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NVIDIA TensorRT-LLM EUVDEUVD-2026-44453

| CVE-2026-47473 HIGH
Write-what-where Condition (CWE-123)
2026-07-14 nvidia GHSA-472c-jr5h-crh5
7.4
CVSS 3.1 · Vendor: nvidia
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Severity by source

Vendor (nvidia) PRIMARY
7.4 HIGH
AV:L/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:H
vuln.today AI
7.4 HIGH

Write-what-where reachable only via local process access with memory-shaping needed gives AV:L and AC:H; a controllable arbitrary write yields full C/I/A High impact within an unchanged scope.

3.1 AV:L/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:H
4.0 AV:L/AC:H/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N

Primary rating from Vendor (nvidia).

CVSS VectorVendor: nvidia

CVSS:3.1/AV:L/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:H
Attack Vector
Local
Attack Complexity
High
Privileges Required
None
User Interaction
None
Scope
Unchanged
Confidentiality
High
Integrity
High
Availability
High

Lifecycle Timeline

2
Analysis Generated
Jul 14, 2026 - 21:20 vuln.today
CVE Published
Jul 14, 2026 - 20:03 cve.org
HIGH 7.4

DescriptionCVE.org

NVIDIA TensorRT-LLM contains a vulnerability where an attacker could cause a write-what-where condition. A successful exploit of this vulnerability might lead to data tampering, denial of service, and information disclosure.

AnalysisAI

Memory corruption in NVIDIA TensorRT-LLM allows an attacker with local access to trigger a write-what-where primitive (CWE-123), enabling arbitrary memory writes that can corrupt data, crash the inference service, or leak sensitive information. The flaw carries a CVSS 7.4 (High) score with a local attack vector and high attack complexity, and affects the TensorRT-LLM library used to build and serve optimized large-language-model inference on NVIDIA GPUs. …

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Attack ChainAIDerived

Hypothetical attack flow derived from CVE metadata

Access
Gain local access to TensorRT-LLM host/process
Delivery
Supply crafted input or model artifact
Exploit
Trigger write-what-where via controllable offset
Execution
Overwrite target memory location/pointer
Impact
Corrupt data, leak info, or crash service

Vulnerability AssessmentAI

Exploitation Exploitation requires local access to the system or process running NVIDIA TensorRT-LLM (AV:L) - this is not a remote, internet-facing unauthenticated flaw despite PR:N, which here reflects no formal authentication step in the modeled local path. … Additional conditions and limiting factors are described in the full assessment.
Risk Assessment The signals are mixed and point to a real-but-not-urgent issue. … Full risk analysis with EPSS, KEV, and SSVC signal comparison available after sign-in.
Exploit Scenario An attacker who can supply crafted inputs or artifacts to a locally reachable TensorRT-LLM inference process manipulates a controllable offset/pointer to write an attacker-chosen value to an attacker-chosen memory location. By repeatedly shaping memory (consistent with the AC:H requirement), they corrupt a control structure to leak model or process data, tamper with outputs, or crash the service. …
Remediation No vendor-released patch identified at time of analysis in the provided data - check NVIDIA's official security bulletin for TensorRT-LLM and upgrade to the fixed release once published (the CVE was reported by NVIDIA, so a vendor advisory is expected). … Detailed patch versions, workarounds, and compensating controls in full report.

Recommended ActionAI

Within 24 hours, inventory all production and development systems running NVIDIA TensorRT-LLM and implement OS-level access controls to restrict local login privileges; disable non-critical TensorRT-LLM services and document all active deployments for risk prioritization. …

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EUVD-2026-44453 vulnerability details – vuln.today

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