For as long as vulnerability management has existed, security teams have been fighting a race against time to patch, remediate, and reduce risk. The AI revolution has amplified those challenges, increasing both the volume of vulnerabilities practitioners have to contend with and the speed at which attackers can identify, weaponize, and exploit them.
The Forum of Incident Response and Security Teams (FIRST) recently reported that actual CVE disclosures were running 46.3% above projections made just four months earlier. And while the growing volume of vulnerabilities is concerning enough on its own, what’s most alarming is the frequency of attacker exploitation. Verizon's 2026 Data Breach Investigations Report found that exploitation of vulnerabilities accounted for 32% of initial access vectors in observed breaches and noted that the trend continues to rise. Trinity Cyber's mid-year analysis of key vulnerability trends reached a similar conclusion: attackers are increasingly weaponizing new CVEs within hours of disclosure, and well before most organizations have an opportunity to patch.
These findings point to what can only be described as a vulnerability tsunami. As AI accelerates the creation and discovery of vulnerabilities, overburdened security teams will face even greater workloads and shrinking response windows as attackers move faster to exploit weaknesses.
Development teams are embracing AI to produce code more quickly, shorten release cycles, and deliver new capabilities faster. While the productivity benefits are undeniable, they come with security implications. Veracode recently reported that AI-generated code introduced security flaws in 45% of coding tasks tested. As organizations use AI to write more code, they are introducing increased risk of insecure code and vulnerabilities reaching production.
AI is not only creating vulnerable code, it is also accelerating how we identify vulnerabilities at an unprecedented scale. Anthropic's Project Glasswing initiative recently reported identifying more than 10,000 high and critical severity vulnerabilities using AI-assisted analysis. The same technology that is helping developers move faster is also helping researchers and attackers find weaknesses at an increased pace.
Historically, vulnerability discovery required significant time, expertise, and manual effort. AI is changing that equation. Researchers can now analyze software more efficiently, uncover weaknesses faster, and identify previously overlooked exposures at scale.
And these gains are not limited to defenders – threat actors now have access to many of the same technologies, allowing them to identify vulnerable targets, prioritize exploitation opportunities, and accelerate attack development.
While AI isn’t making patching obsolete, it is exposing its limitations. The faster vulnerabilities are created and discovered, the harder it becomes to rely on patching as the primary means of risk reduction. In the age of AI, security teams are being asked to remediate at human speed while vulnerability discovery and attacker activity increasingly moves at machine speed.
That imbalance makes patching alone insufficient and is why virtual patching is gaining renewed attention as a compensating control to address the influx of vulnerabilities.
Since our inception, Trinity Cyber has taken a different approach that enables efficient and accurate virtual patching. Our platform prevents exploitation and stops malicious content before attack can reach their targets.
As the industry weathers the vulnerability tsunami, reducing dependence on vulnerability management may prove to be one of the most important advantages an organization can have. The question for security leaders is no longer whether vulnerabilities will exist in their environment. It is how much risk remains while they are waiting to patch them.
Want to see how Trinity Cyber stops threats before they reach your environment? Book a demo to see see it live today.