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Red Hat OpenShift AI 2.25 · Red Hat OpenShift AI 3.3 · Red Hat OpenShift AI 3.4 · Red Hat OpenShift AI 3.5

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.

Red Hat OpenShift AI 2.25 · Red Hat OpenShift AI 3.3 · Red Hat OpenShift AI 3.4 · Red Hat OpenShift AI (RHOAI)

A flaw was found in odh-dashboard. An authenticated user of the dashboard can exploit a vulnerability related to how RoleBindings are created. The system does not properly validate the `roleRef` field, allowing a user to specify an arbitrary role, including highly privileged ones like `cluster-admin`. This can lead to privilege escalation, where an attacker gains unauthorized elevated access within their namespace and potentially persistent control over the system.

Red Hat OpenShift AI 2.25 · Red Hat OpenShift AI 3.3 · Red Hat OpenShift AI 3.4

A flaw was found in odh-dashboard. This vulnerability allows an attacker, who has compromised the dashboard's Service Account (SA) token, to exploit overly broad permissions granted to the SA. This enables the attacker to escalate their privileges to cluster-administrator level, gain access to sensitive data like credentials and keys across the entire cluster, and disrupt multi-tenant isolation.

Red Hat OpenShift AI 2.25 · Red Hat OpenShift AI 3.3 · Red Hat OpenShift AI 3.4 · Red Hat OpenShift AI (RHOAI)

A flaw was found in Feast. An authorization bypass vulnerability exists in the /materialize and /materialize-incremental endpoints. By sending a specially crafted request that omits the feature_views field, an attacker can bypass intended permission checks. This allows an unauthenticated remote attacker, or any authenticated user, to trigger a full re-materialization of all feature views. The consequence is a Denial of Service (DoS) due to data corruption and significant resource consumption across all tenants.

Red Hat OpenShift AI 2.25 · Red Hat OpenShift AI 3.3 · Red Hat OpenShift AI 3.4 · Red Hat OpenShift AI (RHOAI)

A flaw was found in Feast and feast-operator. The default configuration for both the Feast SDK and the feast-operator is "no_auth," meaning no security manager is installed. This default allows unauthenticated and unauthorized access to feature-server, registry-server, and offline-server endpoints. A remote attacker, by exploiting this missing authentication, could achieve remote code execution (RCE) by storing a malicious User-Defined Function (UDF) on the feature-server, trigger a denial of service (DoS) by forcing re-materialization of all tenant features, and gain unauthorized access to cross-tenant data.

Red Hat OpenShift AI 2.25 · Red Hat OpenShift AI 3.3 · Red Hat OpenShift AI 3.4 · Red Hat AI Inference Server

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.

Red Hat OpenShift AI 2.25 · Red Hat OpenShift AI 3.3 · Red Hat OpenShift AI 3.4 · Red Hat OpenShift AI 3.5

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.

Red Hat OpenShift AI 2.25 · Red Hat OpenShift AI 3.3 · Red Hat OpenShift AI 3.4 · Red Hat OpenShift AI 3.5

A flaw was found in ml-metadata. The statically-linked gRPC stack in ml-metadata is outdated, making it vulnerable to known HTTP/2 denial of service (DoS) issues. An in-cluster attacker, with network access to the MLMD pod, could exploit these vulnerabilities by sending specially crafted HTTP/2 requests. This could lead to a denial of service by crashing the MLMD pod, disrupting all pipeline runs in the affected namespace.

Red Hat OpenShift AI 2.25 · Red Hat OpenShift AI 3.3 · Red Hat OpenShift AI 3.4 · Red Hat OpenShift AI 3.5

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.

Red Hat OpenShift AI 2.25 · Red Hat OpenShift AI 3.3 · Red Hat OpenShift AI 3.4 · Red Hat OpenShift AI 3.5

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.

Red Hat OpenShift AI 2.25 · Red Hat OpenShift AI 3.3 · Red Hat OpenShift AI 3.4 · Red Hat OpenShift AI 3.5

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.

Red Hat OpenShift AI 2.25 · Red Hat OpenShift AI 3.3 · Red Hat OpenShift AI 3.4 · Red Hat OpenShift AI 3.5

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.

