Evidence used
- No CISA KEV confirmation is currently recorded.
- A structured source references public exploit or proof-of-concept material.
- EPSS is 0.46% for the current model date.
BlackTreeCVE IntelligenceFull vulnerability report · 2026
CVE-2026-44222High confidence
vLLM: Remote DoS via Special-Token Placeholders
vllm-project · vllm
Official source article: GitHub GHSA-HPV8-X276-M59F ↗. Check the applicable product and release in the original source.
6.5MediumCVSS 3.1
Within 7 days
Patch availableMedium technical severity with public exploit material referenced by a structured source; prioritise exposed affected systems while verifying vendor guidance.
R
Open reassessment dashboard →Operational reassessment
Published severity in operational context
Published severityMedium→Operational priority:High, raised one band.upgradedsince 13 May 2026
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
- Confirm that the asset runs vllm-project vllm and falls inside the recorded affected range.
- Verify the installed build against the product-specific fixed version after deployment.
- Validate exposure, authentication requirements and compensating controls in the actual environment.
- Reopen this reassessment when CVSS, KEV, EPSS, exploit evidence or remediation changes.
Open-source package ranges2 source-attributed ranges
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 package | Affected range | First fixed version | Evidence |
|---|---|---|---|
| PyPIvllm | ECOSYSTEM: introduced 0.6.1; fixed 0.20.0 | 0.20.0 | OSV record ↗aggregator derived · 10 Sep 2026 |
| pipvllm | >= 0.6.1, < 0.20.0 | 0.20.0 | GitHub advisory ↗upstream repository advisory · 17 Jul 2026 |
Direct vendor intelligence
1 currentAuthoritative 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.
CVE-2026-44222 · CSAF 2.0 · revision 3 · finalRed Hat Product Securityvllm: vLLM: Denial of Service via malformed multimodal input or token injection
The vendor explicitly identifies these products as affected by this CVE.
- rhaiis/vllm-cpu-rhel9 as a component of Red Hat AI Inference Server
- rhaiis/vllm-neuron-rhel9 as a component of Red Hat AI Inference Server
- rhaiis/vllm-tpu-rhel9 as a component of Red Hat AI Inference Server
- rhelai3/bootc-aws-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3
- rhelai3/bootc-azure-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3
- rhelai3/bootc-azure-rocm-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3
- rhelai3/bootc-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3
- rhelai3/bootc-gcp-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3
- rhelai3/bootc-rocm-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3
- rhoai/odh-vllm-cuda-rhel9 as a component of Red Hat OpenShift AI (RHOAI)
- rhoai/odh-vllm-gaudi-rhel9 as a component of Red Hat OpenShift AI (RHOAI)
- rhoai/odh-vllm-rocm-rhel9 as a component of Red Hat OpenShift AI (RHOAI)
- Summary
- A flaw was found in vLLM, an inference and serving engine for large language models (LLMs). This vulnerability allows unauthenticated attackers to cause a Denial of Service (DoS) by supplying image or video placeholder sequences without matching data, leading to an unhandled error and worker termination. Additionally, text-only prompts containing special tokens can be misinterpreted as control commands, potentially leading to unexpected behavior.
- Remediation
- For more information visit https://access.redhat.com/errata/RHSA-2026:61627
Medium technical severity with public exploit material referenced by a structured source; prioritise exposed affected systems while verifying vendor guidance.
Patch available01
What, why and how
vLLM is an inference and serving engine for large language models (LLMs). From 0.6.1 to before 0.20.0, there is a a Token Injection vulnerability in vLLM’s multimodal processing. Unauthenticated, text-only prompts that spell special tokens are interpreted as control. Image and video placeholder sequences supplied without matching data cause vLLM to index into empty grids during input-position computation, raising an unhandled IndexError and terminating the worker or degrading availability. Multimodal paths that rely on image_grid_thw/video_grid_thw are affected. This vulnerability is fixed in 0.20.0.
