| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| A flaw was found in Foreman. The template revision endpoint does not enforce object-level authorization when retrieving an audited template revision. An authenticated, low privileged user with a template-related permission, such as view_ptables, can obtain historical template contents belonging to another organization or location by supplying the corresponding audit ID. This can result in unauthorized disclosure of historical template contents, which may contain sensitive configuration information, credentials, or other secrets. The REST API revision endpoints correctly restrict this lookup. |
| A stack-based buffer overflow vulnerability exists in BlueZ, the Linux Bluetooth protocol stack. A remote user within Bluetooth radio range can send a specially crafted Extended Inquiry Response (EIR) packet that causes a buffer overflow when the target device performs Bluetooth discovery. This vulnerability can lead to a Denial of Service (DoS) by crashing the bluetoothd service and may allow for arbitrary code execution. |
| A server-side request forgery (SSRF) vulnerability was found in galaxy_ng, the Ansible Galaxy server plugin for Pulp. An authenticated user with namespace management permissions can set a namespace avatar URL to an arbitrary address, including internal networks, loopback, or cloud instance metadata endpoints. A background worker fetches that URL without checking the destination, which lets the attacker probe internal services and enumerate reachable IP addresses. The HTTP client is also configured without an overall timeout, so a slow or non-responsive target can pin workers and cause a denial of service. |
| A path traversal vulnerability was found in AWX's project archive extraction. The project_archive action plugin extracts zip and tar archive members by joining the project directory path with the member filename without performing path normalization, boundary validation, or rejecting directory traversal sequences. A malicious archive containing members with path traversal components can write files to arbitrary locations on the execution node's filesystem outside the intended project directory. An attacker who controls the archive content, either through a compromised upstream source, a malicious archive URL, or a man-in-the-middle attack on a plain HTTP connection, can achieve arbitrary file writes as the user performing the extraction, potentially leading to remote code execution through mechanisms such as cron files, SSH authorized keys, or playbook content injection. |
| A flaw was found in CRI-O's container-creation environment-variable handling
(`mergeEnvs` in `server/utils.go`, consumed by `setupContainerEnvironmentAndWorkdir` in
`server/container_create.go`). When a `CreateContainer` request supplies a `nil` CRI
`Envs` field, CRI-O falls back to using the target OCI image's `config.Env` entries
unfiltered, in contrast to the normal merge path, which validates each entry for a
`key=value` form before use. An OCI image whose `config.Env` contains an entry with no
`=` character (e.g. a bare `NOEQUALS` string) causes CRI-O to split that entry into a
single-element slice and then index its second element, which is out of range. This
triggers an unrecovered Go runtime panic in the `crio` daemon process, crashing it and
terminating the container-runtime service for all workloads on the node until it is
restarted. |
| A flaw was found in Undertow. A remote attacker could exploit this vulnerability by sending specially crafted WebSocket messages with permessage-deflate negotiated. This could lead to excessive memory consumption due to the PerMessageDeflateFunction.largerBuffer() method using exponential doubling, resulting in a Denial of Service (DoS) for the affected application. |
| A flaw was found in Data Science Pipelines. A restricted user, or tenant, can exploit an improper authorization vulnerability in the setDefaultServiceAccount function. By specifying a more privileged ServiceAccount (SA) during a CreateRun request, an attacker can bypass authorization checks. This allows the tenant to run their containers with elevated privileges, potentially leading to the disclosure of sensitive information (secrets) and the ability to execute commands within other users' pods. |
| 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 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 `guardrails-detectors`, a component of Red Hat OpenShift AI. This vulnerability, known as Regular Expression Denial of Service (ReDoS), allows a remote attacker to provide specially crafted regular expressions to the public detection API. This can cause catastrophic backtracking, leading to a worker process consuming 100% CPU indefinitely and resulting in a denial of service for the entire guardrails-mediated LLM pipeline. |
| A remote code execution vulnerability was found in libaom, the reference AV1 codec implementation. Insufficient bounds validation in the AV1 encoder's SVC (Scalable Video Coding) layer ID control allows an attacker to supply crafted video frame pixels that overlap with internal encoder layer context structures. In fork-based video processing services, an attacker can use this to hijack the cyclic refresh map pointer, brute-force the process base address via a crash oracle, and redirect control flow to achieve arbitrary command execution. Exploitation requires the target service to use libaom with SVC encoding enabled and accept attacker-supplied video frames. |
| A heap-buffer-overflow read vulnerability was found in libaom, the reference AV1 codec implementation. A missing bounds check in the SVC (Scalable Video Coding) layer ID control function allows setting a spatial_layer_id exceeding the configured number of layers. This causes an out-of-bounds heap read of approximately 40,728 bytes when computing a layer context array index. An attacker who can influence SVC encoder parameters in a network-facing service could exploit this for information disclosure (heap content leak) or denial of service (segmentation fault from hitting unmapped memory). |
| An arbitrary address write vulnerability was found in libaom, the reference AV1 codec implementation. A missing bounds check in the SVC (Scalable Video Coding) layer ID control function allows an attacker to inject an arbitrary pointer into the cyclic refresh map field via crafted image pixel values. The encoder then writes approximately 1,200 bytes at the attacker-controlled address. This is fully deterministic and does not require a separate information leak. An attacker who can supply frames to a network-facing libaom encoder with SVC enabled could exploit this for denial of service or potential code execution. |
| A heap buffer overflow vulnerability was found in libaom, the reference AV1 codec implementation. A flaw in the AV1 encoder's Look-Ahead Processing (LAP) mode causes the first-pass stats ring buffer wrap-around guard to be bypassed when g_lag_in_frames is set to 1 or higher. This results in a 232-byte out-of-bounds write on every encoded frame after the second, corrupting adjacent heap objects. An attacker who can influence encoder configuration in a transcoding service or WebRTC session could exploit this to cause a denial of service (process crash) or potentially achieve code execution. |
| 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 Red Hat OpenShift AI (RHOAI) overlay for the training operator. The RHOAI overlay incorrectly aggregates `trainjobs` management permissions into the native Kubernetes `edit ClusterRole`. This allows any user with `edit ClusterRole` permissions in a namespace to create, modify, and delete `TrainJobs`. When combined with a separate vulnerability (TRN-01) that permits arbitrary pod configurations, a remote attacker with namespace editor privileges could exploit this to escalate privileges, potentially leading to arbitrary code execution. |
| 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 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 the Data Science Pipelines Operator (DSPO). A namespace editor can exploit a vulnerability in the spec.database.customExtraParams field, which allows for the injection of dangerous parameters into the MySQL Data Source Name (DSN) string. By manipulating these parameters, an attacker can enable LOCAL INFILE functionality and exfiltrate sensitive files, such as the service account token, from the operator pod. This can lead to privilege escalation, allowing a namespace editor to gain cluster-admin privileges. |
| 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. |
