Veille CVE

Recherche « Red Hat OpenShift AI 2.25 »

57 CVE

  1. CVE-2026-86332 6.5 Moyenne

    Red Hat OpenShift AI 2.25 · Red Hat OpenShift AI 3.5 · Red Hat OpenShift AI (RHOAI)

    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).

  2. CVE-2026-18982 8.8 Élevée

    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.

  3. CVE-2026-18950 8.8 Élevée

    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.

  4. CVE-2026-18949 8.8 Élevée

    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.

  5. CVE-2026-18948 9.9 Critique

    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. 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.

  6. CVE-2026-18947 8.5 Élevée

    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.

  7. CVE-2026-18942 5.5 Moyenne

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

    A flaw was found in the Feast operator. A malicious tenant could inject arbitrary code into their feature repository. This code would be executed by an automated process with elevated privileges, allowing the tenant to steal sensitive credentials. This could lead to a direct escalation of privileges, granting the tenant administrative control over the Kubernetes cluster.

  8. CVE-2026-18941 7.7 Élevée

    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.

  9. CVE-2026-18621 7.6 Élevée

    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.

  10. CVE-2026-18620 7.1 Élevée

    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.

  11. CVE-2026-18618 7.5 Élevée

    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.

  12. CVE-2026-18617 8.8 Élevée

    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.

  13. CVE-2026-18611 7.5 Élevée

    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.

  14. CVE-2026-18608 8.7 Élevée

    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.

  15. CVE-2026-16456 6.5 Moyenne

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

    A flaw was found in the `odh-model-controller`. An authenticated user with permissions to create custom resources can exploit a vulnerability in the `loadSecret` function. This function improperly reads the Secret namespace from user-controlled input without validation. This allows an attacker to read sensitive API keys and cloud credentials from other namespaces, leading to information disclosure.

  16. CVE-2026-15581 8.0 Élevée

    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.

  17. CVE-2026-15467 8.1 Élevée

    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.

  18. CVE-2026-16745 8.8 Élevée

    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.

  19. CVE-2026-15574 7.5 Élevée

    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.

  20. CVE-2026-15143 9.3 Critique

    Red Hat OpenShift AI 2.25 · Red Hat OpenShift AI 3.4

    A flaw was found in the file_type content detector of guardrails-detectors. This vulnerability allows a remote attacker to supply an arbitrary XML Schema Definition (XSD) string, which is processed without proper restrictions. This can lead to server-side requests to arbitrary URLs or local file reads, potentially resulting in sensitive information disclosure, such as cloud provider credentials or access to internal network services.

  21. CVE-2026-15378 9.3 Critique

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

    A flaw was found in the `guardrails-detectors` component. This vulnerability allows a remote attacker to perform a blind Server-Side Request Forgery (SSRF) by submitting a specially crafted XML Schema Definition (XSD) string. This can lead to unauthorized access to sensitive information, including credentials from cloud metadata services, Kubernetes API, internal MinIO, and other internal network endpoints. Additionally, it enables local file reads of critical data such as service account tokens and pod secrets.

  22. CVE-2026-15154 6.5 Moyenne

    Red Hat OpenShift AI 2.25 · Red Hat OpenShift AI 3.3 · Red Hat OpenShift AI 3.4 · Redhat openshift ai

    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.

  23. CVE-2026-48746 9.1 Critique

    vllm-project vllm · Red Hat AI Inference Server 3.2 · Red Hat AI Inference Server 3.3 · Red Hat Ansible Automation Platform 2.6

    vLLM is an inference and serving engine for large language models (LLMs). From 0.3.0 until 0.22.0, a vulnerability in ASGI web servers and starlette's trust on those web servers enables an authentication bypass of the OpenAI API AuthenticationMiddleware. It allows to use the API without providing the configured VLLM_API_KEY or --api-key. This vulnerability is fixed in 0.22.0.

  24. CVE-2026-54293 7.5 Élevée

    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.

  25. CVE-2026-9697 7.4 Élevée

    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.

  26. CVE-2026-6734 8.8 Élevée

    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.

  27. CVE-2026-12151 7.5 Élevée

    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.

  28. CVE-2026-48779 7.5 Élevée

    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.

  29. CVE-2026-50010 7.5 Élevée

    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.

  30. CVE-2026-48059 7.5 Élevée

    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.

  31. CVE-2026-48043 7.5 Élevée

    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.

