Vector Extraction and Vulnerability Prevention

In this session, we’ll explore how Artificial Intelligence (AI) can enhance cybersecurity by extracting attack vector linked to vulnerabilities, offering a more proactive and efficient approach. Traditional methods of detecting vulnerabilities rely on security researchers manually reverse-engineering attack traffic and emulating potential attack behaviors. While effective, this process is time-consuming and exposes systems to risk during testing, increasing the likelihood of compromise in production environments.

AI addresses this challenge by automating the detection of attack vector and behaviors tied to specific vulnerabilities. This capability enables security teams to identify suspicious activities without constant manual intervention or exposing live systems. By integrating AI into vulnerability prevention, organizations can reduce the risk of attacks in production environments. AI-driven systems can autonomously flag suspicious behaviors or protocols indicative of an active threat.

This AI-powered approach enhances vulnerability prevention, offering stronger and more automated protection, reducing the potential for system compromise and providing a higher level of security.