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Ask Google AICyber threats have only become more sophisticated over time, and companies are now discovering more vulnerabilities than ever. For instance, the Common Vulnerabilities and Exposures (CVE) database now tracks tens of thousands of new vulnerabilities annually, and no company has the resources to patch all of them.
The conventional approach of scanning and patching entire systems no longer holds water. Companies clinging to this model are taking on more risk, not less. Instead, vulnerability management has evolved into active, continuous risk management programs, supercharged by AI. How does vulnerability management work in 2026, and how can your company adapt to this evolution? This guide answers these questions.
What is vulnerability management?
Vulnerability management is an organization’s constant process of identifying, classifying, prioritizing, and countering cyber threats in its IT infrastructure. The aim is to prevent attackers from leveraging vulnerabilities to cause major damage to your business.
An exploited cyber threat can cause massive damage, like a ransomware attack that shut down the largest refined oil products pipeline and triggered gas shortages on the U.S. East Coast in 2021, so vulnerability management isn’t just everyday IT hygiene, but a critical part of managing business risk.
Managing vulnerabilities isn’t confined to typical software vulnerabilities that you’ll find listed in the Common Vulnerabilities and Exposures (CVE) database. It also means assessing internal IT systems for network misconfigurations, weak passwords, insecure design patterns, and third-party integration risks, as hackers can also leverage these to cause damage.
Vulnerability management is never complete. Rather, it evolves as your company runs its operations. The cyber threat landscape frequently changes, with AI as a driving force, so companies should always be on guard.
The vulnerability management lifecycle: Five stages
Here’s a clear process your company can follow to manage vulnerabilities:
Stage 1: Discovery
It starts with curating all IT assets in your organization, from virtual machines to physical servers, routers, switches, proprietary databases, and more. After all, you can only manage vulnerabilities in assets that you know exist.
After curating all IT assets, you’ll scan them for vulnerabilities using cybersecurity tools. These tools apply rule-based algorithms, artificial intelligence (AI), and machine learning (ML) to sniff out sneaky vulnerabilities lurking in IT infrastructure.
Stage 2: Assessment
After discovering vulnerabilities, you need to evaluate them by severity. Your organization can’t realistically patch all vulnerabilities, so focus on the ones that could cause the most damage.
The Common Vulnerability Scoring System (CVSS) helps security experts measure severity. The Exploit Prediction Scoring System (EPSS) is another scoring system, based on a machine learning model analyzing whether a vulnerability will be exploited within the next 30 days. You can also assess potential business impact from a vulnerability, then use that to prioritize fixes.
Stage 3: Prioritization
Prioritize the vulnerabilities that you’ll patch immediately. Here, it isn’t just about CVSS and EPSS scores, but also prioritizing based on business risk. For example, a risk may have a lower CVSS score, but because it's identified in a user-facing, business-critical system, prioritize it over a higher-score vulnerability in an air-gapped, non-user-facing system.
Suppose you run an e-commerce marketplace. A vulnerability that can affect the pricing system should get more priority than one affecting an internal database that displays ‘Related Products,’ even if the latter has a higher CVSS score. This should be the case because a bug in the pricing system shuts down the whole e-commerce operation, but your marketplace can still sell products despite a bug in the Related Products recommendation system.
Stage 4: Remediation
At this point, apply the required fixes to the software bugs with the highest priorities. Install patches or change configurations where needed to fix bugs. For vulnerabilities that you can’t immediately remediate, document the accepted risk and deploy some interim measures to prevent issues from escalating. Yet, they’ll need to be fixed in due time.
Stage 5: Verification
Verify the remediation measures deployed above. Rescan the IT assets and ensure the same vulnerabilities don't appear again.
Also, your company should track key cyber metrics like mean-time-to-detect (MTTD), remediation rates, and mean-time-to-remediate (MTTR). These metrics measure how effective your vulnerability management processes are.
The evolution to risk-based vulnerability management
Vulnerability management has largely shifted from compliance-driven patching to genuine business risk reduction. It isn’t just about fixing bugs with the highest CVSS scores, but now leans more on fixing bugs that can have the highest impact if exploited.
For example, a food delivery app should prioritize an identified vulnerability that can affect customer checkout flows, even if another bug affecting the customer review system has a higher CVSS score. Companies that focus solely on CVSS scores often end up patching low-risk vulnerabilities first, while neglecting high-risk ones.
When prioritizing vulnerabilities to fix, ask key questions like:
- Is the vulnerability actively exploited by malicious actors? (Active ones should be prioritized).
- How critical is the asset in which the vulnerability has been identified? (User-facing assets should get higher priority than internal-facing ones).
- Are other mitigations already in place to manage the vulnerability? (Focus more on vulnerabilities without active mitigations).
The Exploit Prediction Scoring System (EPSS), an ML model that predicts the likelihood of a vulnerability being exploited within 30 days, provides a more complete prioritization signal compared to the Common Vulnerability Scoring System (CVSS) alone. Focus your threat mitigation efforts on vulnerabilities that could cause the most immediate harm.
Continuous vulnerability management: Why periodic scanning isn’t enough
We’ve emphasized that vulnerability management has become a never-ending process, owing to the increased sophistication of cyber threats. Gone are the days of quarterly or monthly scans to tick compliance boxes. IT assets must now be scanned constantly to detect new vulnerabilities.
The main issue with periodic scans is that new vulnerabilities are disclosed in cycles, and within each cycle, the new bug may have caused problems before a scheduled monthly or quarterly scan.
