BlackTreeCVE Intelligence
← Back to the CVE catalogue
Full vulnerability report · 2025
CVE-2025-47277High confidence

vLLM Allows Remote Code Execution via PyNcclPipe Communication Service

vllm-project · vllm

Official source article: GitHub GHSA-HJQ4-87XH-G4FV ↗. Check the applicable product and release in the original source.

9.8CriticalCVSS 3.1
Recommended action
Within 72 hours

Critical technical impact with a remotely reachable, unauthenticated path and a public exploit reference; no CISA KEV confirmation is currently recorded.

Patch available
R
Operational reassessment

Published severity in operational context

Open reassessment dashboard →
Published severityCriticalOperational priority:Critical, unchanged from published severity.unchanged

Evidence used

  • No CISA KEV confirmation is currently recorded.
  • A structured source references public exploit or proof-of-concept material.
  • The selected CVSS metric records a network-reachable, unauthenticated path with no user interaction.
  • EPSS is 0.96% for the current model date.

Compensating controls

  • Validate the affected product branch and deploy the verified fixed release.
  • Restrict the affected network interface to trusted sources where business-safe.
  • Increase monitoring for the attack path and post-exploitation behaviour described in the report.

Verification

  1. Confirm that the asset runs vllm-project vllm and falls inside the recorded affected range.
  2. Verify the installed build against the product-specific fixed version after deployment.
  3. Validate exposure, authentication requirements and compensating controls in the actual environment.
  4. Reopen this reassessment when CVSS, KEV, EPSS, exploit evidence or remediation changes.
Mitigation target: Within 3 daysRemediation target: Within 90 days

This automated reassessment organises public evidence. It does not know asset exposure, business impact or control effectiveness and does not replace CVSS or a human risk decision.

Open-source package ranges1 source-attributed range

These OSV and GitHub advisory ranges apply only to the named package and ecosystem. A listed fixed version is not a universal product patch or proof that an update is installed.

Ecosystem and packageAffected rangeFirst fixed versionEvidence
pipvllm>= 0.6.5, < 0.8.50.8.5GitHub advisory ↗upstream repository advisory · 17 Jul 2026
Direct vendor intelligence

Authoritative vendor CSAF and VEX advisories

Structured product status and remediation from the issuing vendor. Product-state explanations are always visible; large lists can be searched or downloaded.

1 current
CVE-2025-47277 · CSAF 2.0 · revision 3 · finalRed Hat Product Securityvllm: vLLM Allows Remote Code Execution via PyNcclPipe Communication Service
15 fixed

The vendor explicitly identifies these products or versions as containing the fix.

  • registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:64a80edcb6ff725047d8154404e95b425765f504c44e4a959b11cc75fd5fa4aa_arm64 as a component of Red Hat AI Inference Server 3.1
  • registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:771bc45e13c5294baa27ea8918d2ecfe7ce89d64a36344a7ee8e70b2b8254998_amd64 as a component of Red Hat AI Inference Server 3.1
  • registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:c52ad67db7c1cc91617bd71ad1272c3a18229a4b7d9bfd0cfee2ba9a91ac4660_amd64 as a component of Red Hat AI Inference Server 3.1
  • registry.redhat.io/rhelai1/bootc-amd-rhel9@sha256:e683240d86973334e53882f4978b89b5c2a9f452b4080392c33b72bd57f91b63_amd64 as a component of Red Hat Enterprise Linux AI 1.5
  • registry.redhat.io/rhelai1/bootc-aws-nvidia-rhel9@sha256:a169a0d43b63280b9f43b99e6f9910cf0f404c7a9089d30dc06a0aa7fe747b8b_amd64 as a component of Red Hat Enterprise Linux AI 1.5
  • registry.redhat.io/rhelai1/bootc-azure-amd-rhel9@sha256:49cfb622a1dc03438e4683661257d8e178d32bf508cbf649ba4637b9a4b79180_amd64 as a component of Red Hat Enterprise Linux AI 1.5
  • registry.redhat.io/rhelai1/bootc-azure-nvidia-rhel9@sha256:0981388b134c612dde4275c1f9570d5cb684117ede06e12edbc021eb8e1529d2_amd64 as a component of Red Hat Enterprise Linux AI 1.5
  • registry.redhat.io/rhelai1/bootc-gcp-nvidia-rhel9@sha256:e0f422a906d386596295e99b64c6158ae44b6b8a12be30868865e76742fccb17_amd64 as a component of Red Hat Enterprise Linux AI 1.5
  • registry.redhat.io/rhelai1/bootc-intel-rhel9@sha256:47c7b3931eb3a829bb4916cf9ecb7d03d83e762801399f8ed3825de0aa213b43_amd64 as a component of Red Hat Enterprise Linux AI 1.5
  • registry.redhat.io/rhelai1/bootc-nvidia-rhel9@sha256:4a40fcdfb64b4cec6dfb0d0ee5c475fc89124ce80d911dd85f5951238b6c980c_arm64 as a component of Red Hat Enterprise Linux AI 1.5
  • registry.redhat.io/rhelai1/bootc-nvidia-rhel9@sha256:539b3bb9fc9330fe7237b7292ce8b112a38dd22bfff9f090e82a518f9b2f2376_amd64 as a component of Red Hat Enterprise Linux AI 1.5
  • registry.redhat.io/rhelai1/instructlab-amd-rhel9@sha256:f34417c39c2f3b78f306d4249e892a9edf61f2a88bb18a3484c1df9716bdd324_amd64 as a component of Red Hat Enterprise Linux AI 1.5
Summary
A flaw was found in vLLM. This vulnerability allows unauthorized access to key-value caches via network exposure of the `TCPStore` interface when using the `PyNcclPipe` KV cache transfer integration with the V0 engine.
Remediation
For more information visit https://access.redhat.com/errata/RHSA-2025:10404
Optional official sources

