The Rise of AI and Its’ Impact on Vulnerability Management
- James "Chilli" Chillingworth
- Oct 21
- 4 min read
AI is accelerating both the scale and sophistication of cyberattacks, making traditional vulnerability management tools and processes insufficient without strategic upgrades. This blog explores how you can adapt to the new threat landscape.
Artificial Intelligence is no longer just a tool for defenders - it’s now a weapon in the hands of attackers. In 2025, AI-powered exploits have reshaped the vulnerability landscape, enabling threat actors to discover, prioritize, and weaponize vulnerabilities faster than most organizations can respond.
I attended the Information Systems Security Association event in Santa Monica California on September 10th and 11th. It was a great event with a lot of discussion about Artificial Intelligence – both good and bad, but it is obvious that there will be many threats generated using AI maliciously. Attackers now use GenAI and agentic AI to surface vulnerabilities faster than defenders can patch them and AI agents can autonomously scan, exploit, and pivot across systems.
I spoke with my fellow Cybersecurity Professional, Mikael Vinding, CISO at AP Technology, who mentioned “AI is changing the cybersecurity landscape in multiple ways. Attackers are using it to accelerate reconnaissance, exploitation, and social engineering. At the same time, organizations implementing AI internally face new risks including misconfigurations, blind spots, and unintended exposures.” He went on to say that “Vulnerability and exposure management platforms are no longer just table stakes - they must evolve. With AI driving both the scale of attacks and the speed at which they unfold, these platforms will need to integrate AI-driven detection, prioritization, and remediation to keep pace. Static approaches won’t be enough; continuous, intelligent adaptation will be the new baseline.”
He's not wrong - according to the World Economic Forum’s Global Cybersecurity Outlook, the average number of weekly cyberattacks per organization has more than doubled since 2021, with AI agents playing a central role in this surge. But, 74% of security leaders now cite vulnerability and risk management as the top area where AI can deliver value.
How AI Exploits Play Out
You may have already heard some of the “scary” stories - an AI-driven botnet scans and exploits a misconfigured authentication endpoint within hours of a new web app going live. A deepfake video of a company CTO triggers unauthorized access changes, which are then used to chain together known vulnerabilities for full system compromise. A threat actor uses AI to cross-reference public CVEs with exposed assets on Shodan, launching targeted exploits before the organization’s weekly scan even begins. These attacks are fast, adaptive, and increasingly precise.
Organizational Challenges and Impacts
Whether or not an organization has a vulnerability management tool, AI-driven exploits may expose systemic weaknesses: data overload from scanners without contextual triage, slow remediation cycles that give attackers a window of opportunity, fragmented tooling that obscures visibility, and a false sense of security from basic compliance or tool deployment. Most critically, defenders often lack the hybrid skillset - cybersecurity and data science - needed to counter AI-augmented threats.
So, what is an organization to do?
Vulnerability management is becoming more complex, especially with AI now being used to accelerate attacks. Your ability to keep up will depend on your size, budget, and the cybersecurity tools and staff you have in place.
If you don’t have a dedicated vulnerability management platform, you’ll need to work with what you’ve got - manually or through other tools (check with your procurement team or other departments and then figure out a way to get proper tooling in the future). Each of these tasks may be projects by themselves, but you will need to start. Start with a solid asset inventory, tag assets by criticality, build patching workflows, and set up a monitoring schedule. Make sure EDR / MDR tools are tuned to catch exploit behavior, SIEM / SOAR rules flag lateral movement, firewall policies aren’t overly permissive, and logging is enabled across critical systems. Train your team to spot deepfakes and phishing attempts - if you’re unsure what phishing tactics to watch for, try CISA’s phishing guidance:
If you do have a platform - or the budget for one - look for AI-enhanced tools that correlate findings across sources, automate patching, simulate real-world exploits, and integrate threat intelligence feeds (check Cyrisma, Cavelo or Top Ten Vuln Softwares).
Regardless of your tooling, aim to shift from periodic scanning to continuous assessment. Align your vulnerability management efforts with business risk and build cross-functional teams that can respond quickly and effectively.
And if you don’t have the internal bandwidth to operationalize all of this, consider bringing in a third party. A good MSSP can help you align AI-related risks with compliance requirements, and implement vulnerability management workflows that match your maturity level, risk profile, and budget.
Yes, it can be done – How One Company Improved Its’ Vulnerability Management
A U.S.-based fintech firm reduced its mean time to remediation (MTTR) by 63% after deploying an AI-powered vulnerability management platform. By correlating scanner outputs with exploit intelligence and asset criticality, they cut their backlog from 2,400 findings to 180 prioritized actions. The firm also integrated automated patching for 70% of its software stack, reducing manual effort by 40%.
Although AI is making things more challenging in places, it is helping in others and yes, there is a way to minimize your risk and improve your cybersecurity!
What Now?
AI-driven exploits are not theoretical - they’re active, adaptive, and accelerating. If your vulnerability management program is still a “bit” less than desired – start with some of the actions suggested in this blog.
Not sure that you’ve got the resources to get it moving? Start with some help – reach out to us to assess your current posture and explore solutions tailored to fit your current situation (click “Contact Us” above or complete the form below).
Next Up in the Series
Prioritization of Findings and Remediations - we’ll explore why most organizations struggle to separate signal from noise, how to move beyond CVSS scores, and what it takes to build a risk-based triage process that actually reduces exposure.
Disclaimer: This article was created with some AI assistance, but edited, reviewed and fact-checked by a real person.