Risk-Based Patch Prioritization

Patch management is fundamental to effective cybersecurity. So why are most organizations still struggling with patch prioritization and implementation?

Given the size and complexity of attack surfaces, no organization can reasonably address all vulnerabilities all the time. Patch prioritization ensures the most critical vulnerabilities are addressed first, optimizing resource use and minimizing security risks.

Yet when it comes to patch management, Ivanti’s research shows “everything is a priority.” Nearly all security professionals rate every factor listed as “moderate” or “high” urgency … but when everything is a priority, nothing is a priority.

Vendors often assign their own severity ratings to alert customers to the potential impact and urgency of newly discovered vulnerabilities. Unfortunately, there’s no industry standard associated with these ratings, so companies are left to compare and prioritize patch releases based on these isolated recommendations. On top of that, ratings are rarely updated to account for active threat context even as vulnerabilities change.

It’s no surprise then that 39% of cybersecurity professionals say they struggle to prioritize risk remediation and patch deployment, and 35% report they struggle to maintain compliance with regard to patching.

This “everything is a priority” approach is neither effective nor sustainable.

The most effective approach to patch management is risk-based prioritization, which builds on risk-based vulnerability management principles. Rather than relying solely on vendor severity ratings or basic CVSS scores, this method considers real-world factors such as exploit availability, asset importance and potential business impact.

Organizations focus their patching efforts on those vulnerabilities that pose the greatest actual threat to their specific environment. This strategic approach ensures teams address the most critical security gaps first, making better use of limited resources while strengthening overall security posture.

The majority of cybersecurity professionals (87%) lack access to critical data that can help them make informed security decisions.

If companies are to make risk-based decisions, they need access to real-time, high-fidelity data from across their entire environment, yet Ivanti’s research shows a sizable share of organizations fall short.

Ivanti's research uncovers the most common data gaps that prevent companies from making more informed security decisions:

• Visibility gaps: 45% of companies report data blind spots, such as shadow IT, which create serious challenges for security professionals monitoring their attack surface.


• Contextual gaps: 41% of companies indicate they lack contextual data about which vulnerabilities are exposing their systems to threat actors.


• Compliance gaps: More than 1 in 3 organizations (37%) report blind spots related to patch configurations, compliance status and/or meeting patch SLAs.

These gaps have serious consequences. AI and automation are often cited as solutions to improve security decision making and operational efficiency, yet data gaps severely limit AI’s ability to analyze comprehensive datasets and generate accurate insights — a major barrier to making informed, evidence-based decisions.

Siloed data, inaccessible data and missing data all contribute to ongoing, persistent data quality issues, which is a problem no AI tool can solve. In fact, 37% cite “data quality problems” as a significant barrier to using AI tools for cybersecurity.

Security professionals report widespread organizational silos between IT and security teams, driven by disconnected tech stacks and cultural divides between the two.

40% of organizations report that the different tools used by IT and security teams contribute to friction between the two groups. But this tech divide represents only part of the problem.

Ivanti’s research also points to cultural and strategic misalignments between IT and security teams that undermine decision making. More specifically, among security professionals:

• 46% believe IT teams lack urgency when addressing cybersecurity problems.


• 40% indicate IT teams don't adequately understand the organization's risk tolerance.

These misalignments are especially apparent when it comes to patch management. Security teams are often focused on rapidly testing and deploying patches to minimize the window of exposure to threats, while IT teams must balance these remediation efforts against the operational impact on business functions, such as potential downtime and productivity loss. This push-pull dynamic can lead to disagreements over patching cycles — security wants speed; IT needs stability.

Compounding the issue, the “everything is urgent” mentality can pressure IT to deploy patches before adequate testing, increasing the risk of system crashes, unplanned outages or the need to roll back updates.

The interplay of these organizational silos and misaligned priorities often leads to fragmented communication and unclear ownership of patch management responsibilities — all of which contribute to ineffective patch prioritization and increased security vulnerabilities.

Today's sophisticated threats demand continuous, proactive monitoring and remediation. AI and automation point the way forward.

AI and automation solutions offer organizations a way to fight back against sophisticated threat actors:

• Transforming prioritization: AIs synthesize massive quantities of data and analyze vulnerabilities based on the organization-wide threat context and risk context.


• Streamlining remediation: Intelligent systems automate patching workflows, which can smooth over existing operational disconnects between security and IT teams, as well as reduce costly inefficiencies in the patching process.

2025 may be the year companies are finally positioned to leverage AI. We asked security professionals, “What group will use AI more effectively in 24 months: threat actors or security teams?” More than half (53%) say security teams will use AI more effectively, compared to 21% who say threat actors will exploit it to their advantage.

Despite the widespread optimism about AI's potential to shift the advantage toward defenders, organizations must first overcome substantial regulatory, talent and financial hurdles to realize this transformative promise. Security professionals report the following:

• 48% cite regulatory and data privacy barriers.


• 46% report they lack the talent to deploy sophisticated AI-fueled technologies.


• 46% complain that the cost of AI tools limits their adoption.

It’s no wonder that fewer than half of organizations Ivanti surveyed use AI and automation for scenarios where it has proven to be highly effective: predictive IT maintenance, detecting usage / traffic anomalies and automating incident-response processes.

This report is based on a survey of over 2,400 executive leaders, IT and cybersecurity professionals conducted in October 2024. The research was administered by Ravn Research, and panelists were recruited by MSI Advanced Customer Insights. The survey results are unweighted. A more comprehensive analysis of the survey data is available in Ivanti’s full report: 2025 State of Cybersecurity: Paradigm shift.