National CERT insights
?CERT means Computer Emergency Response Team; CSIRT is the closely related term Computer Security Incident Response Team.

Choose official national sources for this report. Each advisory shows its original language. Your selection is remembered on this device and included in shared links.

Official European source

ENISA European Vulnerability Database

Official EUVD identifiers, advisory evidence and known-exploited context. Missing fields are not treated as evidence of low risk.

1 current
ENISA EUVD identifier

EUVD-2025-15950

No EUVD known-exploited evidence

ENISA has published the identifier mapping but no EUVD description has been stored yet.

EUVD state
Present in the current official mapping
Known exploitation
Not present in the current ENISA EUVD known-exploited dataset. This is not proof of no exploitation.
ENISA score
Not supplied in the stored EUVD record
Advisory evidence
No linked advisory details stored yet
Recommended actionWithin 72 hours

Critical technical impact with a remotely reachable, unauthenticated path and a public exploit reference; no CISA KEV confirmation is currently recorded.

Patch available
01

What, why and how

vLLM, an inference and serving engine for large language models (LLMs), has an issue in versions 0.6.5 through 0.8.4 that ONLY impacts environments using the `PyNcclPipe` KV cache transfer integration with the V0 engine. No other configurations are affected. vLLM supports the use of the `PyNcclPipe` class to establish a peer-to-peer communication domain for data transmission between distributed nodes. The GPU-side KV-Cache transmission is implemented through the `PyNcclCommunicator` class, while CPU-side control message passing is handled via the `send_obj` and `recv_obj` methods on the CPU side.​ The intention was that this interface should only be exposed to a private network using the IP address specified by the `--kv-ip` CLI parameter. The vLLM documentation covers how this must be limited to a secured network. The default and intentional behavior from PyTorch is that the `TCPStore` interface listens on ALL interfaces, regardless of what IP address is provided. The IP address given was only used as a client-side address to use. vLLM was fixed to use a workaround to force the `TCPStore` instance to bind its socket to a specified private interface. As of version 0.8.5, vLLM limits the `TCPStore` socket to the private interface as configured.

