Evidence used
- No CISA KEV confirmation is currently recorded.
- The selected CVSS metric records a network-reachable, unauthenticated path with no user interaction.
- EPSS is 0.41% for the current model date.
BlackTreeCVE IntelligenceFull vulnerability report · 2026
CVE-2026-73555High confidence
vLLM: Unauthenticated Internal Path and Username Disclosure via Validation Error Messages
vllm-project · vllm
Official source article: GitHub GHSA-HWRM-C4CX-RF4J ↗. Check the applicable product and release in the original source.
5.3MediumCVSS 3.1
Patch only the product branches with a verified fix
Fix availability varies by productMedium technical severity with no CISA KEV confirmation; remediate through the normal risk-based patch cycle unless local exposure raises the priority. Verified remediation exists for at least one product or source, but 26 structured product or package states remain unresolved. Apply remediation only to the exact product branch confirmed by its source.
R
Open reassessment dashboard →Operational reassessment
Published severity in operational context
Published severityMedium→Operational priority:Medium, unchanged from published severity.unchanged
Compensating controls
- Validate the affected product branch and deploy the verified fixed release.
- Restrict the affected network interface to trusted sources where business-safe.
- Monitor vendor guidance and exploitation sources for a material change.
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.
Remediation availability differs by product scope
Verified remediation exists for at least one product or source, but 26 structured product or package states remain unresolved. Apply remediation only to the exact product branch confirmed by its source.
- Red Hat Product Security: 26 affected or under-investigation product states without a fixed product state in the same current advisory
Open-source package ranges3 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; fixed 0.26.0 | 0.26.0 | OSV record ↗aggregator derived · 10 Sep 2026 |
| PyPIvllm | ECOSYSTEM: introduced 0; fixed 0.26.0 | 0.26.0 | OSV record ↗source linked ecosystem record · 10 Sep 2026 |
| pipvllm | < 0.26.0 | 0.26.0 | GitHub advisory ↗upstream repository advisory · 4 Sep 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-2026-73555 · CSAF 2.0 · revision 3 · finalRed Hat Product Securityvllm: vLLM: Information Disclosure via Validation Error Messages
The vendor explicitly identifies these products as affected by this CVE.
- rhaii/vllm-cpu-rhel9 as a component of Red Hat AI Inference Server
- rhaii/vllm-cuda-rhel9 as a component of Red Hat AI Inference Server
- rhaii/vllm-gaudi-rhel9 as a component of Red Hat AI Inference Server
- rhaii/vllm-neuron-rhel9 as a component of Red Hat AI Inference Server
- rhaii/vllm-rocm-rhel9 as a component of Red Hat AI Inference Server
- rhaii/vllm-spyre-rhel9 as a component of Red Hat AI Inference Server
- rhaii/vllm-tpu-rhel9 as a component of Red Hat AI Inference Server
- 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
- Summary
- A flaw was found in vLLM, an inference and serving engine for large language models. Unauthenticated attackers can send malformed JSON requests to various API endpoints, triggering validation errors. The system's error handling mechanism converts these validation errors into strings without properly sanitizing traceback-style file paths. This vulnerability allows for the disclosure of sensitive internal system information, including the operating system username, home and virtual environment paths, Python version, internal package structure, and handler function names.
- Remediation
- Fix deferred
Medium technical severity with no CISA KEV confirmation; remediate through the normal risk-based patch cycle unless local exposure raises the priority. Verified remediation exists for at least one product or source, but 26 structured product or package states remain unresolved. Apply remediation only to the exact product branch confirmed by its source.
Fix availability varies by product01
What, why and how
vLLM is an inference and serving engine for large language models. Prior to 0.26.0, the validation_exception_handler in vllm/entrypoints/openai/server_utils.py converts FastAPI RequestValidationError objects with str(exc), and sanitize_message in vllm/entrypoints/utils.py does not remove traceback-style file paths, allowing unauthenticated malformed JSON requests to /v1/chat/completions, /v1/completions, /tokenize, and /detokenize to disclose the OS username, home and virtual-environment paths, Python version, internal package structure, line numbers, and endpoint handler names. This issue is fixed in version 0.26.0.
