Industry executives and experts share their predictions for 2026. Read them in this 18th annual VMblog.com series exclusive.
By Gene Moody, Field CTO, Action1
New year, new issues.
As we move into 2026, the landscape of vulnerabilities is changing in ways that traditional security models are having a hard time keeping up with. Attack timelines are getting shorter, AI is adding new attack surfaces that haven’t been tested, and identity-driven access is now the go-to method for malicious actors. These predictions show how vulnerability management, prioritization, and response will have to change as theoretical risk turns into real, exploit-driven exposure.
Prompt injection becomes a top enterprise attack vector
In 2026, prompt injection will become one of the most common enterprise attack pathways as attackers exploit the rapid, untested spread of embedded AI. In 2025, many vendors integrated AI models quickly to stay competitive, but few evaluated how those models behave when exposed to crafted inputs, noisy data sources, or interconnected workflows. Once these AI models went live, attackers were able to quickly exploit them to influence outputs in ways that bypass traditional controls, trigger unintended actions, or leak sensitive information. Organizations in 2026 will begin to treat model behavior as an exposed interface with the newfound knowledge that untested AI logic represents a significant (and often invisible) attack surface.
Business-context scoring replaces CVSS as the primary method of prioritization
Organizations enter 2026 deeply aware that CVSS alone produces noisy prioritization and wastes limited remediation capacity. Security teams will increasingly shift toward contextual scoring models that account for exploitability, asset criticality, user access patterns, and operational impact. This change will be driven by the growing realization that high-severity weaknesses on low-value systems often pose minimal danger, while modest vulnerabilities on critical assets can be far more damaging. By mid-year, more enterprises will anchor prioritization to business value rather than theoretical severity, leading to faster, more defensible remediation paths and clearer alignment between security operations and organizational risk tolerance.
Enterprises adopt sovereign vulnerability intelligence as confidence in legacy feeds declines
Throughout 2026, enterprises will expand beyond monolithic vulnerability databases as delays, gaps, and inconsistencies undermine confidence in legacy sources. Governments and industry groups will accelerate the release of sovereign vulnerability repositories that reflect real-world software usage and localized threat activity. These specialized feeds will offer far more relevant intelligence for organization whose environments differ from global averages. At the same time, security teams will increasingly combine multiple sources of vulnerability intelligence to create a richer, more accurate view of risk. As these repositories mature, enterprises benefit from intelligence that is timelier, more contextual, and better aligned with the vulnerabilities that actually exist in their own technology stacks.
Exploitability metrics surpass severity metrics in board-level reporting
Boards will spend 2026 prioritizing what attackers are likely to exploit rather than what scores highest on a severity chart. Executives will grow frustrated with reports that fail to explain real exposure and will push security leaders to quantify which weaknesses are 1) most attractive to malicious actors, 2) how quickly exploits could appear, and 3) which systems carry the greatest business impact. As a result, exploitability models, historical attacker behavior, and exposure-based insights will replace CVSS as the primary language of risk. This shift will drive enterprises to focus on vulnerabilities that pose practical danger rather than theoretical severity, reshaping how organizations allocate time, budget, and attention.
Exploit velocity surpasses enterprise response capacity
By 2026, the compression between vulnerability disclosure and active exploitation will reach a tipping point where traditional patching processes simply cannot keep pace. Automated exploit development, AI-assisted code review, and the commercialization of zero-days will shrink the reaction window to hours, leaving organizations exposed even when they believe they are acting quickly. The result will be widespread recognition that quarterly or even monthly patch cycles are relics of a slower era. Enterprises will enter 2026 forced to adopt continuous patch intelligence, probability-driven ranking models, and strict policy frameworks that dictate how patches are evaluated and deployed based on business-critical context rather than static severity scores.
Credential compromise becomes the backbone of the cybercrime economy
The surge in infostealer malware from 2023 through 2025 created a mature, self-sustaining trade in credentials, tokens, and identity artifacts. That ecosystem will harden in 2026 as access brokers refine pricing models, expand automation, and integrate with other criminal marketplaces. The sheer volume of harvested identities will make credential misuse one of the most dependable revenue streams for attackers. Enterprises will confront the uncomfortable truth that any system lacking enforced MFA represents an active liability and that password-only access is indistinguishable from exposure. Success in 2026 will hinge on raising identity hygiene standards, enforcing strong MFA everywhere, and conducting continuous monitoring for leaked credentials across public and private channels.
Nation-state activity becomes indistinguishable from criminal operations
Over the past three years, geopolitical tensions turned state-backed cyber operations into a constant background presence rather than episodic disruptions. In 2026, this blending of capabilities, infrastructure, and tooling will make attribution harder than ever, and many enterprises will struggle to distinguish targeted espionage from pervasive criminal noise. The overlap in tradecraft will mean that even routine intrusions could have strategic intentions behind them. Organizations operating in critical sectors such as government, utilities, financial services, and civil infrastructure will be compelled to integrate geopolitical risk into operational security planning. Threat intelligence programs will shift toward understanding regional targeting patterns and anticipating long-horizon campaigns rather than reacting to short-term events.
Shadow AI triggers a new class of unmanaged enterprise risk
As AI adoption surged from 2023 to 2025, teams across the enterprise quietly deployed private or third-party LLMs outside official oversight. By 2026, these “shadow models” will represent a significant and largely invisible attack surface, introducing unmonitored data flows, unknown training retention, and inconsistent access controls. Many organizations will discover that sensitive information is already circulating through unapproved AI systems, creating compliance gaps and persistent leakage channels. The proliferation of these unsanctioned models will push enterprises to mandate registration of any AI workflow touching corporate data, impose governance over model endpoints, and offer approved, hardened alternatives to prevent teams from pursuing unsupervised experimentation.
There’s a common thread across these trends: speed and context matter more than ever. Teams that align their vulnerability management programs with how attacks actually unfold in the real world will have a much better chance of reducing meaningful risk in 2026.
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ABOUT THE AUTHOR
Gene is Field CTO for Action1, where he engages with industry leaders and customers worldwide, advocating for modernizing patch management and evolving security standards, while showcasing how Action1 empowers organizations to achieve stronger resilience and compliance. With 30 years in IT, Gene has worked across development, system administration, consulting, management, and security in organizations ranging from small teams to global enterprises. He specializes in translating complex technical challenges into clear, actionable guidance for both technical teams and executives. Known for analytical problem-solving and strategic planning, Gene excels at breaking large, high-stakes problems into manageable components and guiding teams to successful execution.