What

vLLM, an inference and serving engine for large language models (LLMs), has an issue in versions 0.6.5 through 0.8.4 that ONLY impacts environments using the `PyNcclPipe` KV cache transfer integration with the V0 engine. No other configurations are affected. vLLM supports the use of the `PyNcclPipe` class to establish a peer-to-peer communication domain for data transmission between distributed nodes. The GPU-side KV-Cache transmission is implemented through the `PyNcclCommunicator` class, while CPU-side control message passing is handled via the `send_obj` and `recv_obj` methods on the CPU side.​ The intention was that this interface should only be exposed to a private network using the IP address specified by the `--kv-ip` CLI parameter. The vLLM documentation covers how this must be limited to a secured network. The default and intentional behavior from PyTorch is that the `TCPStore` interface listens on ALL interfaces, regardless of what IP address is provided. The IP address given was only used as a client-side address to use. vLLM was fixed to use a workaround to force the `TCPStore` instance to bind its socket to a specified private interface. As of version 0.8.5, vLLM limits the `TCPStore` socket to the private interface as configured.

Why

Attacker-influenced serialised data is reconstructed as trusted objects, which can invoke dangerous application behaviour.

How

An attacker operating through a network path may attempt exploitation without authentication or user interaction. If successful, the issue may cause the confidentiality, integrity or availability impact described by the vendor.

What

vLLM, an inference and serving engine for large language models (LLMs), has an issue in versions 0.6.5 through 0.8.4 that ONLY impacts environments using the `PyNcclPipe` KV cache transfer integration with the V0 engine. No other configurations are affected. vLLM supports the use of the `PyNcclPipe` class to establish a peer-to-peer communication domain for data transmission between distributed nodes. The GPU-side KV-Cache transmission is implemented through the `PyNcclCommunicator` class, while CPU-side control message passing is handled via the `send_obj` and `recv_obj` methods on the CPU side.​ The intention was that this interface should only be exposed to a private network using the IP address specified by the `--kv-ip` CLI parameter. The vLLM documentation covers how this must be limited to a secured network. The default and intentional behavior from PyTorch is that the `TCPStore` interface listens on ALL interfaces, regardless of what IP address is provided. The IP address given was only used as a client-side address to use. vLLM was fixed to use a workaround to force the `TCPStore` instance to bind its socket to a specified private interface. As of version 0.8.5, vLLM limits the `TCPStore` socket to the private interface as configured.

Why

Attacker-influenced serialised data is reconstructed as trusted objects, which can invoke dangerous application behaviour.

How

An attacker operating through a network path may attempt exploitation without authentication or user interaction. If successful, the issue may cause the confidentiality, integrity or availability impact described by the vendor.

02

Exploit reality and attack path

CVSS severity, EPSS forecast probability, public exploit material and CISA-confirmed exploitation are separate signals.

Observed exploitation
?Confirmed exploitation and public exploit material are separate signals. Attacks can occur without public proof-of-concept or exploit code.
No confirmed evidence

No CISA KEV match was present at the last successful refresh. This means no confirmation from that source, not proof of no exploitation.

Public PoC / exploit material
?Confirmed exploitation and public exploit material are separate signals. Attacks can occur without public proof-of-concept or exploit code.
Reference recorded

A structured CVE source labels at least one public reference as exploit material. BlackTree has not independently validated that it is safe, reliable or weaponised.

Likely attack path
a network path → Deserialization of Untrusted Data → cause the confidentiality, integrity or availability impact described by the vendor
Attack surface
Network
Privileges required
None: unauthenticated exploitation is possible
User interaction
None
Attack complexity
Low: no specialised conditions are recorded
Security boundary
Unchanged: impact remains within the vulnerable component's security authority
Weakness
?CWE means Common Weakness Enumeration: a standard category for the underlying weakness.
CWE-502 ↗

CWE-502: Deserialization of Untrusted Data. The product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid.

CVSS vector
?CVSS means Common Vulnerability Scoring System. The vector records the metric values used to calculate technical severity.
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H

Common Vulnerability Scoring System 3.1: the compact vector below is decoded into plain language.

AVNetworkAttack vector: The vulnerable component can be reached over a network.ACLowAttack complexity: No specialised conditions are required beyond attacker-controlled input.PRNonePrivileges required: The attacker does not need an account or existing privileges.UINoneUser interaction: No action by another user is required.SUnchangedScope: The security impact remains within the vulnerable component's authority.CHighConfidentiality impact: A successful attack can cause a major loss.IHighIntegrity impact: A successful attack can cause a major loss.AHighAvailability impact: A successful attack can cause a major loss.
Post-exploitation / living off the land
No specific living-off-the-land technique is confirmed in the structured sources. Monitor normal administration tools for activity inconsistent with the affected service's baseline.
NetworkUnauthenticatedCWE-502Public exploit reference
A

Official authority intelligence

Only matched European and national findings are included. Language selectors and unavailable sources are omitted.

