Redefining Exploitability: Is AI Changing the Rules of Vulnerability Management?
AI is changing how we determine which vulnerabilities pose the greatest risk.
For years, cybersecurity teams have faced the same fundamental challenge: more vulnerabilities than they have the resources to remediate.
The solution has been prioritization. Initially, organizations relied heavily on CVSS severity scores. Then as organizations’ security programs matured, most vulnerability management programs recognized that severity alone doesn't determine risk. At Pillar, we consider vulnerability severity alongside evidence of active exploitation, threats targeting a client's industry, and the practical exploitability of a weakness. This provides a more informed view of which vulnerabilities warrant attention.
Now AI is introducing a new variable into that equation.
AI Is Changing the Economics of Exploitation
Historically, exploiting certain vulnerabilities required significant technical expertise, time, and effort. Those barriers influenced which vulnerabilities attackers pursued.
AI is lowering those barriers.
Attackers can increasingly use AI to accelerate vulnerability analysis, assist with exploit development and identify opportunities to chain weaknesses together. A vulnerability that previously offered little value on its own may become useful as part of a broader attack path.
Consider a low-severity vulnerability that exposes information about an internal system. On its own, the impact may be minimal. Combined with another weakness, however, that information could help an attacker move laterally, escalate privileges, or reach a critical business application.
The individual vulnerabilities haven't necessarily become more severe. What's changing is the attacker's ability to turn them into something consequential.
This raises an important question: Is our current methodology for exploitability keeping pace with what AI is enabling attackers to do?
Exploitability Needs a More Dynamic Definition
Risk-based vulnerability management isn't new. But AI is forcing us to expand how we think about exploitability.
It's no longer sufficient to evaluate whether a vulnerability has a known exploit or whether it's being actively exploited today. We also need to consider how emerging capabilities could change its attractiveness to attackers tomorrow.
That means continuously evaluating five interconnected factors:
Real-world exploitation: Is the vulnerability actively being exploited? What does current threat intelligence tell us about attacker activity?
Industry-specific threats: Are attackers targeting this vulnerability in our industry? Is it particularly relevant to the systems and technologies our organization depends on?
Accessibility and exposure: How easily could an attacker reach the affected system, and what controls stand in their way?
Attack-path potential: Could this vulnerability be combined with other weaknesses to compromise more valuable systems or data?
Evolving exploitability: Are AI-assisted techniques or new attack tools reducing the expertise, time, or effort required to exploit this weakness?
CVSS scores, EPSS, CISA's Known Exploited Vulnerabilities catalog, and industry-specific threat intelligence remain important inputs.
What's evolving is how we interpret those scores and weigh them against increasingly sophisticated attacker capabilities.
A vulnerability that represented an acceptable risk yesterday may warrant a different priority today...not because its severity changed, but because the attacker's ability to exploit it did.
Finding Vulnerabilities Is Only Half the Battle
There's another dimension to this challenge that deserves attention: operational capacity.
As AI changes the speed and sophistication of attacks, organizations need to consider whether their security operations can keep pace.
If you're managing cybersecurity internally, your team is responsible for identifying vulnerabilities, assessing risk, monitoring changes in exploitability, prioritizing remediation, and ensuring the necessary fixes are implemented. For many mid-market organizations, that's a significant burden on already stretched
IT and security teams.
If you're working with a managed security provider, the question becomes: Does your managed security service include continuous vulnerability management and automated remediation?
Not all managed security services do.
Managed detection and response is important, but identifying and responding to malicious activity is different from proactively eliminating vulnerabilities before they're exploited.
Organizations with integrated vulnerability management, threat intelligence, and automated remediation capabilities are better positioned to respond as today’s ever-changing AI-powered threat landscape evolves. Automation can accelerate routine remediation, allowing security teams to focus on more complex risks that require human judgment and careful change management.
The real advantage of Managed Security isn't simply identifying vulnerabilities faster. It's having the capability to act on the right ones before attackers do.
Rethinking the Vulnerability Management Playbook
Risk-based vulnerability management has always been about making informed decisions with limited resources. AI isn't changing that fundamental objective. But it is changing the assumptions behind those decisions.
We can no longer evaluate exploitability as though attacker capabilities are relatively static. AI-assisted vulnerability discovery, exploit development, and attack-path analysis are introducing new considerations into an already complex process.
Even mature vulnerability management programs need to continuously reassess which vulnerabilities represent the greatest risk and whether their remediation capabilities can keep pace.
And let’s talk about how we measure success...Closing hundreds of critical vulnerabilities may demonstrate progress, but it doesn't necessarily tell us how much risk we've reduced. Eliminating a handful of viable attack paths to critical business systems may deliver substantially greater protection.
Finding and fixing everything is NOT vulnerability management. Knowing what matters, understanding how attackers can exploit it, and having the capabilities to eliminate those exposures before they become incidents is how we master vulnerability management today.
AI is changing what attackers can accomplish. Our approach to assessing exploitability, and our ability to act on that assessment, must evolve with it.
