CVE-2026-10053
GitLab vulnerability analysis and mitigation

Overview

CVE-2026-10053 is a path traversal vulnerability in the GitLab CE/EE package registry that can allow an authenticated user to achieve remote code execution (RCE) under certain conditions. It affects all GitLab CE/EE versions from 18.8 before 19.0.6, 19.1 before 19.1.4, and 19.2 before 19.2.2. The vulnerability was published on August 23, 2026, and GitLab has released patches for all affected branches. It carries a CVSS v3.1 base score of 8.5 (High) (GitHub Advisory).

Technical details

The root cause is classified as CWE-22 (Improper Limitation of a Pathname to a Restricted Directory — 'Path Traversal'). The vulnerability resides in GitLab's package registry component, where insufficient sanitization of user-supplied input allows an attacker to craft a malicious package upload that traverses outside the intended directory boundary, ultimately enabling arbitrary file writes that can lead to RCE. Exploitation requires network access and a low-privileged authenticated account, but no user interaction; attack complexity is rated High, indicating that specific conditions or configurations must be met. The vulnerability was originally reported via HackerOne (report #3754194) and tracked internally at GitLab work item #601596 (GitHub Advisory).

Impact

Successful exploitation allows a low-privileged authenticated attacker to write arbitrary files outside the intended package registry directory on the GitLab server, leading to remote code execution. The CVSS scope is marked as Changed, meaning the impact extends beyond the vulnerable component itself — a compromised GitLab server could expose source code repositories, CI/CD secrets, credentials, and other sensitive organizational data. Full confidentiality, integrity, and availability impacts are possible, making this a significant risk for organizations hosting GitLab instances with untrusted or semi-trusted users (GitHub Advisory).

Exploitability

As of the publication date, there is no public proof-of-concept exploit and no confirmed evidence of in-the-wild exploitation (GitHub Advisory). The EPSS score is approximately 0.00715 (~0.7%), indicating a currently low probability of exploitation in the near term. No threat actor attribution has been reported, and the vulnerability is not listed in the CISA Known Exploited Vulnerabilities (KEV) catalog at this time. However, the combination of RCE potential and the widespread use of GitLab in enterprise environments makes this a high-priority patching target.

Exploitation steps

  1. Reconnaissance: Identify GitLab CE/EE instances running affected versions (18.8–19.0.5, 19.1.0–19.1.3, or 19.2.0–19.2.1) using version disclosure endpoints (e.g., /help page or API endpoint /api/v4/version if accessible).
  2. Authenticate: Obtain or use an existing low-privileged GitLab account with access to a project that has the package registry feature enabled.
  3. Craft malicious package: Prepare a package (e.g., a generic, Maven, npm, or other supported format) with a filename or metadata field containing path traversal sequences (e.g., ../../) designed to write a file outside the intended package storage directory.
  4. Upload the package: Use the GitLab Package Registry API or UI to upload the crafted package to a project, triggering the path traversal during server-side file handling.
  5. Achieve arbitrary file write: The traversal causes the server to write attacker-controlled content to a sensitive location (e.g., a web-accessible directory, a cron job path, or a configuration file location).
  6. Execute code: Leverage the written file to achieve remote code execution — for example, by writing a web shell to a publicly accessible path or overwriting a script executed by a scheduled task, then triggering its execution (GitHub Advisory).

Indicators of compromise

  • Network: Unusual or repeated package upload API requests (e.g., PUT /api/v4/projects/:id/packages/) containing encoded path traversal sequences (../, %2e%2e%2f, %252e%252e%252f) in filenames or metadata fields.
  • File System: Unexpected files appearing outside the configured GitLab package registry storage directory; new or modified files in web-accessible directories (e.g., /var/opt/gitlab/gitlab-rails/public/) or system directories not normally written to by the GitLab process.
  • Logs: GitLab production logs (/var/log/gitlab/gitlab-rails/production.log) showing package upload requests with anomalous filenames; errors or warnings related to file path resolution in the package registry component.
  • Process: Unusual child processes spawned by the GitLab Rails or Puma worker processes (e.g., /bin/bash, curl, wget, reverse shell processes); unexpected outbound network connections from the GitLab server to external IPs.

Mitigation and workarounds

GitLab has released patched versions 19.0.6, 19.1.4, and 19.2.2 addressing this vulnerability; upgrading to one of these versions is the primary recommended remediation (GitHub Advisory). If immediate patching is not feasible, organizations should restrict package registry access to trusted users only and monitor package upload activity for suspicious filenames or path traversal patterns. Disabling the package registry feature entirely via GitLab Admin settings (Admin Area > Settings > General > Visibility and access controls) can serve as a temporary workaround until patching is possible.

Community reactions

The vulnerability received coverage from threat intelligence outlets including The Hacker Wire and Hawk-Eye's weekly threat landscape digest shortly after disclosure (GitHub Advisory). Security researcher Suriq published a technical blog post titled "GitLab Package Registry Arbitrary File Write" analyzing the vulnerability mechanics. Social media activity was noted on Mastodon (infosec.exchange) and Twitter/X, with security community members highlighting the RCE potential and urging prompt patching. Tenable published detection plugins (Nessus plugin #339039) to assist organizations in identifying vulnerable instances.

Additional resources


SourceThis report was generated using AI

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