Can AI Help Us Understand Vulnerabilities? Exploring AI-driven Approaches to Cybersecurity
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In this masterclass, we explored how Artificial Intelligence (AI) is transforming vulnerability analysis to enhance cybersecurity. We will begin by examining how vulnerabilities are typically disclosed, with descriptions detailing how they can be exploited by malicious actors. As vulnerability databases grow, analyzing and prioritizing them at scale is becoming an increasing challenge. This is where AI comes in: by using language models (LMs), we can automate and enhance this analysis. LMs are powerful AI tools that learn from text, making them ideal for processing vulnerability descriptions and automating security tasks. This session will provide a brief introduction to how LMs work, how they can be fine-tuned for new tasks, and will explore their applications in cybersecurity. One key use case is the automation of risk assessment during the disclosure process: LMs can anticipate the malicious actions an attacker might take by exploiting a vulnerability based on its description, thus enabling security teams to prioritize and categorize threats more effectively. Another innovative application will also be explored: the use of AI agents as cyberattackers to discover the most critical attack paths within a network. An AI agent can analyze a network with known vulnerabilities and simulate the decisions of an attacker, strategically selecting and sequencing vulnerabilities to exploit based on a specific threat model. By analyzing the identified attack paths, organizations can pinpoint critical weaknesses and implement proactive defenses before real threats emerge.