BSI · German · WID-SEC-2025-2883Red Hat Enterprise AI Inference Server (vLLM): Schwachstelle ermöglicht Codeausführung

Ein Angreifer aus einem angrenzenden Netzwerk kann eine Schwachstelle in Red Hat Enterprise AI Inference Server ausnutzen, um beliebigen Programmcode auszuführen.

Official advisory ↗
Cyber Security Agency of Singapore · English · CSA-SB-20250522Security Bulletin 21 May 2025

The Cyber Security Agency of Singapore included this CVE in its official Security Bulletin 21 May 2025, published on 22 May 2025. Open the linked bulletin for the product, severity and reference information published in that issue.

Official advisory ↗
CERT-FR · French · CERTFR-2025-AVI-1057Multiples vulnérabilités dans les produits VMware

ecord?id=CVE-2025-32414 Référence CVE CVE-2025-32415 https://www.cve.org/CVERecord?id=CVE-2025-32415 Référence CVE CVE-2025-32434 https://www.cve.org/CVERecord?id=CVE-2025-32434 Référence CVE CVE-2025-32444 https://www.cve.org/CVERecord?id=CVE-2025-32444 Référence CVE CVE-2025-3576 https://www.cve.org/CVERecord?id=CVE-2025-3576 Référence CVE CVE-2025-41248 https://www.cve.org/CVERecord?id=CVE-2025-41248 Référence CVE CVE-2025-43859 https://www.cve.org/CVERecord?id=CVE-2025-43859 Référence CVE CVE-2025-4516 https://www.cve.org/CVERecord?id=CVE-2025-4516 Référence CVE CVE-2025-46570 https://www.cve.org/CVERecord?id=CVE-2025-46570 Référence CVE CVE-2025-47277 https://www.cve.org/CVERecord?id=CVE-2025-47277 Référence CVE CVE-2025-48887 https://www.cve.org/CVERecord?id=CVE-2025-48887 Référence CVE CVE-2025-48956 https://www.cve.org/CVERecord?id=CVE-2025-48956 Référence CVE CVE-2025-4947 https://www.cve.org/CVERecord?id=CVE-2025-4947 Référence CVE CVE-2025-49794 https://www.cve.org/CVERecord?id=CVE-2025-49794 Référence CVE CVE-2025-49795 https://www.cve.org/CVERecord?id=CVE-2025-49795 Référence CVE CVE-2025-49796 https://www.cve.org/CVERecord?id=CVE-2025-49796 Référence CVE CVE-2025-50182 https://www.cve.org/CVERecord?id=CVE-2025-50182 Référence CVE CVE-2025-5025 https://www.cve.org/CVERecord?id=CVE

Official advisory ↗
JVN iPedia · Japanese · JVNDB-2025-011489vLLM における信頼できないデータのデシリアライゼーションに関する脆弱性

vLLM には、信頼できないデータのデシリアライゼーションに関する脆弱性が存在します。

Official advisory ↗
03

Patch and workaround

Operational remediation based on structured source evidence.

Status
?Patch availability is based on structured fixed-version fields and authoritative update references. If no fix is verified, check the vendor advisory before making a change.
Patch available
Affected
vllm: >= 0.6.5, < 0.8.5
Fixed
Action
For more information visit https://access.redhat.com/errata/RHSA-2025:10404
Workaround
No verified workaround is recorded. If business-safe, reduce exposure to the affected interface and allow only trusted sources until authoritative guidance is available.
04

Evidence and provenance

Published 20 May 2025 · Last source change 20 May 2025, 17:52 UTC · CWE-502 · Deserialization of Untrusted Data

CVE recordCVE.org · 5.1
CVSS sourceCNA
EPSS source
?The date BlackTree first stored a score for this CVE from the daily FIRST EPSS feed.
FIRST · tracked since 2026-08-14
European sourceENISA EUVD · EUVD-2025-15950
Product sourceCNA
Remediation sourceVendor CSAF · Red Hat Product Security
CWE sourceCNA
NVD statusNVD enriched

Core structured fields are present and their contributing authorities are shown above.

