Attack ChainAIDerived
Hypothetical attack flow derived from CVE metadata – not a confirmed exploit chain
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AccessGain local/adjacent access to TensorRT-LLM host
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DeliverySubmit crafted input to inference service
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ExploitCoerce server-side request to internal resource (SSRF)
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ExecutionRetrieve or tamper with internal data
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ImpactInformation disclosure and data tampering
Vulnerability Assessment
| Weakness |
CWE
OWASP Top 10:2025
A01:2025 - Broken Access Control
ASVS 5.0
V4 - API and Web Service URL allowlisting, SSRF prevention
MITRE ATT&CK
2 techniques across 2 tactics: Initial Access, Credential Access The technique list with ATT&CK links and the kill-chain view is part of the Basic plan and up. |
| Exploitation Conditions | The CVSS vector sets AV:L, so exploitation requires local or adjacent access to the system or service running TensorRT-LLM rather than remote internet reachability; PR:N and UI:N mean no authentication and no user interaction are needed once that access is obtained, and AC:L means no special timing or configuration hurdle is described. The exact feature, API endpoint, or input that triggers the server-side request is NOT described in the available sources (NVIDIA advisory 2026/5883, NVD, CVE.org). The primary limiting factor is the local/adjacent attack vector - an attacker must already be positioned on or beside the inference host, which materially narrows realistic exposure compared to a network-facing SSRF. Affected version per EUVD is TensorRT-LLM 1.3.0rc24. |
| Impact | This is a moderate-severity SSRF (CWE-918) in NVIDIA TensorRT-LLM, scored CVSS 7.1 by NVIDIA (the reporting vendor) with vector AV:L/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N. The signals are mixed and partly conflicting. Notably, the CVSS vector specifies AV:L (local attack vector) even though SSRF is typically a network-reachable class - this suggests the attacker must already have local/adjacent access to the host or the inference service interface rather than reaching it from the open internet; this should be verified against the NVIDIA advisory. There is a second internal inconsistency: NVIDIA's vector sets I:N (no integrity impact), yet the description explicitly states the exploit 'might lead to information disclosure and data tampering' - data tampering implies an integrity impact, so the I:N rating and the description disagree and should be reconciled with the vendor. The vuln.today priority is 'this_week' (not act_now/emergency). KEV status is not present in the input, so this is NOT confirmed actively exploited. No EPSS score was provided, and no SSVC decision fields were supplied. The only references are NVD/CVE.org mirrors and the NVIDIA product-security advisory directory - none of these is a verified working exploit. On balance this is a real but non-emergency, this-week-priority issue: the low attack vector and the absence of confirmed exploitation lower urgency relative to the 7.1 base score, but the scope-change (S:C) and high confidentiality impact keep it above purely theoretical risk. |
| Exploit ScenarioDerived | An attacker with local or adjacent access to a host running TensorRT-LLM submits input that coerces the server into making an attacker-controlled request to internal resources, retrieving data the attacker should not reach (information disclosure) and potentially altering data (per the description). No public exploit code was identified at the time of analysis; only the NVIDIA product-security advisory and NVD/CVE mirrors are referenced. Because the CVSS vector is AV:L/AC:L/PR:N, exploitation is low-complexity and needs no authentication but requires local/adjacent positioning rather than remote internet access. |
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Alert meAnalysisAIv1 – Oct 28, 2026
Server-side request forgery (CWE-918) in NVIDIA TensorRT-LLM, reported by NVIDIA at CVSS 7.1, allows an attacker positioned with local or adjacent access to the inference host to make the service issue requests to attacker-influenced destinations, yielding high confidentiality impact and possible data tampering under a scope change. No authentication and no user interaction are required once that local/adjacent access is obtained, and AC:L means no special timing or configuration hurdle is described. There is no public exploit identified at time of analysis and the CVE is not in CISA KEV; the EUVD record lists TensorRT-LLM 1.3.0rc24 as affected and the vuln.today decision label is this_week.
