.png)
For a long time, the volume of traffic across an organization was small enough that individual files or clusters of servers could be moved relatively slowly through the process of deployment. However, once infrastructure as code (IaC) started to become a significant factor in cloud computing, many developers were able to provision entire production environments through pull requests much more quickly than most security processes were designed to allow. Now, many engineering departments feel the strain of the constant tension between getting product out the door and maintaining security.
One of the major contributing factors to this tension is that many mistakes made during the IaC process appear small at first. However, when you accumulate these "little things," they become extremely dangerous in clouds. Additionally, when remediation relies solely on a human being to review alerts, create help desk tickets, or discuss responsibilities via Slack channels, security has become a time-consuming task, thus resulting in operational drag.
For these reasons, there has been a great deal of discussion surrounding automated remediation for IaC. Companies are not looking to "hype" automation for the sake of automation; they are instead realizing that they cannot continue to perform manual remediation at scale.
Why IaC Security Bottlenecks Happen
In CI/CD, most security bottlenecks are operational issues disguised as security problems. Development teams receive floods of scanner alerts, many of which are repetitive, some irrelevant, and the developers eventually stop treating them as urgent. I have seen repositories where findings continue to exist for months without anyone having time to check if the finding is a true risk versus just another noisy policy engine-generated alert. Once fatigue sets in, security technology may technically exist but it will no longer impact the developer’s behavior in a positive manner.
Typically, the remediation workflow is where things break down. Infrastructure code is pushed by the developer, flagged by the scanner, reviewed manually by a security engineer, and changes are returned to the engineering queue after the deployment context has deleted itself. Pull requests are delayed, releases accumulate, and security reviews become viewed by the developer as a bureaucratic process rather than a collaborative safeguard. Over time, significant developer productivity loss, increased security backlog, and decreased release velocity will occur and be masked from leadership dashboards.
The Limitations of Traditional IaC Scanning Tools
Early on in the use of traditional IaC scanning tools, organizations were able to identify cloud risks much earlier in the development lifecycle, which was critical. However, once they introduced scanning tools, they only provided detection capabilities. In other words, developers were informed regarding how insecure something was, without being provided much help on what to do next. Engineers were still left to research how to fix things via documentation, compare example policies, manually test things, and hope they didn’t break their infrastructure while resolving security concerns. This was manageable at a small scale, but when scaling to an enterprise-sized organization, this became very labor-intensive and exhausting.
As a result, alert fatigue becomes amplified as developers will be continually receiving the same type of alerts across many different projects. After receiving several repeated alerts, developers tend to ignore or postpone responses to alerts until compliance deadlines start forcing them to act. Typically, this is when security teams begin to get labelled as organizational blockers to deployment and therefore require much more effort get approvals for, not because security itself is overly complicated, but because the process for their employees to remediate is extremely inefficient and does not correlate well with how employees would like to process their work actions.
What Are IaC Automation Fixes?
Automated remediation of IaC provides an additional level of support between the point of detecting an insecure configuration until the time that the insecure configuration is fixed. Automated remediation platforms can automatically create secure configuration change proposals and deliver them directly in either a pull request or automated CI/CD workflow. Thus, developers do not have to start from scratch each time a vulnerability is identified by a scanner, because proposed changes conform to the organization's established security policy.
Most of the types of issues that can be resolved with automation are the repetitive ones that consume a lot of operational time. Misconfigured IAM permissions, exposing public cloud storage, improper network rules/firewall settings, missing encryption configurations and/or failure to meet compliance standards are some of the most common examples of issues that can be remediated in a deterministic manner. Additionally, the more sophisticated remediation platforms also take into consideration the contextual information about the infrastructure and do not just rewrite code without regard for context. This is crucial for building confidence in remediation solutions, as some engineers will not trust remediation platforms that introduce system instabilities so that compliance with security controls can occur.
