Key Points:
- Critical flaw in Docker’s Ask Gordon AI patched.
- Vulnerability allowed code execution via image metadata.
- Emphasizes AI supply chain risks and need for zero-trust validation.
Overview of the Docker AI Vulnerability
Recently, a significant security flaw was identified and rectified in Docker’s Ask Gordon AI, which is integrated into Docker Desktop and the Command-Line Interface (CLI). This vulnerability, termed DockerDash by cybersecurity firm Noma Labs, had the potential to allow unauthorized code execution and data theft through the manipulation of image metadata. Docker released version 4.50.0 in November 2025, which addresses this critical issue.
The flaw involved a three-stage attack using malicious metadata labels in Docker images. These labels could trigger dangerous operations when processed by Ask Gordon, exploiting weaknesses in the Model Context Protocol (MCP) Gateway architecture. The lack of validation at multiple stages enabled attackers to bypass security measures.
Technical Implications and Exploitation Risks
The vulnerability posed severe risks, such as remote code execution across cloud and CLI platforms, and data exfiltration from desktop applications. Noma Security highlighted that the flaw originated from treating unverified metadata as executable commands. This oversight allowed attackers to insert harmful instructions within Docker image metadata, effectively breaching security barriers.
The MCP Gateway’s inability to differentiate between legitimate metadata and malicious instructions further exacerbated the problem. By embedding harmful commands in metadata fields, attackers could manipulate the AI’s decision-making process, leading to unauthorized command execution.
Preventive Measures and Future Outlook
To mitigate such risks, Docker’s latest update not only addresses this flaw but also resolves a related prompt injection vulnerability identified by Pillar Security. This additional vulnerability could have been exploited to alter Docker Hub repository metadata, further compromising system security.
Sasi Levi from Noma Labs stressed the importance of recognizing AI supply chain risks as a critical threat. Implementing zero-trust validation for all contextual data provided to AI models is crucial to prevent similar attacks in the future. This approach ensures that AI systems are not compromised by hidden malicious payloads.
Conclusion
The DockerDash vulnerability underscores the pressing need for robust security measures in AI-driven environments. As AI continues to integrate into various technologies, safeguarding against supply chain risks becomes imperative. Docker’s swift response in patching this flaw highlights the industry’s commitment to enhancing cybersecurity protocols and protecting user environments.
