CVE-2026-1977
Unknown Unknown - Not Provided
Remote Code Injection via eval in mcp-vegalite-server Visualize_data

Publication date: 2026-02-06

Last updated on: 2026-04-29

Assigner: VulDB

Description
A security vulnerability has been detected in isaacwasserman mcp-vegalite-server up to 16aefed598b8cd897b78e99b907f6e2984572c61. Affected by this vulnerability is the function eval of the component visualize_data. Such manipulation of the argument vegalite_specification leads to code injection. The attack may be performed from remote. The exploit has been disclosed publicly and may be used. This product utilizes a rolling release system for continuous delivery, and as such, version information for affected or updated releases is not disclosed. The project was informed of the problem early through an issue report but has not responded yet.
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Meta Information
Published
2026-02-06
Last Modified
2026-04-29
Generated
2026-05-27
AI Q&A
2026-02-06
EPSS Evaluated
2026-05-25
NVD
EUVD
Affected Vendors & Products
Showing 1 associated CPE
Vendor Product Version / Range
isaacwasserman mcp-vegalite-server to 16aefed598b8cd897b78e99b907f6e2984572c61 (exc)
Helpful Resources
Exploitability
CWE
CWE Icon
KEV
KEV Icon
CWE ID Description
CWE-74 The product constructs all or part of a command, data structure, or record using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify how it is parsed or interpreted when it is sent to a downstream component.
CWE-94 The product constructs all or part of a code segment using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the syntax or behavior of the intended code segment.
Attack-Flow Graph
AI Powered Q&A
Can you explain this vulnerability to me?

[{'type': 'paragraph', 'content': "CVE-2026-1977 is a code injection vulnerability in the isaacwasserman mcp-vegalite-server project, specifically in the visualize_data component's eval function. The vulnerability arises because the vegalite_specification parameter is processed using Python's eval function without proper sanitization, allowing attackers to inject and execute arbitrary code."}, {'type': 'paragraph', 'content': 'This unsafe use of eval on user-supplied input enables remote attackers to perform arbitrary code execution on the affected system.'}] [1, 2, 4]


How can this vulnerability impact me? :

This vulnerability allows remote attackers to execute arbitrary code on the affected server, which can compromise the confidentiality, integrity, and availability of the system.

  • On local MCP deployments without sandboxing, attackers can execute commands with the privileges of the current user.
  • On local MCP deployments with strong sandboxing, command execution is limited to the sandbox environment.
  • On remote MCP single-tenant or private deployments, attackers can execute code remotely with impact depending on host isolation.
  • On remote MCP multi-tenant or SaaS environments, this poses a critical risk of cross-tenant compromise and potential full service breach.

How does this vulnerability affect compliance with common standards and regulations (like GDPR, HIPAA)?:

I don't know


How can this vulnerability be detected on my network or system? Can you suggest some commands?

[{'type': 'paragraph', 'content': 'This vulnerability involves code injection through the eval function on the vegalite_specification parameter in the visualize_data tool of the mcp-vegalite-server. Detection can focus on identifying suspicious or unexpected usage of this parameter, especially payloads that attempt to execute system commands.'}, {'type': 'paragraph', 'content': "A practical detection method is to monitor or log calls to the visualize_data component and inspect the vegalite_specification argument for suspicious patterns such as Python code execution attempts (e.g., usage of __import__('os').system(...))."}, {'type': 'paragraph', 'content': 'Since the vulnerability is related to Python eval execution, you can attempt to detect exploitation attempts by searching logs or network traffic for payloads containing keywords like "__import__", "system", or other suspicious code snippets.'}, {'type': 'paragraph', 'content': 'Example commands to detect potential exploitation attempts might include:'}, {'type': 'list_item', 'content': "Using grep on server logs to find suspicious payloads: grep -iE '__import__|system|eval' /path/to/mcp-vegalite-server/logs/*"}, {'type': 'list_item', 'content': 'Monitoring network traffic for suspicious payloads with tools like tcpdump or Wireshark filtering for keywords in HTTP requests.'}, {'type': 'list_item', 'content': 'If you have access to the server, running a script to detect eval usage or unexpected command execution in the visualize_data function could help.'}, {'type': 'paragraph', 'content': 'Note that no specific detection tools or commands are provided in the available resources, so these suggestions are based on the nature of the vulnerability and typical detection approaches for code injection.'}] [1, 2, 4]


What immediate steps should I take to mitigate this vulnerability?

Currently, there are no known patches or official mitigations available for this vulnerability as the project maintainers have not responded or provided countermeasures.

Immediate mitigation steps include:

  • Avoid using or exposing the visualize_data tool with the vulnerable eval function on the vegalite_specification parameter.
  • Restrict access to the mcp-vegalite-server, especially limiting remote access to trusted users or networks to reduce the risk of remote exploitation.
  • Consider sandboxing or isolating the MCP service to limit the impact of potential code execution.
  • Monitor for exploitation attempts and suspicious activity as a temporary defense.
  • Evaluate alternative products or workarounds that do not use the vulnerable eval function.

Because the vulnerability allows remote code execution, these steps are critical to reduce exposure until an official fix is released.


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