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OpenRefine has a reflected cross-site scripting vulnerability (XSS) from POST request in ExportRowsCommand

High severity GitHub Reviewed Published Oct 24, 2024 in OpenRefine/OpenRefine • Updated Oct 30, 2024

Package

maven org.openrefine:openrefine (Maven)

Affected versions

< 3.8.3

Patched versions

3.8.3

Description

Summary

The export-rows command can be used in such a way that it reflects part of the request verbatim, with a Content-Type header also taken from the request.

An attacker could lead a user to a malicious page that submits a form POST that contains embedded JavaScript code. This code would then be included in the response, along with an attacker-controlled Content-Type header, and so potentially executed in the victim's browser as if it was part of OpenRefine.

The attacker must know a valid project ID of a project that contains at least one row.

Details

The malicious form sets contentType to text/html (ExportRowsCommand.java line 101) and preview to true (line 107). This combination causes the browser to treat what OpenRefine thinks of as an export preview as a regular webpage.

It would be safer if the export-rows command did not allow overriding the Content-Type header at all, instead relying on the exporter to provide the correct Content-Type. It could also require a CSRF token. As an additional measure, it could add a Content-Security-Policy header to the response disabling scripts and such entirely.

At least the CSV exporter (separator and lineSeparator fields) and templating exporter (any field) are affected. It may also be possible to inject into the dateSettings.custom field or the SQL exporter default value field, if the project contains date or null cells.

PoC

An example form that demonstrates the issue is available on https://wandernauta.nl/os/.

Impact

Execution of arbitrary JavaScript in the user's browser. The attacker-provided code can do anything the user can do, including deleting projects, retrieving database passwords, or executing arbitrary Jython or Closure expressions, if those extensions are also present.

References

@wetneb wetneb published to OpenRefine/OpenRefine Oct 24, 2024
Published to the GitHub Advisory Database Oct 24, 2024
Reviewed Oct 24, 2024
Published by the National Vulnerability Database Oct 24, 2024
Last updated Oct 30, 2024

Severity

High

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity Low
Attack Requirements None
Privileges Required None
User interaction Passive
Vulnerable System Impact Metrics
Confidentiality High
Integrity High
Availability None
Subsequent System Impact Metrics
Confidentiality None
Integrity None
Availability None

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:H/VI:H/VA:N/SC:N/SI:N/SA:N

EPSS score

0.084%
(38th percentile)

Weaknesses

CVE ID

CVE-2024-47880

GHSA ID

GHSA-79jv-5226-783f

Source code

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