What
vLLM is an inference and serving engine for large language models (LLMs). From 0.6.1 to before 0.20.0, there is a a Token Injection vulnerability in vLLM’s multimodal processing. Unauthenticated, text-only prompts that spell special tokens are interpreted as control. Image and video placeholder sequences supplied without matching data cause vLLM to index into empty grids during input-position computation, raising an unhandled IndexError and terminating the worker or degrading availability. Multimodal paths that rely on image_grid_thw/video_grid_thw are affected. This vulnerability is fixed in 0.20.0.
Why
The product uses untrusted input when calculating or using an array index, but the product does not validate or incorrectly validates the index to ensure the index references a valid position within the array.
How
An attacker operating through a network path may attempt exploitation with low privileges. If successful, the issue may cause the confidentiality, integrity or availability impact described by the vendor.
What
vLLM is an inference and serving engine for large language models (LLMs). From 0.6.1 to before 0.20.0, there is a a Token Injection vulnerability in vLLM’s multimodal processing. Unauthenticated, text-only prompts that spell special tokens are interpreted as control. Image and video placeholder sequences supplied without matching data cause vLLM to index into empty grids during input-position computation, raising an unhandled IndexError and terminating the worker or degrading availability. Multimodal paths that rely on image_grid_thw/video_grid_thw are affected. This vulnerability is fixed in 0.20.0.
Why
The product uses untrusted input when calculating or using an array index, but the product does not validate or incorrectly validates the index to ensure the index references a valid position within the array.
How
An attacker operating through a network path may attempt exploitation with low privileges. 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 No confirmed evidence
?
Confirmed exploitation and public exploit material are separate signals. Attacks can occur without public proof-of-concept or exploit code.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 Reference recorded
?
Confirmed exploitation and public exploit material are separate signals. Attacks can occur without public proof-of-concept or exploit code.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 → Improper Validation of Array Index → cause the confidentiality, integrity or availability impact described by the vendor
- Attack surface
- Network
- Privileges required
- Low: a basic authenticated account is required
- 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-129 ↗
CWE-129: Improper Validation of Array Index. The product uses untrusted input when calculating or using an array index, but the product does not validate or incorrectly validates the index to ensure the index references a valid position within the array.
- 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:L/UI:N/S:U/C:N/I:N/A:HCommon 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.PRLowPrivileges required: The attacker needs basic user-level privileges.UINoneUser interaction: No action by another user is required.SUnchangedScope: The security impact remains within the vulnerable component's authority.CNoneConfidentiality impact: No direct loss is represented by this metric.INoneIntegrity impact: No direct loss is represented by this metric.AHighAvailability impact: A successful attack can cause a major loss.- Post-exploitation / living off the land
- Stolen credentials, tokens and legitimate administration functions may provide continued access without deploying a large custom toolset.
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
- rhaiis/vllm-cpu-rhel9 as a component of Red Hat AI Inference Server
- rhaiis/vllm-neuron-rhel9 as a component of Red Hat AI Inference Server
- rhaiis/vllm-tpu-rhel9 as a component of Red Hat AI Inference Server
- rhelai3/bootc-aws-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3
- rhelai3/bootc-azure-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3
- rhelai3/bootc-azure-rocm-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3
- rhelai3/bootc-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3
- rhelai3/bootc-gcp-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3
- rhelai3/bootc-rocm-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3
- rhoai/odh-vllm-cuda-rhel9 as a component of Red Hat OpenShift AI (RHOAI)
- rhoai/odh-vllm-gaudi-rhel9 as a component of Red Hat OpenShift AI (RHOAI)
- rhoai/odh-vllm-rocm-rhel9 as a component of Red Hat OpenShift AI (RHOAI)
- Fixed
- registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:44224455142130c9594b4361fd21494c88244acb59b242f31ecb66019a5238dd_arm64 as a component of Red Hat AI Inference Server 3.2
- registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:e2a077acf23766ef900942296ce963a624d2c4b45ff22ca77cadeb94c051fd95_amd64 as a component of Red Hat AI Inference Server 3.2
- registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:7536efb184e4161d6b8a11477392b93613408c7d68daebb5cbad73b57a985e26_amd64 as a component of Red Hat AI Inference Server 3.2
- registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:590f1bb37f9c9abb51a6ff7f557b45f1dcfba2e4880de979290703c2e6de95be_s390x as a component of Red Hat AI Inference Server 3.3
- registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:e54618292d1e6f1c9c959a42160bad3a153ca7e050665739d3ddd9dbfda541f8_ppc64le as a component of Red Hat AI Inference Server 3.3
- registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:f3dfb688e524f44f071f20954e454a91013a9c48f8cc59a32f7f402bb61d8ed0_amd64 as a component of Red Hat AI Inference Server 3.3
- Action
- For more information visit https://access.redhat.com/errata/RHSA-2026:61627
- 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 12 May 2026 · Last source change 13 May 2026, 12:24 UTC · CWE-129 · Improper Validation of Array Index
CVE recordCVE.org · 5.2
CVSS sourceCNA
EPSS source FIRST · tracked since 2026-08-14
?
