CVE-2025-32433
April 16, 2025, 10:15 p.m.
10.0
Critical
Description
Erlang/OTP is a set of libraries for the Erlang programming language. Prior to versions OTP-27.3.3, OTP-26.2.5.11, and OTP-25.3.2.20, a SSH server may allow an attacker to perform unauthenticated remote code execution (RCE). By exploiting a flaw in SSH protocol message handling, a malicious actor could gain unauthorized access to affected systems and execute arbitrary commands without valid credentials. This issue is patched in versions OTP-27.3.3, OTP-26.2.5.11, and OTP-25.3.2.20. A temporary workaround involves disabling the SSH server or to prevent access via firewall rules.
Product(s) Impacted
| Vendor | Product | Versions |
|---|---|---|
| Erlang |
|
|
Weaknesses
Common security weaknesses mapped to this vulnerability.
CWE-306
Missing Authentication for Critical Function
The product does not perform any authentication for functionality that requires a provable user identity or consumes a significant amount of 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 | erlang | otp | <27.3.3 | / | / | / | / | / | / | / |
| a | erlang | otp | <26.2.5.11 | / | / | / | / | / | / | / |
| a | erlang | otp | <25.3.2.20 | / | / | / | / | / | / | / |
References
Tags
CVSS Score
CVSS Data - 3.1
- Attack Vector: NETWORK
- Attack Complexity: LOW
- Privileges Required: NONE
- Scope: CHANGED
- Confidentiality Impact: HIGH
- Integrity Impact: HIGH
- Availability Impact: HIGH
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H
Timeline
Published: April 16, 2025, 10:15 p.m.
Last Modified: April 16, 2025, 10:15 p.m.
Last Modified: April 16, 2025, 10:15 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.