  32. CVE-2026-47691 10.0 Critique

    netty · Red Hat Cryostat 4 on RHEL 9 · Red Hat Build of Apache Camel 3.33 for Quarkus 3.33.2.SP1 · Red Hat build of Apache Camel 4.18.1.P1 for Spring Boot 3.5.16

    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, Netty's `DnsResolveContext` insufficiently validates the bailiwick of NS records, enabling DNS Cache Poisoning. An attacker controlling an authoritative name server for a subdomain can poison the cache for parent domains (like `.co.uk`). In `io.netty.resolver.dns.DnsResolveContext.AuthoritativeNameServerList#add` method accepts any NS record from the AUTHORITY section as long as the record's name is a suffix of the questionName. Subsequently, the `handleWithAdditional` method caches the associated A records from the ADDITIONAL section directly into the `authoritativeDnsServerCache` under the parent domain's key. This bypasses standard bailiwick rules, where a server authoritative for a subdomain should not be trusted to provide authoritative records for its parent. The poisoned cache is then used for all future resolutions under the parent domain's key. Versions 4.1.135.Final and 4.2.15.Final patch the issue.

  33. CVE-2026-45674 10.0 Critique

    netty · Red Hat Cryostat 4 on RHEL 9 · Red Hat Build of Apache Camel 3.33 for Quarkus 3.33.2.SP1 · Red Hat build of Apache Camel 4.18.1.P1 for Spring Boot 3.5.16

    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, Netty's DnsResolveContext fails to validate the origin (bailiwick) of CNAME records in DNS responses. Versions 4.1.135.Final and 4.2.15.Final patch the issue.

  34. CVE-2026-45416 7.5 Élevée

    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.

  35. CVE-2026-44893 7.5 Élevée

    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.

  36. CVE-2026-44249 8.1 Élevée

    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.

  37. CVE-2026-11816 8.1 Élevée

    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.

  38. CVE-2026-5241 9.6 Critique

    huggingface/transformers · Red Hat OpenShift AI 2.25 · Red Hat OpenShift AI 3.3 · Red Hat OpenShift AI 3.4

    A vulnerability in the LightGlue model loading path of huggingface/transformers version 5.2.0 allows an attacker-controlled model repository to execute arbitrary code during model initialization. The issue arises because the `trust_remote_code` parameter, intended to prevent remote code execution, is overridden by untrusted serialized configuration data in a nested code path. Specifically, when loading a LightGlue model using `AutoModel.from_pretrained()` with `trust_remote_code=False`, the `LightGlueConfig` reads the `trust_remote_code` value from the untrusted `config.json` file and propagates it into nested `AutoConfig.from_pretrained()` calls. This results in the execution of attacker-provided Python modules, even when the victim explicitly disables remote code execution. The vulnerability poses a high risk for environments such as API inference servers, research notebooks, CI/CD pipelines, and model evaluation workers, potentially leading to credential theft, lateral movement, or persistence/backdoor deployment.

  39. CVE-2026-34993 7.3 Élevée

    aio-libs aiohttp · Red Hat Ansible Automation Platform 2.5 for RHEL 8 · Red Hat Ansible Automation Platform 2.5 for RHEL 9 · Red Hat Ansible Automation Platform 2.6 for RHEL 9

    AIOHTTP is an asynchronous HTTP client/server framework for asyncio and Python. Prior to version 3.14.0, using ``CookieJar.load()`` with untrusted input may allow arbitrary code execution. Most applications using this function will be doing so with the user's own data, so this is unlikely to affect many applications. Version 3.14.0 patches the issue. If an application does allow attacker controlled files to be loaded, a workaround on older releases would be to sanitize the files before loading.

  40. CVE-2026-8643 5.5 Moyenne

    Python Packaging Authority pip · Red Hat Ansible Automation Platform 2.5 for RHEL 8 · Red Hat Ansible Automation Platform 2.5 for RHEL 9 · Red Hat Ansible Automation Platform 2.6 for RHEL 9

    pip would treat console_scripts and gui_scripts as paths instead of file names without sanitizing the resolved absolute path to the installation directory, leading to entry points being installed outside the installation directory.