For example, Cisco, the popular networking gear manufacturer, recently disclosed a vulnerability that could let hackers exploit its firewall software to crash devices. The bug, labeled CVE-2026-20349, “could allow an unauthenticated, remote attacker to cause the device to reload unexpectedly, resulting in a denial of service (DoS) condition,” Cisco said. Unfortunately, several organizations had been affected before Cisco deployed a fix. Yet, with active, constant scanning, many companies identified and mitigated the issue before Cisco’s official fix.
Another example is CVE-2026-50751, an authentication bypass vulnerability identified in Check Point, a cybersecurity platform. Attackers leveraged this vulnerability to establish remote access VPN sessions on various corporate networks without providing a valid password. Unfortunately, this flaw was exploited significantly before Check Point formally disclosed it and issued a patch. That a cybersecurity platform like Check Point is exposed to threats shows just how seriously companies should take vulnerability management.
Use agent-based scanning to identify vulnerabilities on endpoint devices and agentless scanning for cloud-based IT assets. The latter connects directly to cloud assets via APIs, allowing you to run continuous risk-based vulnerability management tools without disrupting usage.
Your developers should adopt vulnerability scanning into their workflows. It should be deeply integrated into the CI/CD software development pipeline, with systems rigorously scanned before deployment, not after.
Keep tabs on your mean-time-to-remediate (MTTR), as this metric indicates how effective your vulnerability management process is. The aim is not just to discover bugs but to address them quickly. MTTR for critical vulnerabilities should be in hours, not weeks that give malicious actors openings to exploit them.
How AI is changing vulnerability management
We’ve hinted at applying AI and ML in discovering and fixing cyber vulnerabilities. AI indeed has made a quantifiable impact in this field. For instance, AI models trained on large swathes of threat intelligence help identify vulnerabilities in your IT assets. Predictive modeling then ranks these vulnerabilities based on which are more likely to be exploited.
AI models have reduced false positive rates from automated cybersecurity tools. These tools have become much more accurate, enabling security teams to focus remediation efforts on vulnerabilities with the highest business risks.
It’s one thing to discover a vulnerability and another to know how it could be exploited and what damage it can cause. AI systems provide valuable help by modelling how an attacker can leverage a single vulnerability to steal data, or even chain multiple low-severity vulnerabilities together to achieve much more. These are attack paths that traditional prioritization methods, based on severity, can easily miss.
How Sangfor approaches vulnerability management
We’ve advised extensively on vulnerability management best practices. But which platform can companies adopt to accurately discover, assess, prioritize, and patch cyber vulnerabilities? Sangfor is the ideal solution for large enterprises.
While Sangfor's Athena Next-Generation Firewall (NGFW), Endpoint Protection Platform (EPP), and Network Detection and Response (NDR) do not replace a dedicated vulnerability scanning tool, they work together to reduce the window of exposure between vulnerability disclosure and remediation, by blocking known exploit attempts, detecting anomalous behavior tied to unpatched systems, and giving security teams real-world context to prioritize which vulnerabilities pose the greatest active risk.
The Athena Next-Generation Firewall (NGFW) sits in front of your IT assets. It is designed to protect network perimeters across on-premises, cloud, and hybrid environments, using AI-based detection to identify threat patterns that signature-based methods may miss.
The Athena Endpoint Protection Platform (EPP) provides foundational security for your IT assets. It combines next-generation antivirus (NGAV) and endpoint detection and response (EDR) capabilities into a single solution that protects every endpoint across your IT environment.
Sangfor’s Athena Network Detection and Response (NDR) system continuously analyzes network traffic to flag anomalies that may indicate exploitation of an unpatched vulnerability, helping security teams respond before a known weakness turns into a breach. Automated responses prevent threats from escalating into business risks. Working together with the firewall and the endpoint protection platform, the NDR system facilitates vulnerability management for critical IT assets.
Want to run cloud-based assets securely without stress? Sangfor Cloud Platform (SCP) enables that. This Hyper-Converged Infrastructure (HCI) solution unifies compute, networking, distributed storage, and security into one platform, simplifying operations for your IT team.
As licensing changes following Broadcom's acquisition of VMware prompt many enterprises to re-evaluate their virtualization strategy, the Sangfor Cloud Migration Tool (SCMT) is designed to make that transition to Sangfor Cloud Platform less disruptive assessing VMware workloads for compatibility up front and migrating data while source machines remain operational. VMware workloads are first assessed for compatibility, then you’ll connect SCMT directly to VMware vCenter via APIs to sync data in the background while the source machines remain in operation.
Post-migration, Sangfor automatically injects the required performance drivers and maps vCPU/vRAM configurations to their equivalent Sangfor resources to optimize compatibility. Sangfor offers one of the most effective VMware alternatives.
Frequently asked questions
It’s the continuous process of discovering, assessing, prioritizing, and fixing cyber vulnerabilities in your IT assets. This process prioritizes fixing vulnerabilities that pose the highest business risks.
Vulnerability scanning is a specific action that identifies threats in IT assets, while management is the broad, never-ending process of identifying, prioritizing, and fixing these threats. Scanning only discovers bugs, but management is how these bugs get fixed.
It’s a cybersecurity strategy that prioritizes threats based on the business risks they pose, not just CVSS scores. Instead of treating every cyber threat equally, companies prioritize those that could cause the most immediate damage.
Vulnerability scanning should be a constant process, not periodic. The increased sophistication of cyber threats has made continuous scanning a must-do, or you risk neglecting sneaky bugs that cause major damage later.
AI agents now scan IT assets and identify threats more accurately, particularly the sneaky ones that aren't known in malware databases. AI models also predict how attackers could leverage specific vulnerabilities to break into IT assets, letting you know which vulnerabilities to prioritize for immediate fixing.
