CVE-2025-24814
Feb. 15, 2025, 1:15 a.m.
5.4
Medium
Description
Core creation allows users to replace "trusted" configset files with arbitrary configuration
Solr instances that (1) use the "FileSystemConfigSetService" component (the default in "standalone" or "user-managed" mode), and (2) are running without authentication and authorization are vulnerable to a sort of privilege escalation wherein individual "trusted" configset files can be ignored in favor of potentially-untrusted replacements available elsewhere on the filesystem. These replacement config files are treated as "trusted" and can use "<lib>" tags to add to Solr's classpath, which an attacker might use to load malicious code as a searchComponent or other plugin.
This issue affects all Apache Solr versions up through Solr 9.7. Users can protect against the vulnerability by enabling authentication and authorization on their Solr clusters or switching to SolrCloud (and away from "FileSystemConfigSetService"). Users are also recommended to upgrade to Solr 9.8.0, which mitigates this issue by disabling use of "<lib>" tags by default.
Product(s) Impacted
| Product | Versions |
|---|---|
| Apache Solr |
|
Weaknesses
Common security weaknesses mapped to this vulnerability.
CWE-250
Execution with Unnecessary Privileges
The product performs an operation at a privilege level that is higher than the minimum level required, which creates new weaknesses or amplifies the consequences of other weaknesses.
Tags
CVSS Score
CVSS Data - 3.1
- Attack Vector: NETWORK
- Attack Complexity: LOW
- Privileges Required: LOW
- Scope: UNCHANGED
- Confidentiality Impact: LOW
- Integrity Impact: LOW
- Availability Impact: NONE
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:N
Timeline
Published: Jan. 27, 2025, 9:15 a.m.
Last Modified: Feb. 15, 2025, 1:15 a.m.
Last Modified: Feb. 15, 2025, 1:15 a.m.
Status : Awaiting Analysis
CVE has been recently published to the CVE List and has been received by the NVD.
More infoSource
security@apache.org
*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.