  41. CVE-2026-48526 7.4 Élevée

    jpadilla pyjwt · Red Hat Ansible Automation Platform 2.5 for RHEL 8 · Red Hat Ansible Automation Platform 2.5 for RHEL 9 · Red Hat Ansible Automation Platform 2.6 for RHEL 9

    PyJWT is a JSON Web Token implementation in Python. Prior to 2.13.0, when the verifier is decoding JSON Web Tokens, while supporting both asymmetric and HMAC algorithms, the library does not validate use of JSON Web Keys in HMAC algorithm, allowing attacker to use the issuer public key as the secret key for HMAC algorithm. This vulnerability is fixed in 2.13.0.

  42. CVE-2026-45736 7.5 Élevée

    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. Prior to 8.20.1, the websocket.close() implementation is vulnerable to uninitialized memory disclosure when a TypedArray is passed as the reason argument. This vulnerability is fixed in 8.20.1.

  43. CVE-2026-42587 7.5 Élevée

    netty · io.netty netty-codec-http · io.netty netty-codec-http2 · Red Hat Cryostat 4 on RHEL 9

    Netty is an asynchronous, event-driven network application framework. Prior to 4.2.13.Final and 4.1.133.Final, HttpContentDecompressor accepts a maxAllocation parameter to limit decompression buffer size and prevent decompression bomb attacks. This limit is correctly enforced for gzip and deflate encodings via ZlibDecoder, but is silently ignored when the content encoding is br (Brotli), zstd, or snappy. An attacker can bypass the configured decompression limit by sending a compressed payload with Content-Encoding: br instead of Content-Encoding: gzip, causing unbounded memory allocation and out-of-memory denial of service. The same vulnerability exists in DelegatingDecompressorFrameListener for HTTP/2 connections. This vulnerability is fixed in 4.2.13.Final and 4.1.133.Final.

  44. CVE-2026-42584 9.1 Critique

    netty · io.netty netty-codec-http · Red Hat Cryostat 4 on RHEL 9 · Red Hat AMQ Broker 7.13.6

    Netty is an asynchronous, event-driven network application framework. Prior to 4.2.13.Final and 4.1.133.Final, HttpClientCodec pairs each inbound response with an outbound request by queue.poll() once per response, including for 1xx. If the client pipelines GET then HEAD and the server sends 103, then 200 with GET body, then 200 for HEAD, the queue pairs HEAD with the first 200. The HEAD rule then skips reading that message’s body, so the GET entity bytes stay on the stream and the following 200 is parsed from the wrong offset. This vulnerability is fixed in 4.2.13.Final and 4.1.133.Final.

  45. CVE-2026-42581 9.8 Critique

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

    Netty is an asynchronous, event-driven network application framework. Prior to 4.2.13.Final and 4.1.133.Final, HttpObjectDecoder strips a conflicting Content-Length header when a request carries both Transfer-Encoding: chunked and Content-Length, but only for HTTP/1.1 messages. The guard is absent for HTTP/1.0. An attacker that sends an HTTP/1.0 request with both headers causes Netty to decode the body as chunked while leaving Content-Length intact in the forwarded HttpMessage. Any downstream proxy or handler that trusts Content-Length over Transfer-Encoding will disagree on message boundaries, enabling request smuggling. This vulnerability is fixed in 4.2.13.Final and 4.1.133.Final.

  46. CVE-2026-42579 9.1 Critique

    netty · Red Hat Cryostat 4 on RHEL 9 · Red Hat build of Apache Camel 4.18.1.P1 for Spring Boot 3.5.16 · Red Hat build of Quarkus 3.27.4

    Netty is an asynchronous, event-driven network application framework. Prior to 4.2.13.Final and 4.1.133.Final, Netty's DNS codec does not enforce RFC 1035 domain name constraints during either encoding or decoding. This creates a bidirectional attack surface: malicious DNS responses can exploit the decoder, and user-influenced hostnames can exploit the encoder. This vulnerability is fixed in 4.2.13.Final and 4.1.133.Final.

  47. CVE-2026-42578 7.5 Élevée

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

    Netty is an asynchronous, event-driven network application framework. Prior to 4.2.13.Final and 4.1.133.Final, Netty's HttpProxyHandler constructs HTTP CONNECT requests with header validation explicitly disabled. The newInitialMessage() method creates headers using DefaultHttpHeadersFactory.headersFactory().withValidation(false), then adds user-provided outboundHeaders without any CRLF validation. This allows an attacker who can influence the outbound headers to inject arbitrary HTTP headers into the CONNECT request sent to the proxy server. This vulnerability is fixed in 4.2.13.Final and 4.1.133.Final.

  48. CVE-2026-44432 7.5 Élevée

    urllib3 · Red Hat Ansible Automation Platform 2.5 for RHEL 8 · Red Hat Ansible Automation Platform 2.5 for RHEL 9 · Red Hat Ansible Automation Platform 2.6 for RHEL 9

    urllib3 is an HTTP client library for Python. From 2.6.0 to before 2.7.0, urllib3 could decompress the whole response instead of the requested portion (1) during the second HTTPResponse.read(amt=N) call when the response was decompressed using the official Brotli library or (2) when HTTPResponse.drain_conn() was called after the response had been read and decompressed partially (compression algorithm did not matter here). These issues could cause urllib3 to fully decode a small amount of highly compressed data in a single operation. This could result in excessive resource consumption (high CPU usage and massive memory allocation for the decompressed data) on the client side. This vulnerability is fixed in 2.7.0.

  49. CVE-2026-42338 6.1 Moyenne

    beaugunderson ip-address · Red Hat AMQ Broker 7.13.6 · Red Hat AMQ Broker 7.14.1 · Red Hat Enterprise Linux 10

    ip-address is a library for parsing and manipulating IPv4 and IPv6 addresses in JavaScript. Prior to 10.1.1, Address6.group() and Address6.link() do not HTML-escape attacker-controlled content before embedding it in the HTML strings they return, and AddressError.parseMessage (emitted by the Address6 constructor for invalid input) can contain unescaped attacker-controlled content in one branch. An application that (1) passes untrusted input to Address6 and (2) renders the output of these methods, or the thrown error's parseMessage, as HTML (e.g. via innerHTML) is vulnerable to cross-site scripting. This vulnerability is fixed in 10.1.1.

  50. CVE-2026-42271 8.8 Élevée Exploitée

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

    LiteLLM is a proxy server (AI Gateway) to call LLM APIs in OpenAI (or native) format. From version 1.74.2 to before version 1.83.7, two endpoints used to preview an MCP server before saving it — POST /mcp-rest/test/connection and POST /mcp-rest/test/tools/list — accepted a full server configuration in the request body, including the command, args, and env fields used by the stdio transport. When called with a stdio configuration, the endpoints attempted to connect, which spawned the supplied command as a subprocess on the proxy host with the privileges of the proxy process. The endpoints were gated only by a valid proxy API key, with no role check. Any authenticated user — including holders of low-privilege internal-user keys — could therefore run arbitrary commands on the host. This issue has been patched in version 1.83.7.

  51. CVE-2026-33814 7.5 Élevée

    golang.org/x/net/http2 · Go standard library net/http · Red Hat Enterprise Linux 10 · Red Hat Enterprise Linux 10.0 Extended Update Support

    When processing HTTP/2 SETTINGS frames, transport will enter an infinite loop of writing CONTINUATION frames if it receives a SETTINGS_MAX_FRAME_SIZE with a value of 0.

  52. CVE-2026-43868 5.3 Moyenne

    Apache Software Foundation Apache Thrift · Red Hat Build of Apache Camel 3.33 for Quarkus 3.33.2.SP1 · Red Hat OpenShift AI 2.25 · Red Hat AI Inference Server

    Memory Allocation with Excessive Size Value vulnerability in Apache Thrift. This issue affects Apache Thrift: before 0.23.0. Users are recommended to upgrade to version 0.23.0, which fixes the issue.

  53. CVE-2026-43869 7.3 Élevée

    Apache Software Foundation Apache Thrift · Red Hat Cryostat 4 on RHEL 9 · Red Hat Build of Apache Camel 3.33 for Quarkus 3.33.2.SP1 · Red Hat Multicluster Global Hub 1.3.4

    Improper Validation of Certificate with Host Mismatch vulnerability in Apache Thrift. This issue affects Apache Thrift: before 0.23.0. Users are recommended to upgrade to version 0.23.0, which fixes the issue.

  54. CVE-2026-6321 7.5 Élevée

    fast-uri · Red Hat HawtIO HawtIO 4.4.0 · Red Hat Ansible Automation Platform 2.5 for RHEL 8 · Red Hat Ansible Automation Platform 2.5 for RHEL 9

    fast-uri decoded percent-encoded path separators and dot segments before applying dot-segment removal in its normalize() and equal() functions. Encoded path data was treated like real slashes and parent-directory references, so distinct URIs could collapse onto the same normalized path. Applications that normalize or compare attacker-controlled URLs to enforce path-based policy can be bypassed, with a path that appears confined under an allowed prefix normalizing to a different location. Versions <= 3.1.0 are affected. Update to 3.1.1 or later.