Red Hat OpenShift AI 2.25 · Red Hat OpenShift AI 3.3 · Red Hat OpenShift AI 3.4 · Red Hat OpenShift AI 3.5

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.

Red Hat OpenShift AI 2.25 · Red Hat OpenShift AI 3.3 · Red Hat OpenShift AI 3.4

A flaw was found in odh-dashboard, the web console component of Red Hat OpenShift AI (RHOAI). Due to incorrect network binding, a malicious actor within the cluster can bypass authentication and impersonate any user by providing an arbitrary access token. This allows an attacker to gain unauthorized access to the Kubernetes API, potentially leading to arbitrary code execution, privilege escalation, or information disclosure.

Red Hat OpenShift AI 2.25 · Red Hat OpenShift AI 3.4

A flaw was found in the vllm-orchestrator-gateway component. The system's production binary logs all incoming authorization headers and full chat payloads, which may contain personally identifiable information (PII) and secrets, to persistent logs. This sensitive data, including bearer tokens and chat content, can be accessed by any user with logging privileges. This vulnerability leads to information disclosure, potentially allowing an attacker to harvest credentials and sensitive conversation content.

nltk · Red Hat OpenShift AI 2.25 · Red Hat OpenShift AI 3.4 · Red Hat Exploit Intelligence

NLTK (Natural Language Toolkit) is a suite of open source Python modules, data sets, and tutorials supporting research and development in Natural Language Processing. Prior to 3.10.0-rc1, nltk.data.load() in NLTK is vulnerable to path traversal via URL-encoded path separators and traversal segments when using the nltk: URL scheme. The unsafe-path regex check is performed before url2pathname() decodes the %xx sequences (a classic decode-after-check / TOCTOU-style flaw), allowing an attacker to bypass the protection documented in NLTK's SECURITY.md and read arbitrary files from the filesystem. While literal traversal strings such as ../../../etc/passwd are correctly blocked, encoded variants such as %2fetc%2fpasswd, %2e%2e%2f..., and ..%2f..%2f slip past the regex and are subsequently decoded into a real filesystem path. This vulnerability is fixed in 3.10.0-rc1.

undici · Red Hat Cryostat 4 on RHEL 9 · Red Hat Enterprise Linux 10 · Red Hat Enterprise Linux 8

Impact: undici's ProxyAgent silently drops the requestTls option when configured with a SOCKS5 proxy URI (socks5:// or socks://). The target HTTPS connection through the SOCKS5 tunnel falls back to Node's default trust store, ignoring user-configured ca, cert, key, rejectUnauthorized, and servername settings. Applications that pin to an internal or corporate CA via requestTls.ca will, when their proxy URI is SOCKS5, get the default Mozilla CA bundle as the trust anchor instead. Any cert signed by any publicly-trusted CA for the target hostname is accepted, breaking the intended pin and enabling MITM read and tamper of the HTTPS exchange. Affected applications are those that use undici's ProxyAgent (or Socks5ProxyAgent directly) with SOCKS5 AND rely on requestTls for TLS scope restriction. The bug was introduced in undici 7.23.0 when SOCKS5 support was added. Patches: Upgrade to undici v7.28.0 or v8.5.0. Workarounds: No workaround is available within the SOCKS5 path. If a SOCKS5 proxy with TLS scope restriction is required and an upgrade is not yet possible, route the traffic through an HTTP-proxy ProxyAgent instead, where requestTls is honored correctly.

undici · Red Hat Cryostat 4 on RHEL 9 · Red Hat Enterprise Linux 10 · Red Hat Enterprise Linux 8

Impact: When using Socks5ProxyAgent, undici reuses a single connection pool across different origins without verifying that the pool's origin matches the requested origin. All requests are dispatched through the pool connected to the first origin, regardless of the intended destination. This causes cross-origin request routing: credentials and request data intended for origin B are sent to origin A, responses from the wrong origin are trusted, and HTTPS requests may be silently downgraded to HTTP. Impacted users are applications that use Socks5ProxyAgent (directly or via setGlobalDispatcher) and make requests to more than one origin. This was introduced in undici 7.23.0 via PR #4385 and affects all versions through 8.1.0. Patches: Upgrade to undici v7.26.0 or v8.2.0. Workarounds: Use a separate Socks5ProxyAgent instance per origin, or avoid using Socks5ProxyAgent with multiple origins.