The date BlackTree first stored a score for this CVE from the daily FIRST EPSS feed.European sourceENISA EUVD · EUVD-2026-29799
Product sourceVendor CSAF · Red Hat Product Security
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
View recent updates ↗What changed after publication
- Affected versionsThe structured affected or fixed version information changed.Red Hat Product Security ↗
- Before
- >= 0.6.1, < 0.20.0 · Fixed: No fixed version is explicitly recorded in the structured CVE data.
- After
- >= 0.6.1, < 0.20.0 · Fixed: For more information visit https://access.redhat.com/errata/RHSA-2026:61627
- Remediation statusRemediation status changed from Awaiting fix to Patch available.Red Hat Product Security ↗
- Before
- Awaiting fix
- After
- Patch available
- Vendor guidanceAuthoritative vendor guidance changed from remediation: access.redhat.com/CVE-2026-44222 to remediation: access.redhat.com/CVE-2026-44222.Red Hat Product Security ↗
- Before
- remediation: access.redhat.com/CVE-2026-44222
- After
- remediation: access.redhat.com/CVE-2026-44222
- Affected versionsThe structured affected or fixed version information changed.Red Hat Product Security ↗
- Before
- rhaiis/vllm-cpu-rhel9 as a component of Red Hat AI Inference Server; rhaiis/vllm-cuda-rhel9 as a component of Red Hat AI Inference Server; rhaiis/vllm-neuron-rhel9 as a component of Red Hat AI Inference Server; rhaiis/vllm-rocm-rhel9 as a component of Red Hat AI Inference Server; rhaiis/vllm-tpu-rhel9 as a component of Red Hat AI Inference Server; rhelai3/bootc-aws-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-azure-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-azure-rocm-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-gcp-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-rocm-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhoai/odh-vllm-cuda-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-vllm-gaudi-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-vllm-rocm-rhel9 as a component of Red Hat OpenShift AI (RHOAI) · Fixed: registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:590f1bb37f9c9abb51a6ff7f557b45f1dcfba2e4880de979290703c2e6de95be_s390x as a component of Red Hat AI Inference Server 3.3; registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:e54618292d1e6f1c9c959a42160bad3a153ca7e050665739d3ddd9dbfda541f8_ppc64le as a component of Red Hat AI Inference Server 3.3; registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:f3dfb688e524f44f071f20954e454a91013a9c48f8cc59a32f7f402bb61d8ed0_amd64 as a component of Red Hat AI Inference Server 3.3
- After
- rhaiis/vllm-cpu-rhel9 as a component of Red Hat AI Inference Server; rhaiis/vllm-neuron-rhel9 as a component of Red Hat AI Inference Server; rhaiis/vllm-tpu-rhel9 as a component of Red Hat AI Inference Server; rhelai3/bootc-aws-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-azure-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-azure-rocm-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-gcp-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-rocm-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhoai/odh-vllm-cuda-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-vllm-gaudi-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-vllm-rocm-rhel9 as a component of Red Hat OpenShift AI (RHOAI) · Fixed: registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:44224455142130c9594b4361fd21494c88244acb59b242f31ecb66019a5238dd_arm64 as a component of Red Hat AI Inference Server 3.2; registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:e2a077acf23766ef900942296ce963a624d2c4b45ff22ca77cadeb94c051fd95_amd64 as a component of Red Hat AI Inference Server 3.2; registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:7536efb184e4161d6b8a11477392b93613408c7d68daebb5cbad73b57a985e26_amd64 