  55. CVE-2026-42027 9.8 Critique

    Apache Software Foundation Apache OpenNLP · Red Hat OpenShift AI 2.25 · Red Hat build of Apache Camel for Spring Boot 4 · Red Hat Data Grid 8

    Arbitrary Class Instantiation via Model Manifest in Apache OpenNLP ExtensionLoader Versions Affected: before 1.9.5, before 2.5.9, before 3.0.0-M3 Description:  The ExtensionLoader.instantiateExtension(Class, String) method loads a class by its fully-qualified name via Class.forName() and invokes its no-arg constructor, with the class name sourced from the manifest.properties entry of a model archive. The existing isAssignableFrom check correctly rejects classes that are not subtypes of the expected extension interface (BaseToolFactory for factory=, ArtifactSerializer for serializer-class-*), but the check runs after Class.forName() has already loaded and initialized the named class. Class.forName() with default initialization semantics executes the target class's static initializer before returning, so an attacker who can supply a crafted model archive can cause the static initializer of any class on the classpath to run during model loading, regardless of whether that class passes the subsequent type check. Exploitation requires a class with attacker-useful side effects in its static initializer (for example, JNDI lookup, outbound network I/O, or filesystem access) to be present on the classpath, so this is not a drop-in remote code execution; however, the attack surface grows as third-party model distribution becomes more common (community model repositories, Hugging Face-style sharing), where users routinely load model files from origins they do not control. A secondary, narrower vector affects deployments that ship legitimate BaseToolFactory or ArtifactSerializer subclasses with side-effecting no-arg constructors: a malicious manifest can name such a class and force its constructor to run during model load. Mitigation:  * 2.x users should upgrade to 2.5.9. * 3.x users should upgrade to 3.0.0-M3. Note: The fix introduces a package-prefix allowlist that is consulted before Class.forName() is invoked, so the static initializer of a disallowed class is never executed. Classes under the opennlp. prefix remain permitted by default. Deployments that load models referencing factories or serializers outside opennlp.* must opt those packages in, either programmatically via ExtensionLoader.registerAllowedPackage(String) before the first model load, or by setting the OPENNLP_EXT_ALLOWED_PACKAGES system property to a comma-separated list of allowed package prefixes. Users who cannot upgrade immediately should ensure that all model files are sourced from trusted origins and should audit their classpath for classes with side-effecting static initializers or constructors, particularly any that perform JNDI lookups, network requests, or filesystem operations during class initialization.

  56. CVE-2026-35030 9.1 Critique

    BerriAI litellm · Red Hat Ansible Automation Platform 2.6 · Red Hat OpenShift AI 2.25 · Red Hat OpenShift AI 3.3

    LiteLLM is a proxy server (AI Gateway) to call LLM APIs in OpenAI (or native) format. Prior to 1.83.0, when JWT authentication is enabled (enable_jwt_auth: true), the OIDC userinfo cache uses token[:20] as the cache key. JWT headers produced by the same signing algorithm generate identical first 20 characters. This configuration option is not enabled by default. Most instances are not affected. An unauthenticated attacker can craft a token whose first 20 characters match a legitimate user's cached token. On cache hit, the attacker inherits the legitimate user's identity and permissions. This affects deployments with JWT/OIDC authentication enabled. Fixed in v1.83.0.

  57. CVE-2026-35029 8.8 Élevée

    BerriAI litellm · Red Hat Ansible Automation Platform 2.6 · Red Hat OpenShift AI 2.25 · Red Hat OpenShift AI 3.3

    LiteLLM is a proxy server (AI Gateway) to call LLM APIs in OpenAI (or native) format. Prior to 1.83.0, the /config/update endpoint does not enforce admin role authorization. A user who is already authenticated into the platform can then use this endpoint to modify proxy configuration and environment variables, register custom pass-through endpoint handlers pointing to attacker-controlled Python code, achieving remote code execution, read arbitrary server files by setting UI_LOGO_PATH and fetching via /get_image, and take over other privileged accounts by overwriting UI_USERNAME and UI_PASSWORD environment variables. Fixed in v1.83.0.