It’s one thing to know about CVEs that affect your business’s applications. It’s quite another, however, to go about fixing CVEs quickly, particularly in cases where a CVE impacts a third-party dependency that multiple applications use.
The reason why is that the conventional approach to deploying CVE fixes is to patch each application or container image layer one-by-one. This takes time not only because installing patches can be time-consuming, but also because applications must be re-tested and re-deployed before the updated versions can go live.
In a world where the typical window for exploiting vulnerabilities has shrunk from a year to a day, this approach no longer cuts it. By the time a business has finished the processing of rolling out updates that fix CVEs, the affected applications are likely to be already under attack.
But the question facing development and security teams is: How can they update faster? And how can they ensure that their update process is scalable enough to accommodate patches that affect not just one or two apps, but dozens or hundreds?
Read on for answers as we unpack why the update process is often the weakest link in vulnerability management and what teams can do about it.
The slow, inefficient nature of application updates
The chief barrier to a more efficient vulnerability remediation process is simple enough: A single CVE often impacts multiple applications, which means a business needs to patch and redeploy each one to close its risk exposure.
That’s especially true given that up to 90% of modern codebases include third-party dependencies, and every time a security vulnerability is disclosed that impacts one of those dependencies, all of the applications need to be updated.
Hence why an organization that uses, for example, an open source library to handle authentication or logging across multiple applications would need to update each of those apps in the event that a CVE affecting the library appears.
The challenge intensifies when you consider that conventional approaches to software updates rely on an application-by-application approach. Rather than patching the affected component once and then deploying the new version across all affected applications or environments, each stack must be patched, rebuilt, retested and redeployed independently. Not only is this a slow process, but it also requires the transmission of large quantities of data in the form of updated container image layers, which can clog networks and impede the update process even further.
Matters are even worse when a patch requires updates to application code. In that case, the code must be rebuilt and tested against all of its dependencies before the updated version rolls into production.
On top of all of this is the simple issue of tracking CVEs and figuring out which ones impact your applications, a process that becomes particularly challenging when your codebase includes a number of third-party resources.
All of the above means that, no matter how good an organization is at identifying and triaging CVEs, the application update process can easily become the weakest link in its overall security. If updates take too long, exploits begin.
Modern approaches to streamlining application updates
Fortunately, it doesn’t have to be this way. Better, more efficient approaches to applying CVEs and updating applications exist.
Here’s a look at key practices or strategies for organizations to consider.
Use a common underlying platform
The more standardized a business’s application environment is, the easier it becomes to deploy updates more efficiently because a single update process can fix multiple applications.
Hence the value of adopting a shared underlying platform, such as a common base image (if you’re running all of your applications in containers), a shared runtime and/or a common hosting environment (like Kubernetes). The more consistent your hosting environment and technology stack are, the more quickly you can roll out updates.
Reuse updated application components
As noted above, the traditional approach to CVE management doesn’t include reusing patched code across applications efficiently. Typically, teams need to rebuild and redistribute all of the layers in a container image, even if they patch only part of it.
But that doesn’t mean a better approach is not possible. Developers can, and should, adopt strategies like disaggregating dependencies into discrete base layers or container images. They can then update vulnerable dependencies once, then deploy the updated version across multiple applications. This eliminates the need to update apps one-by-one. It also avoids having to rebuild and redeploy each layer individually.
This strategy becomes even easier for organizations that use orchestrators like Kubernetes, which streamlines the process of replacing an older version of a container with a newer one while keeping other parts of the application (those within the pod) unaffected.
Leverage intelligent buildpacks
Along similar lines, buildpacks, which automatically compile source code into executable container images or binaries, can streamline updates. This is especially true for buildpacks that support “smart” features like intelligent layer caching (meaning the ability to rebuild code without having to redownload components that haven’t changed) and that understand the semantics of building certain types of applications (which makes it possible for them to streamline application patch and update deployments).
In this way, buildpacks offer another means of updating only what needs to be updated, without wasting time rebuilding entire hosting stacks in a redundant fashion.
Take advantage of AI agents
It would be a mistake to think of AI as a panacea that can solve all application update woes. But when combined with the technologies described above, AI can help to streamline updates even more.
Specifically, developers can prompt AI agents with instructions that tell them which patch to apply and which components to change, or avoid changing. In environments where agents have access to tools like buildpacks and orchestrators, and where applications are deployed using consistent base images and runtimes, agents can strategically apply updates in ways that avoid duplicates and unnecessary rebuilds.
Conclusion: Rethinking the vulnerability update process
The practice of patching applications in response to a CVE often receives less attention than discovering or prioritizing CVEs. But it’s just as critical because, again, a CVE that is not patched quickly may as well not be patched at all, given the speed at which exploits now appear.
This is why finding ways to add efficiency and scalability to the application update process is essential. The old approach doesn’t work; modern organizations need to leverage solutions like platform standardization, buildpacks and AI to patch their applications faster than threat actors can exploit them.
SD Times Q&A
How can teams patch CVEs faster when a vulnerability affects multiple applications?
Teams can accelerate CVE patching across multiple applications by standardizing on a common base image or runtime, disaggregating shared dependencies into discrete container layers, and updating those layers once rather than rebuilding each application independently. Orchestrators like Kubernetes further simplify rolling out the updated layer across all affected workloads simultaneously.
What are buildpacks and how do they help with CVE remediation?
Buildpacks are tools that automatically compile source code into executable container images or binaries. Buildpacks that support intelligent layer caching can rebuild only the changed components of an image, avoiding redundant redownloads and full-stack rebuilds. This makes them useful for applying security patches faster and with less network overhead.
How long does it typically take attackers to exploit a newly disclosed CVE?
The window between CVE disclosure and active exploitation has narrowed significantly in recent years, with some research indicating it can be as short as one day for high-profile vulnerabilities. This makes slow, application-by-application patching processes a critical security risk.
What percentage of modern codebases contain third-party dependencies?
Industry research commonly cites figures around 80–90% of modern codebases as containing open source or third-party dependencies. Because a single vulnerable dependency can affect many applications simultaneously, this concentration dramatically increases the blast radius of any given CVE.
Can AI agents automate CVE patching in containerized environments?
AI agents can assist with CVE patching by accepting targeted instructions about which components to update and which to leave unchanged. When combined with buildpacks, container orchestrators, and consistent base images, agents can apply patches selectively — avoiding redundant rebuilds and reducing the manual effort required per vulnerability.
