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OctoPrint has possible file exfiltration via query parameters on upload endpoints

High severity GitHub Reviewed Published Jun 23, 2026 in OctoPrint/OctoPrint • Updated Aug 21, 2026

Package

pip OctoPrint (pip)

Affected versions

<= 1.11.7
>= 2.0.0rc1, <= 2.0.0rc2

Patched versions

1.11.8
2.0.0rc3

Description

Impact

OctoPrint versions up until and including 1.11.7 as well as 2.0.0rc1 and 2.0.0rc2 contain a vulnerability that allows an attacker with the FILE_UPLOAD permission to exfiltrate files from the host that OctoPrint has read access to, by moving them into the upload folder where they then can be downloaded from. This vulnerability was already reported as GHSA-m9jh-jf9h-x3h2/CVE-2025-48067 but the fix provided in OctoPrint 1.11.2 turned out to be incomplete.

The primary risk lies in the potential exfiltration of secrets stored inside OctoPrint's config, or further system files. By removing important runtime files, this could also be used to impact the availability of the host after an attempted server restart. Given that the attacker requires a user account with file upload permissions, the actual impact of this should however hopefully be minimal in most cases.

Patches

The vulnerability has been patched in version 1.11.8 and 2.0.0rc3.

Details

OctoPrint's web application is implemented in Flask, but uploads are first intercepted by a custom upload handler built on Tornado that sits in front of it. The handler streams the upload to a temporary file on disk - so files larger than the available memory can be uploaded - and rewrites the request, adding internal form fields that tell Flask where to find that temporary file.

These fields are reserved and meant to be set only by the upload handler, never by the client. The previous fix from GHSA-m9jh-jf9h-x3h2/CVE-2025-48067 stripped them from the request received from the client when they were sent as multipart form fields, yet they could still reach Flask through other channels: as plain query parameters, or - since the Tornado handler and Flask did not parse requests identically - smuggled in via several "parser differentials" that looked harmless to the handler while Flask still saw the injected fields. Any of these let an attacker make OctoPrint treat an arbitrary file on the host as a freshly uploaded one and move it into the upload folder.

The following endpoints in OctoPrint are affected:

  • /api/files/{local|sdcard}
  • /api/languages
  • /plugin/backup/restore
  • /plugin/pluginmanager/upload_file

Further upload endpoints in third party plugins might be affected too.

The fix rejects requests carrying any of the reserved fields, aligns the Tornado handler's request parsing with Flask's (Werkzeug) to avoid any differential parsing, and re-validates the request rewritten by Tornado before forwarding it to Flask.

Credits

This vulnerability was discovered and responsibly disclosed to OctoPrint by Koh Jun Sheng and Jacopo Tediosi.

Timeline

2026-06-04: Report received
2026-06-04: Report acknowledged
2026-06-08: Report verified
2026-06-17: Fix ready for 1.11.x
2026-06-22: Fix ported to 2.0.0
2026-06-23: Fix released with 1.11.8 and 2.0.0rc3

References

@foosel foosel published to OctoPrint/OctoPrint Jun 23, 2026
Published to the GitHub Advisory Database Jun 23, 2026
Reviewed Jun 23, 2026
Last updated Aug 21, 2026

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 Adjacent
Attack Complexity Low
Attack Requirements None
Privileges Required Low
User interaction None
Vulnerable System Impact Metrics
Confidentiality High
Integrity Low
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:A/AC:L/AT:N/PR:L/UI:N/VC:H/VI:L/VA:N/SC:N/SI:N/SA:N

EPSS score

Exploit Prediction Scoring System (EPSS)

This score estimates the probability of this vulnerability being exploited within the next 30 days. Data provided by FIRST.
(23rd percentile)

Weaknesses

External Control of File Name or Path

The product allows user input to control or influence paths or file names that are used in filesystem operations. Learn more on MITRE.

Interpretation Conflict

Product A handles inputs or steps differently than Product B, which causes A to perform incorrect actions based on its perception of B's state. Learn more on MITRE.

CVE ID

CVE-2026-54134

GHSA ID

GHSA-j4h9-pm27-4rfw

Source code

Credits

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