CVE-2025-57813
Aug. 26, 2025, 4:15 p.m.
5.9
Medium
Description
traQ is a messenger application built for Digital Creators Club traP. Prior to version 3.25.0, a vulnerability exists where sensitive information, such as OAuth tokens, are recorded in log files when an error occurs during the execution of an SQL query. An attacker could intentionally trigger an SQL error by methods such as placing a high load on the database. This could allow an attacker who has the authority to view the log files to illicitly acquire the recorded sensitive information. This vulnerability has been patched in version 3.25.0. If upgrading is not possible, a temporary workaround involves reviewing access permissions for SQL error logs and strictly limiting access to prevent unauthorized users from viewing them.
Product(s) Impacted
| Vendor | Product | Versions |
|---|---|---|
| Traq |
|
|
Weaknesses
Common security weaknesses mapped to this vulnerability.
CWE-532
Insertion of Sensitive Information into Log File
Information written to log files can be of a sensitive nature and give valuable guidance to an attacker or expose sensitive user information.
*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 | traq | traq | <3.25.0 | / | / | / | / | / | / | / |
Tags
CVSS Score
CVSS Data - 3.1
- Attack Vector: NETWORK
- Attack Complexity: HIGH
- Privileges Required: HIGH
- Scope: UNCHANGED
- Confidentiality Impact: HIGH
- Integrity Impact: HIGH
- Availability Impact: NONE
CVSS:3.1/AV:N/AC:H/PR:H/UI:N/S:U/C:H/I:H/A:N
Timeline
Published: Aug. 26, 2025, 4:15 p.m.
Last Modified: Aug. 26, 2025, 4:15 p.m.
Last Modified: Aug. 26, 2025, 4:15 p.m.
Status : Received
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.