Nikesh Arora, Chairman and CEO of Palo Alto Networks, expressed concern over the increasing use of advanced artificial intelligence (AI) models for discovering software vulnerabilities and identifying potential attack vectors.
While such capabilities can help strengthen cybersecurity, they can also provide attackers with faster ways to exploit weaknesses in corporate systems. As Arora noted in a LinkedIn post, the main challenge is ensuring that organizations can verify, prioritize, and patch vulnerabilities at the same speed that AI discovers them.
Arora emphasized that most organizations lack the necessary resources to apply patches at the required pace, especially small businesses. Small businesses often suffer from a shortage of security specialists, while large companies are forced to test patches on existing applications. Furthermore, he noted that different models detect different types of weaknesses, meaning one model cannot provide complete coverage.
Vulnerability discovery is only the initial stage. Teams must confirm it, assess the risk, develop a fix, test it for failures, and then deploy it. False positives, or incorrect alerts, lead to wasted time, and untested patches can disrupt service operations.
The scale of the problem is growing. The U.S. National Institute of Standards and Technology reported that the number of submissions to its Vulnerability Database increased by 263% between 2020 and 2025. In 2025, nearly 42,000 entries were enriched, but this proved insufficient. In April 2026, the institute decided to prioritize based on risk, focusing on exploitable vulnerabilities and critical software.
AI developers are beginning to link discovery with remediation. Anthropic's Glasswing project, launched in April 2026 with the participation of Palo Alto Networks, provides selected organizations with access to Claude Mythos Preview for defensive security purposes. Anthropic reported that partners identified over 10,000 high or critical severity vulnerabilities by June and expanded the program to approximately 150 additional organizations.
On November 4, OpenAI announced that a controlled Linux kernel pipeline generated candidate fixes for 948 local privilege escalation vulnerabilities, which allow a user to gain higher access rights. Human researchers reviewed these results before passing them on to maintainers.
On November 4, CERT-In in India issued a warning that attackers using machine intelligence and payment APIs are targeting non-banking credit institutions, fintech companies, payment providers, and cryptocurrency platforms. The agency also published a 2026 guide on defending against vulnerabilities using AI and AI security auditing.
Arora advocates for virtual patching as a temporary measure. He stated: 'The most obvious solution is virtual patching. It is a time-tested technology that is currently available from cyber vendors for endpoints, WAF, cloud, and network use cases.'
A WAF is a web application firewall that filters website and application traffic. A virtual patch is a security rule that blocks a known method of exploiting a vulnerability without changing the affected software. This buys time to test a permanent update but does not eliminate the weakness itself. The Open Worldwide Application Security Project warns that it only protects traffic that the system checks and does not recognize rule variations.
Arora calls for the creation of a universal vulnerability registry and the acceleration of the development of defensive signatures, or detection rules. He also highlights operational technology—systems that control or monitor physical processes such as energy, water supply, and transportation. Updating these systems can be complex, as an outage could affect safety or essential services.



