CVE-2025-65637
Dec. 23, 2025, 12:26 a.m.
7.5
High
Description
A denial-of-service vulnerability exists in github.com/sirupsen/logrus when using Entry.Writer() to log a single-line payload larger than 64KB without newline characters. Due to limitations in the internal bufio.Scanner, the read fails with "token too long" and the writer pipe is closed, leaving Writer() unusable and causing application unavailability (DoS). This affects versions < 1.8.3, 1.9.0, and 1.9.2. The issue is fixed in 1.8.3, 1.9.1, and 1.9.3+, where the input is chunked and the writer continues to function even if an error is logged.
Product(s) Impacted
| Vendor | Product | Versions |
|---|---|---|
| Turbopuffer |
|
|
Weaknesses
Common security weaknesses mapped to this vulnerability.
CWE-400
Uncontrolled Resource Consumption
The product does not properly control the allocation and maintenance of a limited resource, thereby enabling an actor to influence the amount of resources consumed, eventually leading to the exhaustion of available resources.
*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 | turbopuffer | logrus | / | / | / | / | / | go | / | / |
| a | turbopuffer | logrus | 1.9.0 | / | / | / | / | go | / | / |
| a | turbopuffer | logrus | 1.9.2 | / | / | / | / | go | / | / |
References
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: Dec. 4, 2025, 7:16 p.m.
Last Modified: Dec. 23, 2025, 12:26 a.m.
Last Modified: Dec. 23, 2025, 12:26 a.m.
Status : Analyzed
CVE has had analysis completed and all data associations made.
More infoSource
cve@mitre.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.