as a component of Red Hat AI Inference Server 3.2; registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:590f1bb37f9c9abb51a6ff7f557b45f1dcfba2e4880de979290703c2e6de95be_s390x as a component of Red Hat AI Inference Server 3.3; registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:e54618292d1e6f1c9c959a42160bad3a153ca7e050665739d3ddd9dbfda541f8_ppc64le as a component of Red Hat AI Inference Server 3.3; registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:f3dfb688e524f44f071f20954e454a91013a9c48f8cc59a32f7f402bb61d8ed0_amd64 as a component of Red Hat AI Inference Server 3.3
- Vendor guidanceAuthoritative vendor guidance changed from remediation: access.redhat.com/CVE-2026-44222 to remediation: access.redhat.com/CVE-2026-44222.Red Hat Product Security ↗
- Before
- remediation: access.redhat.com/CVE-2026-44222
- After
- remediation: access.redhat.com/CVE-2026-44222
- Remediation statusRemediation status changed from Mitigation available to Patch available.Red Hat Product Security ↗
- Before
- Mitigation available
- After
- Patch available
- Affected versionsThe structured affected or fixed version information changed.Red Hat Product Security ↗
- Before
- rhaiis/vllm-cpu-rhel9 as a component of Red Hat AI Inference Server; rhaiis/vllm-cuda-rhel9 as a component of Red Hat AI Inference Server; rhaiis/vllm-neuron-rhel9 as a component of Red Hat AI Inference Server; rhaiis/vllm-rocm-rhel9 as a component of Red Hat AI Inference Server; rhaiis/vllm-spyre-rhel9 as a component of Red Hat AI Inference Server; rhaiis/vllm-tpu-rhel9 as a component of Red Hat AI Inference Server; rhelai3/bootc-aws-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-azure-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-azure-rocm-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-gcp-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-rocm-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhoai/odh-vllm-cuda-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-vllm-gaudi-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-vllm-rocm-rhel9 as a component of Red Hat OpenShift AI (RHOAI)
- After
- rhaiis/vllm-cpu-rhel9 as a component of Red Hat AI Inference Server; rhaiis/vllm-cuda-rhel9 as a component of Red Hat AI Inference Server; rhaiis/vllm-neuron-rhel9 as a component of Red Hat AI Inference Server; rhaiis/vllm-rocm-rhel9 as a component of Red Hat AI Inference Server; rhaiis/vllm-tpu-rhel9 as a component of Red Hat AI Inference Server; rhelai3/bootc-aws-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-azure-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-azure-rocm-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-gcp-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-rocm-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhoai/odh-vllm-cuda-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-vllm-gaudi-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-vllm-rocm-rhel9 as a component of Red Hat OpenShift AI (RHOAI) · Fixed: registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:590f1bb37f9c9abb51a6ff7f557b45f1dcfba2e4880de979290703c2e6de95be_s390x as a component of Red Hat AI Inference Server 3.3; registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:e54618292d1e6f1c9c959a42160bad3a153ca7e050665739d3ddd9dbfda541f8_ppc64le as a component of Red Hat AI Inference Server 3.3; registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:f3dfb688e524f44f071f20954e454a91013a9c48f8cc59a32f7f402bb61d8ed0_amd64 as a component of Red Hat AI Inference Server 3.3
CVE published
Fixed release recorded from official guidance
Fixed release recorded from official guidance
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.