Red Hat OpenShift AI 2.25: Deserialization of Untrusted Data
CVE-2026-18948 is a critical-severity deserialization of untrusted data vulnerability in Red Hat OpenShift AI 2.25 from Red Hat, with a CVSS 3.1 base score of 9.9 out of 10. It can be exploited remotely over the network by an attacker with a low-privileged account, without any action from a user. There is no confirmed exploitation so far. EPSS estimates a 1.08% chance of exploitation within 30 days, higher than 66% of scored CVEs.
Critical severity: a successful attack would have severe impact.
What to do
- Check which version of Red Hat OpenShift AI 2.25 you run against the affected versions below, and install the vendor's latest release.
Affected products and versions
| Vendor | Product | Affected versions | Fixed in |
|---|---|---|---|
| Red Hat | Red Hat OpenShift AI 2.25 | Not specified in the record | Not stated |
| Red Hat | Red Hat OpenShift AI 3.3 | Not specified in the record | Not stated |
| Red Hat | Red Hat OpenShift AI 3.4 | Not specified in the record | Not stated |
| Red Hat | Red Hat OpenShift AI (RHOAI) | Not specified in the record | Not 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
- LowA basic user account is enough.
- User interaction
- NoneNo action by a victim is required.
- Scope
- ChangedThe attack can reach beyond the vulnerable component into other systems.
- Confidentiality
- HighAll data handled by the component can be read.
- Integrity
- HighData or code can be modified at will.
- Availability
- HighThe component can be taken down completely.
Vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H. Scored by CNA (redhat.com).
Official description
A flaw was found in Feast. The system improperly deserializes user-defined functions (UDFs) stored in its registry, which are serialized using the 'dill' library. This allows a remote attacker to store a malicious UDF, leading to unauthenticated arbitrary code execution on the feature server in default configurations. An authenticated attacker can also achieve arbitrary code execution on the registry server by bypassing authorization checks during deserialization. This vulnerability can result in cross-tenant data access and lateral movement within the system.
Source: the CVE record as published by its numbering authority, via NVD and CVE.org.
The underlying weakness: Deserialization of Untrusted Data
The product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid.
How developers prevent this class of flaw
- If available, use the signing/sealing features of the programming language to assure that deserialized data has not been tainted. For example, a hash-based message authentication code (HMAC) could be used to ensure that data has not been modified.
- When deserializing data, populate a new object rather than just deserializing. The result is that the data flows through safe input validation and that the functions are safe.
- Explicitly define a final object() to prevent deserialization.
More Deserialization of Untrusted Data vulnerabilities (CWE-502)
Timeline
- CVE record published.
- CISA published its SSVC assessment (exploitation: none, automatable: no, technical impact: total).
- Record last changed materially (score, affected products, status or references).
References
Other references
Other vulnerabilities in Red Hat OpenShift AI 2.25
- 8.8 High severity
- 8.8 High severity
- 8.8 High severity
- 8.5 High severity
- 7.7 High severity
- 7.6 High severity
Recent Deserialization of Untrusted Data vulnerabilities
- 8.1 High severity
- 8.0 High severity
- 7.5 High severity
- 9.8 Critical severity
- 9.8 Critical severity
- 9.0 Critical severity
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