CVE-2024-7037: open-webui: path traversal → arbitrary file write/RCE
GHSA-54f4-v6v9-9q82 MEDIUM CISA: ATTENDAny user with admin credentials on open-webui <= 0.3.8 can overwrite system files via a crafted upload filename, achieving remote code execution. Despite the Medium CVSS rating, treat this as critical for internal AI deployments — shared admin credentials are endemic in AI/ML teams. Update immediately or block access to the pipeline upload endpoint at the network layer.
What is the risk?
CVSS 6.5 underrepresents operational risk. The High Privilege requirement is the only meaningful barrier, and AI teams routinely share admin credentials or run open-webui with minimal access controls on internal networks. Path traversal-to-RCE is a trivial, well-documented exploit chain requiring no AI/ML expertise. Deployments exposed beyond localhost — even on internal networks — should be treated as high severity.
What systems are affected?
| Package | Ecosystem | Vulnerable Range | Patched |
|---|---|---|---|
| Open WebUI | pip | <= 0.3.8 | No patch |
Do you use Open WebUI? You're affected.
How severe is it?
What is the attack surface?
What should I do?
6 steps-
Update open-webui immediately to a version beyond 0.3.8.
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If patching is delayed, block /api/pipelines/upload at the WAF or reverse proxy layer.
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Audit existing pipeline files in CACHE_DIR for unexpected content or path-traversal artifacts.
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Enforce strong unique admin credentials and restrict admin access to trusted IPs.
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Monitor CACHE_DIR parent directories for unexpected file creation or modification via filesystem auditing (auditd, inotify).
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Limit Docker volume mounts to the minimum required — avoid mounting host paths writable by the app container.
What does CISA's SSVC say?
Source: CISA Vulnrichment (SSVC v2.0). Decision based on the CISA Coordinator decision tree.
How is it classified?
Which compliance frameworks are affected?
This CVE is relevant to:
Frequently Asked Questions
What is CVE-2024-7037?
Any user with admin credentials on open-webui <= 0.3.8 can overwrite system files via a crafted upload filename, achieving remote code execution. Despite the Medium CVSS rating, treat this as critical for internal AI deployments — shared admin credentials are endemic in AI/ML teams. Update immediately or block access to the pipeline upload endpoint at the network layer.
Is CVE-2024-7037 actively exploited?
No confirmed active exploitation of CVE-2024-7037 has been reported, but organizations should still patch proactively.
How to fix CVE-2024-7037?
1. Update open-webui immediately to a version beyond 0.3.8. 2. If patching is delayed, block /api/pipelines/upload at the WAF or reverse proxy layer. 3. Audit existing pipeline files in CACHE_DIR for unexpected content or path-traversal artifacts. 4. Enforce strong unique admin credentials and restrict admin access to trusted IPs. 5. Monitor CACHE_DIR parent directories for unexpected file creation or modification via filesystem auditing (auditd, inotify). 6. Limit Docker volume mounts to the minimum required — avoid mounting host paths writable by the app container.
What systems are affected by CVE-2024-7037?
This vulnerability affects the following AI/ML architecture patterns: self-hosted LLM deployments, AI pipeline systems, model serving, agent frameworks.
What is the CVSS score for CVE-2024-7037?
CVE-2024-7037 has a CVSS v3.1 base score of 6.5 (MEDIUM). The EPSS exploitation probability is 1.03%.
What is the AI security impact?
Affected AI Architectures
MITRE ATLAS Techniques
AML.T0010.001 AI Software AML.T0037 Data from Local System AML.T0049 Exploit Public-Facing Application AML.T0072 Reverse Shell Compliance Controls Affected
What are the technical details?
Original Advisory
In version v0.3.8 of open-webui/open-webui, the endpoint /api/pipelines/upload is vulnerable to arbitrary file write and delete due to unsanitized file.filename concatenation with CACHE_DIR. This vulnerability allows attackers to overwrite and delete system files, potentially leading to remote code execution.
Exploitation Scenario
An attacker obtains admin credentials via credential stuffing, phishing, or password reuse common in AI/ML teams. They send a POST to /api/pipelines/upload with a filename crafted as '../../etc/cron.d/backdoor' or '../../usr/local/lib/python3.x/site-packages/malicious.py'. The server concatenates the unsanitized filename with CACHE_DIR and writes attacker-controlled content to the resolved path. The cron variant schedules a reverse shell; the Python module variant injects malicious code executed during the next LLM inference request. Standard tooling (curl, Burp Suite) suffices — no AI/ML knowledge required.
Weaknesses (CWE)
CWE-22 — Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal'): The product uses external input to construct a pathname that is intended to identify a file or directory that is located underneath a restricted parent directory, but the product does not properly neutralize special elements within the pathname that can cause the pathname to resolve to a location that is outside of the restricted directory.
- [Implementation] Assume all input is malicious. Use an "accept known good" input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does. When performing input validation, consider all potentially relevant properties, including length, type of input, the full range of acceptable values, missing or extra inputs, syntax, consistency across related fields, and conformance to business rules. As an example of business rule logic, "boat" may be syntactically valid because it only contains alphanumeric characters, but it is not valid if the input is only expected to contain colors such as "red" or "blue." Do not rely exclusively on looking for malicious or malformed inputs. This is likely to miss at least one undesirable input, especially if the code's environment changes. This can give attackers enough room to bypass the intended validation. However, denylis
- [Architecture and Design] For any security checks that are performed on the client side, ensure that these checks are duplicated on the server side, in order to avoid CWE-602. Attackers can bypass the client-side checks by modifying values after the checks have been performed, or by changing the client to remove the client-side checks entirely. Then, these modified values would be submitted to the server.
Source: MITRE CWE corpus.
CVSS Vector
CVSS:3.0/AV:N/AC:L/PR:H/UI:N/S:U/C:N/I:H/A:H References
Timeline
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