Unauth Data Science Pipelines Operator: Weak PRNG Exposes MariaDB/MinIO Creds
CVE-2026-18611 Published on August 10, 2026

Data-science-pipelines-operator: dspo: cryptographically weak secret generation (math/rand) for db and s3 credentials
A flaw was found in the Data Science Pipelines Operator. This vulnerability allows an unauthenticated attacker to derive sensitive credentials, such as MariaDB root/user passwords and MinIO access/secret keys, if they can access the MinIO Route or MariaDB Service. The flaw occurs because the operator uses a cryptographically weak pseudo-random number generator (PRNG) to generate these credentials, making them predictable. Successful exploitation could lead to unauthorized access to all pipeline artifacts and metadata, resulting in significant information disclosure.

Vendor Advisory Vendor Advisory Vendor Advisory Vendor Advisory NVD

Vulnerability Analysis

CVE-2026-18611 can be exploited with network access, and does not require authorization privileges or user interaction. This vulnerability is considered to have a low attack complexity. The potential impact of an exploit of this vulnerability is considered to have a high impact on confidentiality, with no impact on integrity and availability.

Attack Vector:
NETWORK
Attack Complexity:
LOW
Privileges Required:
NONE
User Interaction:
NONE
Scope:
UNCHANGED
Confidentiality Impact:
HIGH
Integrity Impact:
NONE
Availability Impact:
NONE

Timeline

Reported to Red Hat.

Made public. 7 days later.

Weakness Type

What is a PRNG Vulnerability?

The product uses a Pseudo-Random Number Generator (PRNG) in a security context, but the PRNG's algorithm is not cryptographically strong.

CVE-2026-18611 has been classified to as a PRNG vulnerability or weakness.


Products Associated with CVE-2026-18611

Want to know whenever a new CVE is published for Red Hat Openshift Ai? stack.watch will email you.

 

Affected Versions

Red Hat OpenShift AI 2.25: Red Hat OpenShift AI 3.3: Red Hat OpenShift AI 3.4: Red Hat OpenShift AI 3.4: