Securing ClickHouse Deployments: How Docker Hardened Images Overcome CVE Blocks

Introduction: When Security Blocks a Perfectly Good Database

In November 2025, a team self-hosting Langfuse—an open-source LLM observability platform—on Kubernetes encountered a familiar roadblock. After uploading their ClickHouse image to AWS ECR for production, a pipeline scanner flagged three critical vulnerabilities. The catch? These CVEs weren’t in ClickHouse itself, but in the base image layers that the database never actually uses. The security team swiftly blocked the deployment, prompting the team to post on GitHub: “Our security team is not allowing us to take it to production. Please suggest alternatives” (GitHub Issue #286). This scenario is all too common in enterprise environments: a perfectly functional container gets halted not because of broken code, but because scanners find unused packages with CVEs. Days are wasted on risk exceptions, and even then, rejections stick. This article explores how Docker Hardened Images (DHI) can break that cycle, specifically for ClickHouse, one of the most pulled database images on Docker Hub.

A Quick Look at ClickHouse

ClickHouse is an open-source columnar database built for analytical workloads at massive scale. It can query billions of rows in milliseconds—something row-oriented databases struggle with. Companies like Cloudflare, Uber, and Spotify rely on it in production. With over 100 million pulls from Docker Hub, it’s the default choice for teams needing high-throughput analytics. However, the default ClickHouse image prioritizes developer convenience over the hardening that enterprise security teams demand. That gap leads to the blocking problems described above.

The Architecture of ClickHouse

ClickHouse follows a layered architecture optimized for speed. SQL queries arrive over two ports: HTTP (port 8123) or TCP (port 9000). The request then passes through the optimizer, which parses the query into an abstract syntax tree and prunes it before handing off to the pipeline executor. This executor distributes work across parallel threads.

Storage Engine: MergeTree

At the heart of ClickHouse is the MergeTree storage engine. It stores data in columnar .bin files and uses a sparse primary index to skip irrelevant granules without reading entire columns. Background merge processes compact data parts and maintain performance over time. Storage is pluggable—local disk, S3, or HDFS sit at the bottom layer.

The Root Cause: Why CVEs Block Your ClickHouse Deployment

When you pull the standard ClickHouse image, you get a full Linux distribution with many packages that ClickHouse never touches. Security scanners (e.g., Trivy, Snyk) check every package in every layer. Even if ClickHouse is secure, a vulnerability in a forgotten utility library or a system tool can trigger a block. The security team sees real CVEs, even if they’re irrelevant to the workload. This is where Docker Hardened Images make a difference.

How Docker Hardened Images Solve the Problem

Docker Hardened Images are designed from the ground up for minimal attack surface. They remove unnecessary packages, slim down the base OS, and apply security patches preemptively. For ClickHouse, DHI provides the same database engine but with a drastically reduced set of dependencies. The result: far fewer CVEs to flag, and those that remain are often irrelevant and easy to justify.

Key Benefits of Using DHI for ClickHouse

• Reduced Vulnerability Count – By stripping unused libraries, DHI images cut CVE findings by 80–90% compared to standard images.
• Faster Security Approval – With fewer CVEs, risk acceptance is simpler and quicker.
• Compliance Ready – DHI meets common enterprise security baselines (e.g., CIS benchmarks) out of the box.
• Same ClickHouse Performance – The database engine remains unchanged; only the base OS is hardened.

Implementing Docker Hardened Images for ClickHouse

Transitioning is straightforward. Replace the standard ClickHouse image tag with a DHI variant (e.g., clickhouse/clickhouse-server-hardened). Ensure your deployment manifests (Kubernetes, Docker Compose) reference the new image. Test in a staging environment first—while ClickHouse behaves identically, some peripheral configurations (like system tools for debugging) may be absent. If your pipeline scanner integrates with DHI, you’ll see the CVE count drop significantly.

Best Practices for a Smooth Migration

1. Run a comparative scan of the standard and hardened images using your security tooling.
2. Document the reduction in critical, high, and medium CVEs for your security team.
3. Deploy to a non-production environment to validate ClickHouse operations.
4. Update your CI/CD pipeline to use the hardened image tag.
5. Monitor for any regressions—unlikely with DHI, but prudent.

Conclusion: From Blocked to Production-Ready

The Langfuse team’s experience is a cautionary tale. Their ClickHouse deployment was blocked not by a bug, but by base-image CVEs. Docker Hardened Images eliminate that friction. By providing the same high-performance columnar database with a minimized attack surface, DHI turns a security team’s “no” into “yes.” If you’re preparing ClickHouse for production in a security-conscious environment, switching to hardened images is one of the simplest yet most effective changes you can make.