CVE-2024-51501

Nov. 8, 2024, 4:15 p.m.

None
No Score

Description

Refit is an automatic type-safe REST library for .NET Core, Xamarin and .NET The various header-related Refit attributes (Header, HeaderCollection and Authorize) are vulnerable to CRLF injection. The way HTTP headers are added to a request is via the `HttpHeaders.TryAddWithoutValidation` method. This method does not check for CRLF characters in the header value. This means that any headers added to a refit request are vulnerable to CRLF-injection. In general, CRLF-injection into a HTTP header (when using HTTP/1.1) means that one can inject additional HTTP headers or smuggle whole HTTP requests. If an application using the Refit library passes a user-controllable value through to a header, then that application becomes vulnerable to CRLF-injection. This is not necessarily a security issue for a command line application like the one above, but if such code were present in a web application then it becomes vulnerable to request splitting (as shown in the PoC) and thus Server Side Request Forgery. Strictly speaking this is a potential vulnerability in applications using Refit and not in Refit itself. This issue has been addressed in release versions 7.2.22 and 8.0.0 and all users are advised to upgrade. There are no known workarounds for this vulnerability.

Product(s) Impacted

Product Versions
Refit library for .NET Core, Xamarin and .NET
  • ['8.0.0']

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-93
Improper Neutralization of CRLF Sequences ('CRLF Injection')
The product uses CRLF (carriage return line feeds) as a special element, e.g. to separate lines or records, but it does not neutralize or incorrectly neutralizes CRLF sequences from inputs.

Timeline

Published: Nov. 4, 2024, 11:15 p.m.
Last Modified: Nov. 8, 2024, 4:15 p.m.

Status : Awaiting Analysis

CVE has been recently published to the CVE List and has been received by the NVD.

More info

Source

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.