The DockerDash vulnerability is a critical security flaw discovered in Ask Gordon, an AI assistant embedded within Docker Desktop and the Docker CLI. This assistant interprets Docker image metadata, specifically LABEL fields, as executable instructions without proper validation. An attacker can craft a malicious Docker image embedding weaponized instructions in these metadata labels. When a user queries Ask Gordon about this image, the assistant reads and forwards these instructions to the Model Context Protocol (MCP) Gateway, a middleware component that bridges AI agents and local execution environments. The MCP Gateway, unable to distinguish between benign metadata and executable commands, executes the instructions with the victim's Docker privileges. This results in remote code execution (RCE) on the victim's system. Additionally, the flaw allows data exfiltration by leveraging Ask Gordon's read-only permissions to gather sensitive environment details such as installed tools, container configurations, mounted directories, and network topology. The root cause is a failure of contextual trust and zero-trust validation in the AI's processing pipeline, termed Meta-Context Injection. The attack chain involves publishing a malicious Docker image, victim interaction with Ask Gordon, and unvalidated command execution via MCP tools. Docker addressed this vulnerability in version 4.50.0 released in November 2025, which also fixed a related prompt injection flaw discovered by Pillar Security. This vulnerability highlights the emerging risks in AI supply chain security and the need for strict validation of AI inputs, especially in environments integrating AI with system-level operations.

For European organizations, the DockerDash vulnerability poses a significant risk to both cloud and local development environments that utilize Docker Desktop and CLI with Ask Gordon AI. Successful exploitation can lead to full remote code execution under the user's Docker privileges, potentially allowing attackers to deploy malware, pivot within networks, or disrupt containerized services. Data exfiltration risks threaten confidentiality by exposing sensitive internal configurations, network details, and operational metadata. Organizations relying heavily on containerization for development, CI/CD pipelines, or production workloads face operational disruptions and potential compliance violations if sensitive data is leaked. The vulnerability also undermines trust in AI-assisted tooling, which is increasingly integrated into developer workflows. Given Docker's widespread adoption across European enterprises, especially in technology, finance, and manufacturing sectors, the impact could be broad and severe. Attackers exploiting this flaw could gain footholds in critical infrastructure, leading to cascading effects on service availability and data integrity. The lack of authentication and user interaction barriers lowers the attack complexity, increasing the likelihood of exploitation in targeted or opportunistic attacks.

1. Immediately upgrade all Docker Desktop and CLI installations to version 4.50.0 or later, which contains the patch for DockerDash. 2. Implement strict zero-trust validation on all metadata and contextual inputs processed by AI assistants like Ask Gordon to prevent execution of untrusted commands. 3. Restrict MCP Gateway privileges and isolate its execution environment to minimize the impact of potential command injections. 4. Enforce container image provenance policies, including scanning and verifying Docker images before use to detect malicious LABEL metadata. 5. Educate developers and DevOps teams about the risks of querying AI assistants with untrusted images and encourage cautious interaction with AI tools. 6. Monitor Docker environments for unusual MCP Gateway activity or unexpected command executions indicative of exploitation attempts. 7. Use runtime security tools to detect anomalous container behavior and unauthorized code execution. 8. Collaborate with security teams to integrate AI supply chain risk assessments into existing vulnerability management and incident response workflows.