CVE-2025-59538
Oct. 2, 2025, 7:11 p.m.
7.5
High
Description
Argo CD is a declarative, GitOps continuous delivery tool for Kubernetes. For versions 2.9.0-rc1 through 2.14.19, 3.0.0-rc1 through 3.2.0-rc1, 3.1.6 and 3.0.17, when the webhook.azuredevops.username and webhook.azuredevops.password are not set in the default configuration, the /api/webhook endpoint crashes the entire argocd-server process when it receives an Azure DevOps Push event whose JSON array resource.refUpdates is empty. The slice index [0] is accessed without a length check, causing an index-out-of-range panic. A single unauthenticated HTTP POST is enough to kill the process. This issue is resolved in versions 2.14.20, 3.2.0-rc2, 3.1.8 and 3.0.19.
Product(s) Impacted
| Vendor | Product | Versions |
|---|---|---|
| Argo |
|
|
Weaknesses
Common security weaknesses mapped to this vulnerability.
CWE-248
Uncaught Exception
An exception is thrown from a function, but it is not caught.
*CPE(s)
Affected systems and software identified for this CVE.
| Type | Vendor | Product | Version | Update | Edition | Language | Software Edition | Target Software | Target Hardware | Other Information |
|---|---|---|---|---|---|---|---|---|---|---|
| a | argo | argo_cd | 2.9.0-2.14.19 | / | / | / | / | / | / | / |
| a | argo | argo_cd | 3.0.0-3.2.0-rc1 | / | / | / | / | / | / | / |
| a | argo | argo_cd | 3.1.6 | / | / | / | / | / | / | / |
| a | argo | argo_cd | 3.0.17 | / | / | / | / | / | / | / |
Tags
CVSS Score
CVSS Data - 3.1
- Attack Vector: NETWORK
- Attack Complexity: LOW
- Privileges Required: NONE
- Scope: UNCHANGED
- Confidentiality Impact: NONE
- Integrity Impact: NONE
- Availability Impact: HIGH
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Timeline
Published: Oct. 1, 2025, 9:16 p.m.
Last Modified: Oct. 2, 2025, 7:11 p.m.
Last Modified: Oct. 2, 2025, 7:11 p.m.
Status : Awaiting Analysis
CVE has been recently published to the CVE List and has been received by the NVD.
More infoSource
security-advisories@github.com
*Disclaimer: Some vulnerabilities do not have an associated CPE. To enhance the data, we use AI to infer CPEs based on CVE details. This is an automated process and might not always be accurate.