CVE-2025-6587 in Docker
Summary
by MITRE • 07/03/2025
System environment variables are recorded in Docker Desktop diagnostic logs, when using shell auto-completion. This leads to unintentional disclosure of sensitive information such as api keys, passwords, etc. A malicious actor with read access to these logs could obtain secrets and further use them to gain unauthorized access to other systems. Starting with version 4.43.0 Docker Desktop no longer logs system environment variables as part of diagnostics log collection.
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Analysis
by VulDB Data Team • 05/05/2026
This vulnerability represents a critical information disclosure flaw in Docker Desktop diagnostic logging functionality that emerged from the improper handling of environment variables during shell auto-completion operations. The issue stems from the diagnostic logging system's indiscriminate capture of all system environment variables without proper sanitization or filtering mechanisms, creating a significant security risk when these logs are generated during interactive shell sessions. The vulnerability specifically affects scenarios where users engage with shell auto-completion features, which are commonly used for productivity and automation tasks within containerized development environments. When users type commands that trigger auto-completion, the system captures not only the command itself but also the complete environment context including sensitive credentials and API keys that may be stored in environment variables. This flaw directly violates security principles related to least privilege and data protection, as it exposes confidential information that should remain isolated within the user's secure execution environment.
The technical implementation of this vulnerability involves the diagnostic logging subsystem's failure to distinguish between legitimate operational data and sensitive credential information within environment variables. When shell auto-completion is triggered, the logging mechanism captures the entire process environment including variables such as AWS_ACCESS_KEY_ID, DATABASE_PASSWORD, API_TOKEN, and other confidential parameters that are typically stored in environment variables for application configuration. The flaw manifests as a lack of input validation and output sanitization within the logging pipeline, creating a direct path for sensitive data exposure. This vulnerability aligns with CWE-200 (Information Exposure) and CWE-312 (Sensitive Data Exposure) classifications, as it enables unauthorized disclosure of confidential information through improper logging practices. The attack vector specifically leverages the diagnostic logging feature that is designed for troubleshooting but inadvertently becomes a conduit for credential leakage when users interact with shell completion mechanisms. The vulnerability demonstrates poor separation of concerns between operational logging and security-sensitive data handling, creating an attack surface that malicious actors can exploit to gain unauthorized access to systems and resources.
The operational impact of this vulnerability extends beyond simple credential exposure to encompass broader security implications for containerized development environments and DevOps workflows. When malicious actors gain read access to diagnostic logs, they can extract authentication tokens, database credentials, cloud service access keys, and other sensitive information that could enable them to compromise connected systems, access cloud resources, or perform unauthorized operations within the affected infrastructure. The vulnerability particularly affects development teams using Docker Desktop for container orchestration, where environment variables are commonly used to store configuration data including secrets and credentials. The risk is amplified in environments where diagnostic logs are stored in accessible locations or shared across teams, as the exposure can occur without explicit user knowledge or consent. This creates a persistent security risk that can compound over time as more sensitive information is inadvertently logged and stored in diagnostic repositories. The vulnerability also impacts compliance with security standards such as SOC 2, PCI DSS, and GDPR, as it creates potential data breaches through improper handling of sensitive information. Organizations using Docker Desktop for development and testing may unknowingly expose critical infrastructure access credentials through routine diagnostic logging activities, making this vulnerability particularly dangerous in production environments where security controls are expected to be robust.
The mitigation strategy for this vulnerability involves implementing comprehensive logging sanitization and environment variable filtering mechanisms within Docker Desktop's diagnostic subsystem. Version 4.43.0 of Docker Desktop addresses this issue by introducing proper filtering that prevents system environment variables from being included in diagnostic logs, effectively closing the information disclosure channel. Organizations should ensure all Docker Desktop installations are updated to version 4.43.0 or later to eliminate this vulnerability. Additional defensive measures include implementing log access controls to limit who can read diagnostic logs, establishing regular log review procedures to detect potential credential exposure, and configuring automated monitoring for suspicious log patterns. Security teams should also consider implementing environment variable sanitization at the application level and using secret management solutions that do not rely on environment variables for credential storage. The fix aligns with ATT&CK technique T1531 (Create or Modify System Process) by addressing improper logging mechanisms that inadvertently expose sensitive data, and follows security best practices for preventing information disclosure vulnerabilities. Organizations should conduct security assessments to identify any existing instances of credential exposure through diagnostic logs and implement proper log rotation and secure storage practices to minimize the attack surface. The resolution demonstrates the importance of proper input validation and output sanitization in security-sensitive components, particularly those involved in system diagnostics and monitoring functions.