CyberSecBulletin
CVE-2026-18611NVD status: Awaiting Analysis

Red Hat OpenShift AI 2.25: Use of Cryptographically Weak Pseudo-Random Number Generator (PRNG)

Published Updated By the CyberSecBulletin desk

CVE-2026-18611 is a high-severity use of cryptographically weak pseudo-random number generator (PRNG) vulnerability in Red Hat OpenShift AI 2.25 from Red Hat, with a CVSS 3.1 base score of 7.5 out of 10. It can be exploited remotely over the network by an unauthenticated attacker, without any action from a user. There is no confirmed exploitation so far. EPSS estimates a 0.61% chance of exploitation within 30 days, which is low compared with other CVEs.

Next patch cycle

High severity with no evidence of exploitation so far.

What to do

  1. Check which version of Red Hat OpenShift AI 2.25 you run against the affected versions below, and install the vendor's latest release.
  2. Until you can update, restrict network access to the affected service so it is not reachable from untrusted networks.

Affected products and versions

VendorProductAffected versionsFixed in
Red HatRed Hat OpenShift AI 2.25Not specified in the recordNot stated
Red HatRed Hat OpenShift AI 3.3Not specified in the recordNot stated
Red HatRed Hat OpenShift AI 3.4Not specified in the recordNot stated
Red HatRed Hat OpenShift AI 3.5Not specified in the recordNot stated

Version data comes from the organisation that assigned the CVE. Confirm against the vendor advisory before deciding you are unaffected.

How the severity score breaks down

Attack vector
NetworkCan be exploited remotely over a network, including the internet.
Attack complexity
LowNo special conditions are needed; the attack works reliably.
Privileges required
NoneNo account or login is needed.
User interaction
NoneNo action by a victim is required.
Scope
UnchangedImpact stays within the vulnerable component.
Confidentiality
HighAll data handled by the component can be read.
Integrity
NoneNothing can be modified.
Availability
NoneAvailability is not affected.

Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N. Scored by CNA (redhat.com).

Official description

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.

Source: the CVE record as published by its numbering authority, via NVD and CVE.org.

The underlying weakness: Use of Cryptographically Weak Pseudo-Random Number Generator (PRNG)

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

How developers prevent this class of flaw

  • Use functions or hardware which use a hardware-based random number generation for all crypto. This is the recommended solution. Use CyptGenRandom on Windows, or hw_rand() on Linux.

More Use of Cryptographically Weak Pseudo-Random Number Generator (PRNG) vulnerabilities (CWE-338)

Timeline

  1. CVE record published.
  2. CISA published its SSVC assessment (exploitation: none, automatable: yes, technical impact: partial).
  3. Record last changed materially (score, affected products, status or references).

References

Other vulnerabilities in Red Hat OpenShift AI 2.25

All Red Hat OpenShift AI 2.25 vulnerabilities

Recent Use of Cryptographically Weak Pseudo-Random Number Generator (PRNG) vulnerabilities

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