CVE-2025-67725
Dec. 22, 2025, 6:51 p.m.
7.5
High
Description
Tornado is a Python web framework and asynchronous networking library. In versions 6.5.2 and below, a single maliciously crafted HTTP request can block the server's event loop for an extended period, caused by the HTTPHeaders.add method. The function accumulates values using string concatenation when the same header name is repeated, causing a Denial of Service (DoS). Due to Python string immutability, each concatenation copies the entire string, resulting in O(n²) time complexity. The severity can vary from high if max_header_size has been increased from its default, to low if it has its default value of 64KB. This issue is fixed in version 6.5.3.
Product(s) Impacted
| Vendor | Product | Versions |
|---|---|---|
| Tornadoweb |
|
|
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 | tornadoweb | tornado | / | / | / | / | / | / | / | / |
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. 12, 2025, 6:15 a.m.
Last Modified: Dec. 22, 2025, 6:51 p.m.
Last Modified: Dec. 22, 2025, 6:51 p.m.
Status : Analyzed
CVE has had analysis completed and all data associations made.
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.