undici · Red Hat Cryostat 4 on RHEL 9 · Red Hat AMQ Broker 7.13.6 · Red Hat AMQ Broker 7.14.1

Impact: The undici WebSocket client enforces maxPayloadSize on the cumulative byte count of fragments in a message but does not enforce a limit on the number of fragments. A malicious WebSocket server can stream many small or empty continuation frames that each pass per-frame and cumulative-size validation, collectively causing unbounded memory growth in the client process. The result is memory exhaustion and a denial of service. Affected applications are those using the undici WebSocket client (new WebSocket(...)) or the WebSocketStream API that can be induced to connect to an attacker-controlled or compromised WebSocket endpoint. All releases starting at undici 6.17.0 are affected. Patches: Upgrade to undici >= 6.26.0, >= 7.28.0, or >= 8.5.0. Workarounds: No workaround is available. The fix must be applied through an upgrade.

websockets ws · Red Hat Cryostat 4 on RHEL 9 · Red Hat AMQ Broker 7.13.6 · Red Hat AMQ Broker 7.14.1

ws is an open source WebSocket client and server for Node.js. All versions from 1.1.0 up to (but not including) 5.2.5, from 6.0.0 up to 6.2.4, from 7.0.0 up to 7.5.11, and from 8.0.0 up to 8.21.0 are affected by a memory exhaustion DoS vulnerability. A peer can send a high volume of exceptionally small fragments and data chunks, with modest network traffic, to force the remote peer into allocating and holding structural wrappers that consume far more memory than the default documented message-size limit, leading to process termination due to OOM. This issue has been fixed in versions 5.2.5, 6.2.4, 7.5.11, and 8.21.0.

netty · Red Hat Cryostat 4 on RHEL 9 · Red Hat AMQ Broker 7.13.6 · Red Hat AMQ Broker 7.14.1

Netty is a network application framework for development of protocol servers and clients. Prior to versions 4.1.135.Final and 4.2.15.Final, SimpleTrustManagerFactory.engineGetTrustManagers() and related paths wrap any user-supplied plain X509TrustManager in X509TrustManagerWrapper, which extends X509ExtendedTrustManager but implements the 3-arg checkServerTrusted(chain, authType, SSLEngine) by discarding the SSLEngine and calling the 2-arg delegate. Because the object now IS an X509ExtendedTrustManager, neither SunJSSE's internal AbstractTrustManagerWrapper nor Netty's own OpenSslX509TrustManagerWrapper will re-wrap it to add endpoint-identification. Consequently, even though Netty 4.2 sets endpointIdentificationAlgorithm="HTTPS" by default, a client built with `SslContextBuilder.forClient().trustManager(somePlainX509TrustManager)` performs no hostname verification at all. Versions 4.1.135.Final and 4.2.15.Final patch the issue.

netty · Red Hat Cryostat 4 on RHEL 9 · Red Hat AMQ Broker 7.14.1 · Red Hat Build of Apache Camel 3.33 for Quarkus 3.33.2.SP1

Netty is a network application framework for development of protocol servers and clients. Prior to versions 4.1.135.Final and 4.2.15.Final, the HAProxy PROXY protocol v2 codec in netty leaks native or heap memory on every connection when a client sends a syntactically valid header containing nested `PP2_TYPE_SSL` TLVs (type-length-value records) at depth two or greater. The leak occurs on the successful parse path — no exception is thrown, the message fires downstream, the decoder removes itself, and the application releases the `HAProxyMessage` normally. Yet the underlying cumulation buffer (a pooled, potentially direct `ByteBuf` allocated by the channel) remains permanently pinned. Versions 4.1.135.Final and 4.2.15.Final patch the issue.

netty · Red Hat Cryostat 4 on RHEL 9 · Red Hat AMQ Broker 7.14.1 · Red Hat Build of Apache Camel 3.33 for Quarkus 3.33.2.SP1