Material change intelligence

What changed after publication

View recent updates ↗
  1. Affected versionsThe structured affected or fixed version information changed.
    Before
    >= 0.6.5, < 0.8.5 · Fixed: An authoritative update reference is available, but the fixed version is not recorded in the structured CVE fields. Check the linked vendor advisory for the applicable release.
    After
    >= 0.6.5, < 0.8.5 · Fixed: For more information visit https://access.redhat.com/errata/RHSA-2025:10404
    Red Hat Product Security ↗
  2. Affected versionsThe structured affected or fixed version information changed.
    Before
    Fixed: registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:64a80edcb6ff725047d8154404e95b425765f504c44e4a959b11cc75fd5fa4aa_arm64 as a component of Red Hat AI Inference Server 3.1; registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:771bc45e13c5294baa27ea8918d2ecfe7ce89d64a36344a7ee8e70b2b8254998_amd64 as a component of Red Hat AI Inference Server 3.1; registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:c52ad67db7c1cc91617bd71ad1272c3a18229a4b7d9bfd0cfee2ba9a91ac4660_amd64 as a component of Red Hat AI Inference Server 3.1; registry.redhat.io/rhelai1/bootc-amd-rhel9@sha256:e683240d86973334e53882f4978b89b5c2a9f452b4080392c33b72bd57f91b63_amd64 as a component of Red Hat Enterprise Linux AI 1.5.1; registry.redhat.io/rhelai1/bootc-aws-nvidia-rhel9@sha256:a169a0d43b63280b9f43b99e6f9910cf0f404c7a9089d30dc06a0aa7fe747b8b_amd64 as a component of Red Hat Enterprise Linux AI 1.5.1; registry.redhat.io/rhelai1/bootc-azure-amd-rhel9@sha256:49cfb622a1dc03438e4683661257d8e178d32bf508cbf649ba4637b9a4b79180_amd64 as a component of Red Hat Enterprise Linux AI 1.5.1; registry.redhat.io/rhelai1/bootc-azure-nvidia-rhel9@sha256:0981388b134c612dde4275c1f9570d5cb684117ede06e12edbc021eb8e1529d2_amd64 as a component of Red Hat Enterprise Linux AI 1.5.1; registry.redhat.io/rhelai1/bootc-gcp-nvidia-rhel9@sha256:e0f422a906d386596295e99b64c6158ae44b6b8a12be30868865e76742fccb17_amd64 as a component of Red Hat Enterprise Linux AI 1.5.1; registry.redhat.io/rhelai1/bootc-intel-rhel9@sha256:47c7b3931eb3a829bb4916cf9ecb7d03d83e762801399f8ed3825de0aa213b43_amd64 as a component of Red Hat Enterprise Linux AI 1.5.1; registry.redhat.io/rhelai1/bootc-nvidia-rhel9@sha256:4a40fcdfb64b4cec6dfb0d0ee5c475fc89124ce80d911dd85f5951238b6c980c_arm64 as a component of Red Hat Enterprise Linux AI 1.5.1; registry.redhat.io/rhelai1/bootc-nvidia-rhel9@sha256:539b3bb9fc9330fe7237b7292ce8b112a38dd22bfff9f090e82a518f9b2f2376_amd64 as a component of Red Hat Enterprise Linux AI 1.5.1; registry.redhat.io/rhelai1/instructlab-amd-rhel9@sha256:f34417c39c2f3b78f306d4249e892a9edf61f2a88bb18a3484c1df9716bdd324_amd64 as a component of Red Hat Enterprise Linux AI 1.5.1; registry.redhat.io/rhelai1/instructlab-intel-rhel9@sha256:2ec7df6d207c24989660f42e656340581fa488fed399ec343cda5b288f3f1f7c_amd64 as a component of Red Hat Enterprise Linux AI 1.5.1; registry.redhat.io/rhelai1/instructlab-nvidia-rhel9@sha256:89114d614ccbbbbd8a78d143fac90570ab81650ced7d4a9f39f7ba416113ae3b_amd64 as a component of Red Hat Enterprise Linux AI 1.5.1; registry.redhat.io/rhelai1/instructlab-nvidia-rhel9@sha256:f4e7a03db9b24711381b5e1279e19eadf6b7dd20510711a17212261fb67f3e11_arm64 as a component of Red Hat Enterprise Linux AI 1.5.1
