CVE-2025-29785
June 2, 2025, 5:32 p.m.
7.5
High
Description
quic-go is an implementation of the QUIC protocol in Go. The loss recovery logic for path probe packets that was added in the v0.50.0 release can be used to trigger a nil-pointer dereference by a malicious QUIC client. In order to do so, the attacker first sends valid QUIC packets from different remote addresses (thereby triggering the newly added path validation logic: the server sends path probe packets), and then sending ACKs for packets received from the server specifically crafted to trigger the nil-pointer dereference. v0.50.1 contains a patch that fixes the vulnerability. This release contains a test that generates random sequences of sent packets (both regular and path probe packets), that was used to verify that the patch actually covers all corner cases. No known workarounds are available.
Product(s) Impacted
| Vendor | Product | Versions |
|---|---|---|
| Quic-go |
|
|
Weaknesses
Common security weaknesses mapped to this vulnerability.
CWE-248
Uncaught Exception
An exception is thrown from a function, but it is not caught.
*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 | quic-go | quic-go | 0.50.0 | / | / | / | / | / | / | / |
| a | quic-go | quic-go | 0.50.1 | / | / | / | / | / | / | / |
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: June 2, 2025, 11:15 a.m.
Last Modified: June 2, 2025, 5:32 p.m.
Last Modified: June 2, 2025, 5:32 p.m.
Status : Awaiting Analysis
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.