Netty is a network application framework for development of protocol servers and clients. In netty-codec-http2 prior to versions 4.1.135.Final and 4.2.15.Final, the `DelegatingDecompressorFrameListener` class orchestrates HTTP/2 decompression by embedding a per-stream `EmbeddedChannel` that runs the appropriate decompression codec (gzip, deflate, zstd) and forwards decompressed chunks to a wrapped listener. Each decompressed chunk is a pooled `ByteBuf` handed to an anonymous `ChannelInboundHandlerAdapter` tail handler, which becomes the sole owner responsible for releasing it. A remote peer could send frames that would result in the flow-controller throwing and so trigger a resource leak which at the end might take down the whole JVM due OOME. Versions 4.1.135.Final and 4.2.15.Final patch the issue.

netty · Red Hat Cryostat 4 on RHEL 9 · Red Hat AMQ Broker 7.13.6 · Red Hat AMQ Broker 7.14.1

Netty is a network application framework for development of protocol servers and clients. Prior to versions 4.1.135.Final and 4.2.15.Final, SslClientHelloHandler.decode() reads the 24-bit TLS handshake length and, when the ClientHello does not fit in the first record, eagerly allocates `ctx.alloc().buffer(handshakeLength)` (line 161). The guard at line 140 is `handshakeLength > maxClientHelloLength && maxClientHelloLength != 0`, and the commonly-used SniHandler/AbstractSniHandler constructors (SniHandler(Mapping), SniHandler(AsyncMapping), AbstractSniHandler()) pass maxClientHelloLength=0 and handshakeTimeoutMillis=0, so the length guard is disabled and no timeout is scheduled. A 16 MiB request exceeds the default pooled chunk size and becomes a huge/unpooled allocation performed immediately. The buffer is retained in the handler until the channel closes. Versions 4.1.135.Final and 4.2.15.Final patch the issue.

netty · Red Hat Cryostat 4 on RHEL 9 · Red Hat AMQ Broker 7.14.1 · Red Hat Build of Apache Camel 3.33 for Quarkus 3.33.2.SP1

Netty is a network application framework for development of protocol servers and clients. In netty-codec-haproxy prior to versions 4.1.135.Final and 4.2.15.Final, when decoding a PP2_TYPE_SSL TLV, HAProxyMessage.readNextTLV() first calls `header.retainedSlice(header.readerIndex(), length)` and only then reads the 1-byte client field and 4-byte verify field. If the attacker sets the TLV length below 5, the subsequent readByte/readInt throws IndexOutOfBoundsException. HAProxyMessageDecoder only catches HAProxyProtocolException around this call, so the IOOBE propagates and the retained slice on the pooled cumulation buffer is never released. Versions 4.1.135.Final and 4.2.15.Final patch the issue.

netty · Red Hat Cryostat 4 on RHEL 9 · Red Hat AMQ Broker 7.13.6 · Red Hat AMQ Broker 7.14.1

Netty is a network application framework for development of protocol servers and clients. In netty-handler prior to versions 4.1.135.Final and 4.2.15.Final, an attacker can bypass IPv6 subnet rules due to an incorrect masking operation in IpSubnetFilterRule.compareTo(). Valid public IP addresses can bypass the restrictions. Versions 4.1.135.Final and 4.2.15.Final patch the issue.

keras-team/keras · Red Hat OpenShift AI 2.25 · Red Hat OpenShift AI (RHOAI) · Keras keras

Keras versions prior to 3.14.0 are vulnerable to a path traversal issue in the archive extraction utilities located in `keras/src/utils/file_utils.py`. The functions `filter_safe_tarinfos()` and `filter_safe_zipinfos()` validate archive member paths against the process current working directory (CWD) instead of the actual extraction destination. When the process runs with CWD set to `/`, which is common in Docker containers, CI/CD runners, and Jupyter environments, the validation boundary becomes the filesystem root, allowing traversal paths to bypass the security check. Additionally, the zip filter contains a bug that causes an `AttributeError` when a blocked entry is encountered, leading to incomplete extraction. Furthermore, Python 3.11 installations lack the `filter="data"` safety net, leaving them entirely reliant on the flawed CWD-based filter. Exploitation of this vulnerability can result in arbitrary file writes outside the intended extraction directory, enabling attackers to overwrite configuration files, inject malicious code, or corrupt machine learning datasets and pipelines.