What
vLLM is an inference and serving engine for large language models. Prior to 0.26.0, the validation_exception_handler in vllm/entrypoints/openai/server_utils.py converts FastAPI RequestValidationError objects with str(exc), and sanitize_message in vllm/entrypoints/utils.py does not remove traceback-style file paths, allowing unauthenticated malformed JSON requests to /v1/chat/completions, /v1/completions, /tokenize, and /detokenize to disclose the OS username, home and virtual-environment paths, Python version, internal package structure, line numbers, and endpoint handler names. This issue is fixed in version 0.26.0.
Why
The product generates an error message that includes sensitive information about its environment, users, or associated data.
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 is an inference and serving engine for large language models. Prior to 0.26.0, the validation_exception_handler in vllm/entrypoints/openai/server_utils.py converts FastAPI RequestValidationError objects with str(exc), and sanitize_message in vllm/entrypoints/utils.py does not remove traceback-style file paths, allowing unauthenticated malformed JSON requests to /v1/chat/completions, /v1/completions, /tokenize, and /detokenize to disclose the OS username, home and virtual-environment paths, Python version, internal package structure, line numbers, and endpoint handler names. This issue is fixed in version 0.26.0.
Why
The product generates an error message that includes sensitive information about its environment, users, or associated data.
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 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 None recorded
?
Confirmed exploitation and public exploit material are separate signals. Attacks can occur without public proof-of-concept or exploit code.No exploit-tagged reference or CISA SSVC proof-of-concept state is currently recorded. Research may still exist outside the structured feeds.
- Likely attack path
- a network path → Generation of Error Message Containing Sensitive Information → 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-209 ↗
CWE-209: Generation of Error Message Containing Sensitive Information. The product generates an error message that includes sensitive information about its environment, users, or associated data.
- 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:L/I:N/A:NCommon 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.CLowConfidentiality impact: A successful attack can cause a limited loss.INoneIntegrity impact: No direct loss is represented by this metric.ANoneAvailability impact: No direct loss is represented by this metric.- 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. - Fix availability varies by product
- Affected
- rhaii/vllm-cpu-rhel9 as a component of Red Hat AI Inference Server
- rhaii/vllm-cuda-rhel9 as a component of Red Hat AI Inference Server
- rhaii/vllm-gaudi-rhel9 as a component of Red Hat AI Inference Server
- rhaii/vllm-neuron-rhel9 as a component of Red Hat AI Inference Server
- rhaii/vllm-rocm-rhel9 as a component of Red Hat AI Inference Server
- rhaii/vllm-spyre-rhel9 as a component of Red Hat AI Inference Server
- rhaii/vllm-tpu-rhel9 as a component of Red Hat AI Inference Server
- 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-gaudi-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-kserve-agent-rhel9 as a component of Red Hat OpenShift AI (RHOAI)
- rhoai/odh-kserve-controller-rhel9 as a component of Red Hat OpenShift AI (RHOAI)
- rhoai/odh-kserve-router-rhel9 as a component of Red Hat OpenShift AI (RHOAI)
- rhoai/odh-kserve-storage-initializer-rhel9 as a component of Red Hat OpenShift AI (RHOAI)
- rhoai/odh-llm-d-kv-cache-rhel9 as a component of Red Hat OpenShift AI (RHOAI)
- rhoai/odh-vllm-gaudi-rhel9 as a component of Red Hat OpenShift AI (RHOAI)
- Fixed
- 0.26.0.
- Action
- Use the product-specific evidence above. Patch only products with a verified fixed release, and keep every affected or under-investigation state without a matching fix in the remediation queue.
- Workaround
- A mitigation or workaround reference is available from the source linked below; validate it against the affected product and version.
04
Evidence and provenance
Published 13 Aug 2026 · Last source change 14 Aug 2026, 15:57 UTC · CWE-209 · Generation of Error Message Containing Sensitive Information
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-2026-58053
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
- Vendor guidanceAuthoritative vendor guidance changed: added mitigation: github.com/GHSA-hwrm-c4cx-rf4j; added patch: github.com/46415; removed remediation: github.com/GHSA-hwrm-c4cx-rf4j; 2 further additions.security-advisories@github.com ↗
- Before
- remediation: github.com/GHSA-hwrm-c4cx-rf4j
- After
- mitigation: github.com/GHSA-hwrm-c4cx-rf4j · patch: github.com/46415 · patch: github.com/e87521626febe2763f997691d1599de4175f4324 · 1 more references
- Affected versionsThe structured affected or fixed version information changed.CNA ↗
- Before
- < 0.26.0 · Fixed: 0.26.0.
- After
- vllm: < 0.26.0 · Fixed: 0.26.0.
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.