RapidFort Introduces Runtime Profiling to Shrink Container Attack Surfaces
RapidFort's new runtime container profiling tool analyzes actual container usage to identify and remove unnecessary components, reducing the attack surface without disrupting applications.
The persistent challenge of container security often lies not in identifying vulnerabilities, but in effectively mitigating them. A common issue is that standard container images, even those from trusted sources like NGINX, can come pre-loaded with hundreds of categorized vulnerabilities stemming from unused operating system packages, development tools, and libraries. While vulnerability scanners highlight these issues, they fail to indicate which components are actually executed by the application, making it difficult to determine safe removal.
Traditional approaches to reducing this attack surface have relied on manual inspection by developers. This method is labor-intensive, difficult to scale, and prone to errors, especially when personnel change. Furthermore, a component that appears unnecessary during a static review might be critical under specific load conditions or during less common operational paths. Removing such a component could lead to costly application outages, negating the security benefits.
RapidFort's new approach shifts from guesswork to behavior-aware hardening by distinguishing between what is installed and what is executed. While a Software Bill of Materials (SBOM) lists all installed components, a Runtime Bill of Materials (RBOM) captures the software components observed in use when a container is running. This distinction is crucial for making informed decisions about hardening an image based on observed behavior, complementing the inventory and compliance data provided by an SBOM.
The company proposes a three-stage repeatable hardening process: profile, harden, and validate. The profiling stage involves observing the workload under representative conditions, including functional tests, staging traffic, and stress testing, to create a credible baseline of executed components and configurations. This baseline then guides the hardening process.
In the hardening stage, the baseline is used to identify and remove components not observed during profiling. Organizations can tailor the intensity of removal based on the service's risk profile, ranging from removing all unused components to focusing only on unused packages with known vulnerabilities. An explicit 'keep' or override list is also essential for retaining necessary components that might not have been observed during the profiling phase.
Finally, the validation stage is critical. The hardened image must be rigorously tested to ensure it functions identically to the original. This validation should serve as a release gate, with any failures requiring investigation and resolution before the image is promoted. Feedback from validation should also inform future profiling iterations, creating a continuous improvement loop.
By automating this profiling, hardening, and validation process within CI/CD pipelines, organizations can achieve scalable and repeatable container security. This automation can flag changes in component usage, such as new components being introduced or previously used ones disappearing, for review. However, human oversight remains vital for setting removal intensity, managing exceptions, and approving releases, ensuring that security decisions align with operational context and risk tolerance.
The ultimate goal is to create secure container images that contain only what the workload needs, and no more than can be safely justified. This evidence-based, continuously validated approach to reducing unnecessary software offers a more meaningful security improvement than simply accumulating vulnerability reports.