RemediationAI
No vendor-released patch identified at time of analysis: none of the supplied references (NVIDIA advisory 2026/5883, NVD, CVE.org) states a fixed version, so no patched release number can be cited and the NVIDIA advisory should be monitored for an update. Because the triggering feature is not described in the available sources, mitigation has to be applied at the network and access layers. First, restrict outbound egress from TensorRT-LLM inference hosts to an explicit allowlist of model, tokenizer and artifact sources, since the whole point of an SSRF is reaching destinations the server can see and the attacker cannot; the trade-off is that legitimate fetches from arbitrary URLs or internal mirrors will break and must be added to the allowlist. Second, tighten who can reach the inference service at all - the vector is AV:L with PR:N/UI:N, so anyone who can already interact with the host or its local/adjacent interfaces needs no credentials to attempt exploitation; limiting shell and local socket access to trusted operators and segregating the inference host from management and cloud-metadata networks reduces reachable SSRF targets, at the cost of added operational friction. Third, if an external artifact fetch path is identified in your deployment, serve those artifacts from a controlled local mirror rather than accepting user-supplied locations, understanding that this depends on confirming which interface is affected, which the current sources do not document.
Affected VersionsENISA
Affected Packages
Source: OSV (Open Source Vulnerabilities)
Affects your stack
Affects 1 package in euvd
Checking this CVE against your own stacks and servers is part of the Basic plan and up.
Technical ContextAI · show details
TensorRT-LLM is NVIDIA's open-source library and serving stack for building, optimizing and running large language model inference, typically deployed on GPU hosts that fetch model weights, tokenizer files and related artifacts. The assigned weakness is CWE-918 (Server-Side Request Forgery): the server constructs or follows an outbound request whose destination is influenced by untrusted input without adequate validation of the target, so the attacker can pivot the request into networks or services the server can reach but the attacker cannot. The CVSS vector carries S:C, meaning the impacted component (the forged request's destination) is a different security authority from the vulnerable TensorRT-LLM component, which is why confidentiality is rated high despite the local attack vector. NVIDIA's score is C:H/I:N/A:N; the independent assessment keeps C:H but raises integrity to I:L to reflect possible data tampering. Notably, the specific feature, API endpoint or input that triggers the outbound request is not described in the available sources (NVIDIA advisory 2026/5883, NVD, CVE.org), and the affected version range in the CPE string is a wildcard, with EUVD naming only 1.3.0rc24.
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Severity by source
AV:L/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N
Kept NVIDIA's AV:L/AC:L/PR:N/S:C and C:H for SSRF information disclosure, but raised I:N to I:L to reflect the description's stated data tampering.
Primary rating from Vendor (nvidia).
CVSS VectorVendor: nvidia
DescriptionCVE.org
NVIDIA TensorRT-LLM contains a vulnerability where an attacker could cause a server-side request forgery. A successful exploit of this vulnerability might lead to information disclosure and data tampering.
Executive ViewAI
NVIDIA TensorRT-LLM, a component of AI inference infrastructure, contains a high-severity server-side request forgery (SSRF) vulnerability (CVE-2026-24269) that enables an attacker with local or adjacent network access to the inference host to redirect service requests to attacker-controlled destinations, potentially leading to data exposure and tampering. This affects organizations deploying TensorRT-LLM, exposing sensitive model data and inference results. Leadership should prioritize remediation to prevent unauthorized access and protect proprietary AI assets.
No vendor-released patch identified at time of analysis. Interim mitigations include restricting local and adjacent access to inference hosts, implementing network segmentation and egress filtering to block unauthorized outbound requests, and monitoring for anomalous SSRF attempts.
Threat Intelligence Overview
How this decision was reached
The engine reads each signal below and applies a fixed list of rules from top to bottom. The first rule that matches sets the recommended action – like a statement, every line is shown.
What every action level means
SSVC AssessmentENISA
Priority Score
Attack Technique
Server-Side Request Forgery exploits applications that fetch remote resources based on user-supplied URLs.
Information disclosure occurs when an application unintentionally exposes sensitive data that aids attackers in reconnaissance or directly compromises security.
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EUVD-2026-110821
GHSA-mx93-gv2q-hr6f
NVD
CVE.org
EPSS
Exploit-DB