RHSA-2026:30087CriticalCVSS 9.8

Red Hat Security Advisory: Red Hat AI Inference Server 3.3.5 (Spyre)

Published
June 25, 2026
Last Modified
July 27, 2026

🔗 CVE IDs covered (20)

CVE-2026-44431 →CVE-2026-44432 →CVE-2025-62164 →CVE-2026-6100 →CVE-2026-34588 →CVE-2026-34982 →CVE-2026-35385 →CVE-2026-4775 →CVE-2026-4786 →CVE-2026-4878 →CVE-2026-22773 →CVE-2026-22778 →CVE-2026-24779 →CVE-2025-66448 →CVE-2026-37555 →CVE-2026-39979 →CVE-2026-40164 →CVE-2026-48818 →CVE-2026-10118 →CVE-2026-22807 →

📋 Description

CVE-2025-62164 — vllm: VLLM deserialization vulnerability leading to DoS and potential RCE CVE-2025-66448 — vllm: vLLM: Remote Code Execution via malicious model configuration CVE-2026-4775 — libtiff: libtiff: Arbitrary code execution or denial of service via signed integer overflow in TIFF file processing CVE-2026-4786 — python: cpython: Python: Arbitrary code execution via command injection in webbrowser.open() API CVE-2026-4878 — libcap: libcap: Privilege escalation via TOCTOU race condition in cap_set_file() CVE-2026-6100 — python: Python: Arbitrary code execution or information disclosure via use-after-free in decompression modules CVE-2026-10118 — poppler: Integer overflow in Poppler SplashOutputDev::tilingPatternFill leads to heap buffer overflow via unchecked dimension multiplication CVE-2026-22773 — vllm: vLLM: Denial of Service via specially crafted image in multimodal model serving CVE-2026-22778 — vLLM: vLLM: Remote code execution via invalid image processing in the multimodal endpoint. CVE-2026-22807 — vLLM: vLLM: Arbitrary code execution via untrusted model loading CVE-2026-24779 — vLLM: vLLM: Server-Side Request Forgery allows internal network access CVE-2026-34588 — OpenEXR: OpenEXR: Arbitrary code execution and information disclosure via crafted EXR file CVE-2026-34982 — vim: arbitrary command execution via modeline sandbox bypass CVE-2026-35385 — OpenSSH: OpenSSH: Privilege escalation via scp legacy protocol when not preserving file mode CVE-2026-37555 — libsndfile: integer overflow in ima_reader_init() CVE-2026-39979 — jq: out-of-bounds read in jv_parse_sized() on error formatting for non-NUL-terminated buffers CVE-2026-40164 — jq: jq: Denial of Service via crafted JSON object causing hash collisions CVE-2026-44431 — urllib3: urllib3: Information disclosure via cross-origin redirects forwarding sensitive headers CVE-2026-44432 — urllib3: urllib3: Denial of Service due to excessive HTTP response decompression CVE-2026-48818 — starlette: Starlette: SSRF and NTLM credential theft via UNC paths in StaticFiles on Windows

🎯 Affected products4

  • Red Hat AI Inference Server 3.3
  • registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:681d191e22994e4da2d4844219e2401ee363d4b3524cd19bb00076dce685a36a_s390x as a component of Red Hat AI Inference Server 3.3
  • registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:906987407c1ed10139dadc5f8aef64584f407a6017467fce726e2e9c42d9f9c8_amd64 as a component of Red Hat AI Inference Server 3.3
  • registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:9c8187509c26e824143f51f9522d7b6457f3aea33e5f7983bb203e4bb231473d_ppc64le as a component of Red Hat AI Inference Server 3.3

✅ Remediation

For more information visit https://access.redhat.com/errata/RHSA-2026:30087 Workaround: No mitigation is currently available that meets Red Hat Product Security’s standards for usability, deployment, applicability, or stability. Workaround: Red Hat has investigated whether a possible mitigation exists for this issue, and has not been able to identify a practical example. Please update the affected package as soon as possible. Workaround: To mitigate this issue, avoid processing untrusted or maliciously crafted TIFF files with applications linked against the libtiff library. If processing untrusted TIFF files is unavoidable, consider running the affected applications within a sandboxed environment to limit the potential impact of successful exploitation. This operational control helps contain the effects of an out-of-bounds write, reducing the risk of denial of service or arbitrary code execution. Workaround: Mitigation for this issue is either not available or the currently available options do not meet the Red Hat Product Security criteria comprising ease of use and deployment, applicability to widespread installation base, or stability. Workaround: Mitigation for this issue is either not available or the currently available options do not meet the Red Hat Product Security criteria comprising ease of use and deployment, applicability to widespread installation base or stability. Workaround: To mitigate this issue, users should avoid opening untrusted or suspicious PDF documents with applications that utilize the Poppler library for rendering. Limiting exposure to untrusted content can reduce the risk of exploitation. Workaround: To mitigate this issue, ensure that vLLM instances are configured to load models only from trusted and verified repositories. Restrict access to the model repository path to prevent unauthorized modification or introduction of malicious code. Implement strict access controls and integrity checks for all model sources. Workaround: To mitigate this issue, restrict network access to the vLLM service to only trusted clients. Implement strict network segmentation for vLLM pods in containerized environments to limit potential lateral movement. Ensure that vLLM instances are not exposed to untrusted external networks without proper access controls and input validation at the perimeter. Workaround: To mitigate this issue, disable the modeline support by adding the following command to the Vim configuration file: ~~~ set nomodeline ~~~ Workaround: Do not process untrusted WAV files with the libsndfile library. Workaround: To mitigate this issue, manually ensure that every buffer is NUL-terminated before passing it to the 'jv_parse_sized' function.

🔗 References (24)