    After
    Fixed: registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:64a80edcb6ff725047d8154404e95b425765f504c44e4a959b11cc75fd5fa4aa_arm64 as a component of Red Hat AI Inference Server 3.1; registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:771bc45e13c5294baa27ea8918d2ecfe7ce89d64a36344a7ee8e70b2b8254998_amd64 as a component of Red Hat AI Inference Server 3.1; registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:c52ad67db7c1cc91617bd71ad1272c3a18229a4b7d9bfd0cfee2ba9a91ac4660_amd64 as a component of Red Hat AI Inference Server 3.1; registry.redhat.io/rhelai1/bootc-amd-rhel9@sha256:e683240d86973334e53882f4978b89b5c2a9f452b4080392c33b72bd57f91b63_amd64 as a component of Red Hat Enterprise Linux AI 1.5; registry.redhat.io/rhelai1/bootc-aws-nvidia-rhel9@sha256:a169a0d43b63280b9f43b99e6f9910cf0f404c7a9089d30dc06a0aa7fe747b8b_amd64 as a component of Red Hat Enterprise Linux AI 1.5; registry.redhat.io/rhelai1/bootc-azure-amd-rhel9@sha256:49cfb622a1dc03438e4683661257d8e178d32bf508cbf649ba4637b9a4b79180_amd64 as a component of Red Hat Enterprise Linux AI 1.5; registry.redhat.io/rhelai1/bootc-azure-nvidia-rhel9@sha256:0981388b134c612dde4275c1f9570d5cb684117ede06e12edbc021eb8e1529d2_amd64 as a component of Red Hat Enterprise Linux AI 1.5; registry.redhat.io/rhelai1/bootc-gcp-nvidia-rhel9@sha256:e0f422a906d386596295e99b64c6158ae44b6b8a12be30868865e76742fccb17_amd64 as a component of Red Hat Enterprise Linux AI 1.5; registry.redhat.io/rhelai1/bootc-intel-rhel9@sha256:47c7b3931eb3a829bb4916cf9ecb7d03d83e762801399f8ed3825de0aa213b43_amd64 as a component of Red Hat Enterprise Linux AI 1.5; registry.redhat.io/rhelai1/bootc-nvidia-rhel9@sha256:4a40fcdfb64b4cec6dfb0d0ee5c475fc89124ce80d911dd85f5951238b6c980c_arm64 as a component of Red Hat Enterprise Linux AI 1.5; registry.redhat.io/rhelai1/bootc-nvidia-rhel9@sha256:539b3bb9fc9330fe7237b7292ce8b112a38dd22bfff9f090e82a518f9b2f2376_amd64 as a component of Red Hat Enterprise Linux AI 1.5; registry.redhat.io/rhelai1/instructlab-amd-rhel9@sha256:f34417c39c2f3b78f306d4249e892a9edf61f2a88bb18a3484c1df9716bdd324_amd64 as a component of Red Hat Enterprise Linux AI 1.5; registry.redhat.io/rhelai1/instructlab-intel-rhel9@sha256:2ec7df6d207c24989660f42e656340581fa488fed399ec343cda5b288f3f1f7c_amd64 as a component of Red Hat Enterprise Linux AI 1.5; registry.redhat.io/rhelai1/instructlab-nvidia-rhel9@sha256:89114d614ccbbbbd8a78d143fac90570ab81650ced7d4a9f39f7ba416113ae3b_amd64 as a component of Red Hat Enterprise Linux AI 1.5; registry.redhat.io/rhelai1/instructlab-nvidia-rhel9@sha256:f4e7a03db9b24711381b5e1279e19eadf6b7dd20510711a17212261fb67f3e11_arm64 as a component of Red Hat Enterprise Linux AI 1.5
    Red Hat Product Security ↗
  3. Affected versionsThe structured affected or fixed version information changed.
    Before
