Cyber security stocks are pumped up on P(doom)

By the Editorial Team · Saturday, September 26, 2026

Major cybersecurity firms like Palo Alto Networks and CrowdStrike have seen their stock prices more than double amid growing concerns about AI-enabled cyber threats that bypass traditional defenses. This surge reflects expected increases in corporate cybersecurity spending and highlights a future where collaboration between AI developers and established security vendors will be crucial to addressing both automated and human-targeted attacks.

The rising concern over the potential for artificial intelligence (AI) to cause widespread harm, often referred to by the term "P(doom)," has coincided with a notable surge in the stock prices of major cybersecurity firms. Over the past six months, companies such as Palo Alto Networks, CrowdStrike, and Fortinet have seen their shares more than double in value, reflecting increased investor confidence amid growing cyber threats linked to AI.

AI technologies have expanded the capabilities of malicious actors, enabling them to bypass traditional security measures with sophisticated methods. These include the creation of deepfake media, highly personalized phishing schemes, and the manipulation of AI agents within networks to leak sensitive data. As a result, corporate spending on cybersecurity is expected to rise substantially, with reports projecting an average annual increase of around 10 percent in cybersecurity budgets between 2025 and 2030. Revenue growth expectations for industry leaders like Palo Alto Networks and CrowdStrike stand at approximately 20 percent per year over the next two years.

However, the longevity of traditional cybersecurity vendors’ dominance in capturing this growing market is under scrutiny. Some experts point to the emergence of large language models (LLMs) as both the source of new cyber vulnerabilities and potential tools for addressing them. Since the release of Anthropic’s Mythos model last April, LLMs have been employed extensively for software scanning, identifying thousands of previously undetected vulnerabilities. This capability extends to generating patches—corrective updates for flawed code—a business avenue closely tied to LLM technologies.

Nonetheless, challenges remain in prioritizing which vulnerabilities require immediate attention and ensuring timely implementation of updates within organizations. Established cybersecurity companies continue to hold a competitive edge due to their deep integration with clients’ systems and incident response protocols. There is potential for collaboration between cybersecurity vendors and AI model developers to enhance defenses against software-based threats.

Despite advances in automated detection, over 80 percent of cyberattacks still exploit human factors such as stolen credentials and compromised passwords. According to Bernstein, while AI-driven techniques empower cybercriminals, LLM providers are not currently well-positioned to identify these human-centric threats. Looking ahead, AI firms may strengthen their relationships with enterprise clients as they expand into application services, yet the volume and complexity of AI-enabled attacks are expected to surpass the scope that LLMs can singly address.

In summary, rising fears about AI-induced risks have galvanized investment in cybersecurity, driving growth for established companies. At the same time, emerging AI technologies offer promising tools for vulnerability discovery and remediation, but traditional vendors maintain an important role in managing human-targeted threats and operational security. The evolving landscape suggests a likely future of cooperation between AI innovators and cybersecurity firms to counter increasingly sophisticated cyber risks.

This article was reported by synthesizing coverage from multiple independent news outlets to present a balanced, unbiased account. Read about our editorial standards. Spotted an error? Let us know.