| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| A flaw was found in Redis community. The cluster bus packet parser, responsible for handling PING, PONG, and MEET packets, fails to properly validate string-carrying extensions for null-termination. This oversight allows a remote attacker to craft a malicious packet, leading to an out-of-bounds read when the packet's payload is processed. Successful exploitation of this vulnerability could result in the disclosure of sensitive information or a remote denial of service (DoS). |
| A vulnerability in CRI-O checkpoint restore allows a user who can create a pod from a malicious checkpointed container to bypass the destination Kubernetes security context. The restored process may retain credentials, Linux capabilities, no_new_privs, and seccomp state from the checkpoint instead of enforcing the destination configuration. This can allow execution with elevated privileges across the container security boundary.
Affected upstream supported versions are CRI-O 1.34 and later. Downstream Red Hat products are affected from OCP 4.17 onward. Fixes have been applied to supported branches but are not yet released.
Exploitation requires permission to create a pod from a malicious checkpoint image and checkpoint restore functionality to be available. |
| 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. |
| A flaw was found in the RHOAI training-operator. This vulnerability allows a user with standard edit or admin roles in any Kubernetes namespace to escalate their privileges. Through the creation of training jobs, an attacker can impersonate service accounts, access the host filesystem, and potentially execute arbitrary code remotely. This issue arises from the aggregation of training job permissions onto native Kubernetes edit and admin ClusterRoles, coupled with unrestricted PodTemplateSpec passthrough. |
| A flaw was found in the Data Science Pipelines Operator (DSPO). The operator's ClusterRole, which defines its permissions, includes extensive privileges beyond what is necessary for its operation. These excessive permissions, such as the ability to execute commands within pods and manage cluster-wide roles, could be exploited. If the DSPO pod were compromised, an attacker could leverage these privileges to gain full administrative control over the entire Kubernetes cluster. |
| A flaw was found in the TrustyAI Service (TAS) deployment. This vulnerability allows any pod on the cluster network to bypass authentication and directly access the TAS backend API. An attacker can exploit this to read, tamper with, or delete monitoring data and configurations, and inject arbitrary data into the service, potentially disrupting tenant operations. |
| A flaw was found in the trustyai-service-operator's LMEvalJob controller. An authenticated user within the cluster can exploit this vulnerability by configuring a sidecar container to bypass existing security policies. This allows the user to enable and execute untrusted remote code, leading to arbitrary code execution within the cluster. |
| A flaw was found in the foreman_ansible plugin's Ansible inventory API. The controller builds its host query using an unscoped Host.where call that does not enforce the search filter associated with the caller's view_hosts permission. An authenticated user whose host visibility is restricted by a permission filter can supply arbitrary host IDs within their organization and receive the full Ansible inventory for those hosts, including parameter values marked as hidden. |
| A flaw was found in the foreman_ansible plugin's Ansible override values API. The destroy action resolves the target LookupValue record by ID without verifying it belongs to an AnsibleVariable the caller is authorized to edit. An authenticated user with the edit_ansible_variables permission can delete any LookupValue by ID, including override values for Ansible variables outside their permission filter scope and override values belonging to Puppet smart class parameters. |
| A flaw was found in the foreman_remote_execution plugin's template invocations controller. The show_template_invocation_by_host action resolves the job invocation by ID without evaluating the caller's view_job_invocations permission filter against the record. An authenticated user whose job invocation visibility is restricted by a permission filter can enumerate job invocation IDs and read the live output, rendered script, and input values for other users' job invocations within their own organizations. |
| A flaw was found in Data Science Pipelines (DSP). An attacker with namespace editor privileges can bypass security hardening by submitting a malicious Argo Workflow through the V1 API path. This allows the API server to create pods with elevated privileges, acting as a 'confused deputy' on behalf of the attacker. Successful exploitation grants the attacker node-root access, enabling arbitrary code execution and full control over the underlying node. |
| A flaw was found in odh-dashboard in Red Hat OpenShift AI. The backend-for-frontend route GET /api/nim-serving/:nimResource reads Kubernetes Secrets using the dashboard service account and returns the full Secret object, including .data, without an authorization check. Any authenticated dashboard user can retrieve the cluster NVIDIA NGC API key Secret (apiKeySecret) and the NIM image pull secret (nimPullSecret). Create and delete of the same NIM credential are admin-gated; the read path is not. This is missing authorization (CWE-862) and insufficiently protected credentials (CWE-522). It is distinct from CVE-2026-5483 (service-account token leak in the Kubernetes client response wrapper on the same route) and CVE-2026-16456 (odh-model-controller cross-namespace confused deputy). |
| A flaw was found in the jwcrypto library, which is used for implementing Javascript Object Signing and Encryption (JOSE) standards. The issue occurs when the library verifies a General JSON Serialization JWS using a set of keys. Due to a coding error, the library fails to correctly identify the specific key ID (kid) and may instead accept a signature made by any valid key in the set. This can allow an attacker with a valid key to bypass authorization checks in applications that rely on the key ID to identify specific tenants or users. |
| A flaw was found in jwcrypto. A remote attacker can send a specially crafted JSON Web Encryption (JWE) token containing numerous period delimiters. This malformed token can force the JWE.deserialize() function to allocate excessive memory, leading to a MemoryError. This issue results in a denial of service (DoS) for services that process untrusted JWE values. |
| A flaw was found in FFmpeg. The tdsc_load_cursor() function writes beyond
the bounds of a heap-allocated buffer when processing crafted TDSC cursor
data. A remote attacker could exploit this by supplying a specially crafted
video file, potentially leading to a denial of service or arbitrary code
execution. |
| A flaw was found in Katello where the Content View Filter Rules API does not properly enforce authorization on the parent Content View Filter. An authenticated, low-privileged user with Content View permissions in one organization may be able to access and modify filter rules belonging to a Content View Filter in another organization by supplying that filter's identifier. This can result in unauthorized disclosure of filter-rule information and unauthorized changes to unpublished Content View filter configuration. |
| A flaw was found in the maas-api and maas-controller ServiceAccounts within Red Hat OpenShift AI. These ServiceAccounts are granted cluster-wide permissions that exceed their operational requirements. An attacker who compromises the identity of these ServiceAccounts, either through a remote code execution vulnerability or by creating a malicious pod in the same namespace, could exploit these excessive permissions. This could lead to full cluster administrator privileges through the creation of new ClusterRoleBindings or the disclosure of sensitive information by accessing all secrets across the cluster. |
| 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. |
| A flaw was found in the MaaS API. This vulnerability allows any pod within the cluster to bypass the Kuadrant AuthPolicy gateway by forging HTTP headers, specifically `X-MaaS-Username` and `X-MaaS-Group`, which are trusted verbatim. This lack of first-party authentication enables an attacker to gain unauthorized access and escalate privileges. The concrete consequences include the ability to mint Kubernetes ServiceAccount tokens in other tenants' namespaces, revoke API keys, and exfiltrate sensitive model access configuration. |
| A flaw was found in the Red Hat OpenShift AI (RHOAI) MaaS Gateway. Improper configuration of the Gateway in a model-serving context allows a standard user with low privileges to intercept, read, log, and alter all MaaS model traffic. This includes sensitive information such as access keys, input prompts, and outputs, leading to significant information disclosure and data tampering. |