How IaC Automation Fixes Reduce Security Bottlenecks
Automated remediation allows developers to immediately create remediations for issues detected by automating the entire review cycle. This enables developers to add secure changes into their own workflows as opposed to relying on their security engineering teams to tell them how to remediate secure configurations in their infrastructure. As a result, mean time to remediation will decrease at an accelerated pace because the time-consuming research and validation processes will no longer be completed manually.
In addition to speed, developers being able to self-service their own remediation efforts represents a major cultural change. Rather than being thought of as an external auditor, security will now be an integrated part of engineering workflows. Vulnerable configurations will be remediated prior to deployment into production, the frequency of excessive alerts will reduce since the alerts would all become actionable, and collaboration between DevOps and security teams will be improved since both groups will be working out of the same integrated workflow versus working out of two separate ticket queues.
Real-World Example Workflow
A common occurrence is that a cloud bucket is publicly accessible due to an improperly configured Terraform deployment. In most cases, an IaC scanner will identify the project and block the pull request until developers and security teams can coordinate a manual remediation process. Depending on how quickly the organization responds, this process will take anywhere from several hours to several days, particularly if the affected deployment has production infrastructure or is in a regulated environment.
With automation, the remediation workflow changes completely. The scanner detects the exposure and the remediation engine automatically generates a compliant configuration update that is applied to the pull request (pull request includes secure fix). The developer can then look at the changes, verify that functionality still works, and merge it seamlessly with minimal disruption. What once was a constrained deployment will now be a relatively straightforward and more streamlined review process with significantly less operational overhead.
Best Practices for Implementing IaC Automation Fixes
Successful Teams are using the CI/CD (Continuous Integration/Continuous Delivery) Process to integrate early remediation practices into their workflow rather than treating it as a checklist item at the end of the process. When remediation workflows occur pre-merge/integration, the insecure configurations are never allowed deep into the process, which eventually prevents them from impacting a production release. In addition, for organizations utilizing GitOps methods, insecure configurations are remediated prior to being merged/integrated since all infrastructure changes have gone through an approved version-controlled process; therefore, any integrations that occur will be able to be automated seamlessly.
Furthermore, it is essential to have a policy-driven and transparent remediation process. Developers will need visibility into what created the fixes and how these fixes meet the security needs of the organization. Although fully automated remediation may sound appealing in theory; however, most teams today still want human approval before the merging/integration of infrastructure changes. Most successful organizations use automation as a support mechanism to make engineering decisions rather than completely replacing the judgement of the engineers.
Future of DevOps Security Automation
The next stage of IaC remediation will be a major shift towards using AI to assist with security operations. This does not mean that “AI will replace DevOps teams” as has been promoted, but that new systems will have a much better understanding of the context surrounding their infrastructure. Remediation engines will analyze workload characteristics, identify dependencies and deployment intentions in addition to simply matching against static rules before presenting possible fixes. This change is meaningful because traditional remediation logic is too simplistic to keep up with the increasingly dynamic nature of cloud environments.
Over time, we should expect autonomous remediation pipelines to become commonplace for solving routine infrastructure issues. Continuous enforcement of policies, self-healing cloud configurations and runtime correction techniques are being developed in established cloud security programs. Organizations that can adapt rapidly don’t necessarily have the greatest number of alerts or the largest security teams; instead, these organizations will be able to manage their infrastructure risk quickly while maintaining a high level of engineering efficiency.
Conclusion
IaC automation fixes tackle one of the modern DevOps' most unfortunate realities: security remediation workflows that cannot scale with deployment speed. By automatically synthesizing deterministic, policy-aligned fixes in developer workflows, organizations decrease manual remediation investment, increase deployment velocity, and augment cloud security posture simultaneously. The security problem starts becoming less of a bottleneck during the release and more of an integrated engineering capability.
Platforms including Gomboc are built expressly around this idea. Gomboc helps organizations automatically remediate IaC and cloud runtime problems while lessening alert fatigue, consistently enforcing secure configurations, and maintaining DevOps velocity without locking teams into a constantly cyclical sequence of remediations. And quite honestly, that's probably where cloud security should go next — from overwhelming teams with alerts to, instead, helping them resolve issues before those issues escalate into full-blown incidents.