    Fixed: registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:64a80edcb6ff725047d8154404e95b425765f504c44e4a959b11cc75fd5fa4aa_arm64 as a component of Red Hat AI Inference Server 3.1; registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:771bc45e13c5294baa27ea8918d2ecfe7ce89d64a36344a7ee8e70b2b8254998_amd64 as a component of Red Hat AI Inference Server 3.1; registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:c52ad67db7c1cc91617bd71ad1272c3a18229a4b7d9bfd0cfee2ba9a91ac4660_amd64 as a component of Red Hat AI Inference Server 3.1; registry.redhat.io/rhelai1/bootc-amd-rhel9@sha256:e683240d86973334e53882f4978b89b5c2a9f452b4080392c33b72bd57f91b63_amd64 as a component of Red Hat Enterprise Linux AI 1.5; registry.redhat.io/rhelai1/bootc-aws-nvidia-rhel9@sha256:a169a0d43b63280b9f43b99e6f9910cf0f404c7a9089d30dc06a0aa7fe747b8b_amd64 as a component of Red Hat Enterprise Linux AI 1.5; registry.redhat.io/rhelai1/bootc-azure-amd-rhel9@sha256:49cfb622a1dc03438e4683661257d8e178d32bf508cbf649ba4637b9a4b79180_amd64 as a component of Red Hat Enterprise Linux AI 1.5; registry.redhat.io/rhelai1/bootc-azure-nvidia-rhel9@sha256:0981388b134c612dde4275c1f9570d5cb684117ede06e12edbc021eb8e1529d2_amd64 as a component of Red Hat Enterprise Linux AI 1.5; registry.redhat.io/rhelai1/bootc-gcp-nvidia-rhel9@sha256:e0f422a906d386596295e99b64c6158ae44b6b8a12be30868865e76742fccb17_amd64 as a component of Red Hat Enterprise Linux AI 1.5; registry.redhat.io/rhelai1/bootc-intel-rhel9@sha256:47c7b3931eb3a829bb4916cf9ecb7d03d83e762801399f8ed3825de0aa213b43_amd64 as a component of Red Hat Enterprise Linux AI 1.5; registry.redhat.io/rhelai1/bootc-nvidia-rhel9@sha256:4a40fcdfb64b4cec6dfb0d0ee5c475fc89124ce80d911dd85f5951238b6c980c_arm64 as a component of Red Hat Enterprise Linux AI 1.5; registry.redhat.io/rhelai1/bootc-nvidia-rhel9@sha256:539b3bb9fc9330fe7237b7292ce8b112a38dd22bfff9f090e82a518f9b2f2376_amd64 as a component of Red Hat Enterprise Linux AI 1.5; registry.redhat.io/rhelai1/instructlab-amd-rhel9@sha256:f34417c39c2f3b78f306d4249e892a9edf61f2a88bb18a3484c1df9716bdd324_amd64 as a component of Red Hat Enterprise Linux AI 1.5; registry.redhat.io/rhelai1/instructlab-intel-rhel9@sha256:2ec7df6d207c24989660f42e656340581fa488fed399ec343cda5b288f3f1f7c_amd64 as a component of Red Hat Enterprise Linux AI 1.5; registry.redhat.io/rhelai1/instructlab-nvidia-rhel9@sha256:89114d614ccbbbbd8a78d143fac90570ab81650ced7d4a9f39f7ba416113ae3b_amd64 as a component of Red Hat Enterprise Linux AI 1.5; registry.redhat.io/rhelai1/instructlab-nvidia-rhel9@sha256:f4e7a03db9b24711381b5e1279e19eadf6b7dd20510711a17212261fb67f3e11_arm64 as a component of Red Hat Enterprise Linux AI 1.5
    After
    Fixed: registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:64a80edcb6ff725047d8154404e95b425765f504c44e4a959b11cc75fd5fa4aa_arm64 as a component of Red Hat AI Inference Server 3.1; registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:771bc45e13c5294baa27ea8918d2ecfe7ce89d64a36344a7ee8e70b2b8254998_amd64 as a component of Red Hat AI Inference Server 3.1; registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:c52ad67db7c1cc91617bd71ad1272c3a18229a4b7d9bfd0cfee2ba9a91ac4660_amd64 as a component of Red Hat AI Inference Server 3.1; registry.redhat.io/rhelai1/bootc-amd-rhel9@sha256:e683240d86973334e53882f4978b89b5c2a9f452b4080392c33b72bd57f91b63_amd64 as a component of Red Hat Enterprise Linux AI 1.5.1; registry.redhat.io/rhelai1/bootc-aws-nvidia-rhel9@sha256:a169a0d43b63280b9f43b99e6f9910cf0f404c7a9089d30dc06a0aa7fe747b8b_amd64 as a component of Red Hat Enterprise Linux AI 