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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.

xdgmime · Red Hat Enterprise Linux 10 · Red Hat Enterprise Linux 10.0 Extended Update Support · Red Hat Enterprise Linux 8

A flaw was found in xdgmime. A heap-based buffer overflow can be triggered in _xdg_mime_magic_parse_magic_line() in the xdgmimemagic.c file on little-endian systems when an attacker-controlled MIME magic file in a user-writable XDG data location (e.g., in the $XDG_DATA_HOME/mime/magic path) is parsed by an application performing MIME type detection (e.g., via g_content_type_guess()). When performing byte-swap, incorrect pointer arithmetic on the write side causes an out-of-bounds write of 2 bytes, resulting in an application crash or memory corruption.

huggingface text-generation-inference

text-generation-inference through 3.3.7 contains a server-side request forgery (SSRF) vulnerability in the OpenAI-compatible multimodal chat completions endpoint that allows unauthenticated network attackers to coerce the server into issuing arbitrary HTTP GET requests by supplying a crafted image_url value in chat message content. The fetch_image function in router/src/validation.rs performs no validation of private, loopback, link-local, or cloud metadata target addresses, and the reqwest HTTP client follows redirects by default, enabling attackers to bypass scheme checks via redirect chains to reach internal services and cloud instance-metadata endpoints for internal port scanning and credential theft.

FFmpeg · Red Hat Enterprise Linux AI 3.0 for RHEL 9 · Red Hat Enterprise Linux AI 3.2 for RHEL 9 · Red Hat Enterprise Linux AI 3.3 for RHEL 9

FFmpeg's RASC video decoder (decode_dlta in libavcodec/rasc.c) performs 32-bit reads and writes at the row cursor before the NEXT_LINE row-boundary check and validates the DLTA region in pixel rather than byte units, so a DLTA run on a PAL8 frame can access several bytes past the row allocation. A crafted media stream using the RASC FourCC, decoded by libavcodec, triggers a bitstream-controlled out-of-bounds heap write and adjacent out-of-bounds read, leading to memory corruption.

vllm-project vllm · Red Hat AI Inference Server 3.2 · Red Hat AI Inference Server 3.3 · Red Hat AI Inference Server 3.4

vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.22.0, an assert-based security check in vLLM's activation function loading allows any unauthenticated attacker to achieve arbitrary code execution on the server by publishing a malicious HuggingFace model, when vLLM runs in Python optimized mode (python -O or PYTHONOPTIMIZE=1). This vulnerability is fixed in 0.22.0.

Red Hat Enterprise Linux AI 3.3 for RHEL 9 · Red Hat Enterprise Linux AI 3.4 for RHEL 9 · Red Hat Enterprise Linux AI 3.5 for RHEL 9 · Red Hat AI Inference Server 3.2

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.

Red Hat Enterprise Linux AI 3.3 for RHEL 9 · Red Hat Enterprise Linux AI 3.4 for RHEL 9 · Red Hat Enterprise Linux AI 3.5 for RHEL 9 · Red Hat AI Inference Server 3.2

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).

Red Hat Enterprise Linux AI 3.3 for RHEL 9 · Red Hat Enterprise Linux AI 3.4 for RHEL 9 · Red Hat Enterprise Linux AI 3.5 for RHEL 9 · Red Hat AI Inference Server 3.2

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.

Red Hat Enterprise Linux 10.0 Extended Update Support · Red Hat Enterprise Linux 7 Extended Lifecycle Support · Red Hat Enterprise Linux 8 · Red Hat Enterprise Linux 8.4 Advanced Mission Critical Update Support

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.

Kludex starlette · Red Hat AI Inference Server 3.3 · Red Hat Exploit Intelligence · Red Hat Migration Toolkit for Applications 8

Starlette is a lightweight ASGI framework/toolkit. In versions 1.0.1 and earlier, StaticFiles on Windows is vulnerable to SSRF. An UNC path such as \\attacker.com\share can cause os.path.realpath to initiate an outbound SMB connection before the path is rejected, exposing the service account’s NTLMv2 credentials for offline cracking or relay even though the HTTP response is only a 404. The issue affects default follow_symlink=False deployments, including frameworks built on Starlette such as FastAPI; POSIX systems and follow_symlink=True are unaffected. The issue is fixed in 1.1.0.

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.

Red Hat Enterprise Linux 10 · Red Hat Enterprise Linux 10.0 Extended Update Support · Red Hat Enterprise Linux 7 Extended Lifecycle Support · Red Hat Enterprise Linux 8

A flaw was found in Poppler's Splash backend. A remote attacker could exploit this vulnerability by crafting a malicious PDF file that, when rendered, triggers an integer overflow in the `tilingPatternFill` function. This overflow leads to an undersized heap memory allocation, allowing a subsequent out-of-bounds write. Successful exploitation could result in arbitrary code execution, information disclosure, or denial of service within the context of the application processing the PDF.

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.

Kludex python-multipart · Red Hat Ansible Automation Platform 2.6 · Red Hat Ansible Automation Platform 2.7 · Red Hat Migration Toolkit for Applications 8.2

Python-Multipart is a streaming multipart parser for Python. Prior to 0.0.27, python-multipart has a denial of service vulnerability in multipart part header parsing. When parsing multipart/form-data, MultipartParser previously had no limit on the number of part headers or the size of an individual part header. An attacker could send a request with either many repeated headers without terminating the header block or a single very large header value, causing excessive CPU work before request rejection or completion. This vulnerability is fixed in 0.0.27.

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.

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.

Red Hat Enterprise Linux 10 · Red Hat Enterprise Linux 10.0 Extended Update Support · Red Hat Enterprise Linux 8 · Red Hat Enterprise Linux 8.4 Advanced Mission Critical Update Support

An issue was discovered in libsndfile 1.2.2 IMA ADPCM codec. The AIFF code path (line 241) was fixed with (sf_count_t) cast, but the WAV code path (line 235) and close path (line 167) were not. When samplesperblock (int) * blocks (int) exceeds INT_MAX, the 32-bit multiplication overflows before being assigned to sf.frames (sf_count_t/int64). With samplesperblock=50000 and blocks=50000, the product 2500000000 overflows to -1794967296. This causes incorrect frame count leading to heap buffer overflow or denial of service. Both values come from the WAV file header and are attacker-controlled. This issue was discovered after an incomplete fix for CVE-2022-33065.