1.5.1; registry.redhat.io/rhelai1/bootc-azure-amd-rhel9@sha256:49cfb622a1dc03438e4683661257d8e178d32bf508cbf649ba4637b9a4b79180_amd64 as a component of Red Hat Enterprise Linux AI 1.5.1; registry.redhat.io/rhelai1/bootc-azure-nvidia-rhel9@sha256:0981388b134c612dde4275c1f9570d5cb684117ede06e12edbc021eb8e1529d2_amd64 as a component of Red Hat Enterprise Linux AI 1.5.1; registry.redhat.io/rhelai1/bootc-gcp-nvidia-rhel9@sha256:e0f422a906d386596295e99b64c6158ae44b6b8a12be30868865e76742fccb17_amd64 as a component of Red Hat Enterprise Linux AI 1.5.1; registry.redhat.io/rhelai1/bootc-intel-rhel9@sha256:47c7b3931eb3a829bb4916cf9ecb7d03d83e762801399f8ed3825de0aa213b43_amd64 as a component of Red Hat Enterprise Linux AI 1.5.1; registry.redhat.io/rhelai1/bootc-nvidia-rhel9@sha256:4a40fcdfb64b4cec6dfb0d0ee5c475fc89124ce80d911dd85f5951238b6c980c_arm64 as a component of Red Hat Enterprise Linux AI 1.5.1; registry.redhat.io/rhelai1/bootc-nvidia-rhel9@sha256:539b3bb9fc9330fe7237b7292ce8b112a38dd22bfff9f090e82a518f9b2f2376_amd64 as a component of Red Hat Enterprise Linux AI 1.5.1; registry.redhat.io/rhelai1/instructlab-amd-rhel9@sha256:f34417c39c2f3b78f306d4249e892a9edf61f2a88bb18a3484c1df9716bdd324_amd64 as a component of Red Hat Enterprise Linux AI 1.5.1; registry.redhat.io/rhelai1/instructlab-intel-rhel9@sha256:2ec7df6d207c24989660f42e656340581fa488fed399ec343cda5b288f3f1f7c_amd64 as a component of Red Hat Enterprise Linux AI 1.5.1; registry.redhat.io/rhelai1/instructlab-nvidia-rhel9@sha256:89114d614ccbbbbd8a78d143fac90570ab81650ced7d4a9f39f7ba416113ae3b_amd64 as a component of Red Hat Enterprise Linux AI 1.5.1; registry.redhat.io/rhelai1/instructlab-nvidia-rhel9@sha256:f4e7a03db9b24711381b5e1279e19eadf6b7dd20510711a17212261fb67f3e11_arm64 as a component of Red Hat Enterprise Linux AI 1.5.1
    Red Hat Product Security ↗
Material fields only · duplicate refreshes suppressed · history retained for the configured operational retention period
Technical terms and abbreviations used in this report
CVE
Common Vulnerabilities and Exposures: the public identifier for one disclosed vulnerability.
CVSS
Common Vulnerability Scoring System: a technical severity framework; it is not patching priority by itself.
EPSS
Exploit Prediction Scoring System: FIRST's estimate of the probability that exploitation activity will be observed in the next 30 days; it is a forecast, not confirmation.
CWE
Common Weakness Enumeration: the standard category describing the underlying software or hardware weakness.
CNA
CVE Numbering Authority: an organisation authorised to assign and publish CVE records.
CISA ADP
Cybersecurity and Infrastructure Security Agency Authorized Data Publisher: structured enrichment added to a CVE record.
NVD
National Vulnerability Database: NIST's enrichment service for CVE records.
CERT / CSIRT
A computer security incident response team that publishes warnings or coordinates incident response.
PoC
Proof of concept: public material that demonstrates or helps reproduce exploitation.
CSAF
Common Security Advisory Framework: a machine-readable format for security advisories.
LoTL
Living off the land: abuse of legitimate tools or system functions during an attack.
Free version - for non-commercial use only.CVE-2025-47277 · cve.blacktree.nl