Attack ChainAIDerived
Hypothetical attack flow derived from CVE metadata – not a confirmed exploit chain
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AccessObtain low-privileged Triton account
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DeliveryCraft malicious DALI pipeline input
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ExploitSubmit request to DALI-enabled endpoint
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ExecutionTrigger user interaction to execute pipeline
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PersistDALI backend consumes uncontrolled resources
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ImpactTriton server becomes unavailable
Vulnerability Assessment
| Weakness |
CWE
OWASP Top 10:2025
A06:2025 - Insecure Design
ASVS 5.0
V2 - Validation and Business Logic Resource consumption limits
MITRE ATT&CK
1 technique across 1 tactic: Impact The technique list with ATT&CK links and the kill-chain view is part of the Basic plan and up. |
| Exploitation Conditions | The attacker must hold a low-privileged account on the Triton Inference Server (PR:L from CVSS vector - unauthenticated exploitation is not indicated). The DALI backend must be enabled and accessible to the attacker's account. User interaction is required (UI:R from CVSS vector), meaning exploitation cannot be fully automated without some action from an authorized user or the attacker acting in their own low-privileged context. Exploitation is limited to availability impact only - no confidentiality or integrity compromise is possible per the CVSS vector (C:N/I:N). The scope is unchanged (S:U), meaning the vulnerability cannot be used to pivot beyond the Triton server process. Deployments where the DALI backend is disabled or where inference API access is restricted to fully trusted internal accounts are not meaningfully exposed. |
| Impact | The CVSS vector (AV:N/AC:L/PR:L/UI:R/S:U/C:N/I:N/A:H) characterizes this as a medium-severity, network-exploitable denial-of-service affecting availability only. The PR:L requirement means an attacker must hold at least a low-privileged account on the Triton instance, reducing the exposed attack surface compared to unauthenticated vulnerabilities. The UI:R flag is atypical for a pure server-side DoS and may indicate an administrator or authorized user must trigger a specific action (e.g., loading a model pipeline or submitting a particular inference request type) for exploitation to succeed. No EPSS score was provided in the input data, so exploitation probability cannot be quantified. There is no CISA KEV listing and no public exploit code identified, suggesting this has not been observed in active campaigns. The overall real-world risk is moderate: deployments exposing Triton's inference endpoints to untrusted authenticated users (e.g., shared multi-tenant inference infrastructure) face the highest practical risk, while air-gapped or single-tenant deployments are significantly less exposed. |
| Exploit ScenarioDerived | An attacker with a low-privileged account on a shared Triton Inference Server instance crafts a malicious DALI pipeline or inference request designed to consume disproportionate server resources (CPU, memory, or threads). After an authorized user or the attacker themselves triggers execution of the malicious pipeline - satisfying the UI:R condition - the DALI backend processes the request without enforcing resource limits, causing the server process to degrade or become unresponsive, denying service to other legitimate inference clients. No public exploit code has been identified at time of analysis. |
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Alert meAnalysisAIv1 – May 20, 2026
Uncontrolled resource consumption in NVIDIA Triton Inference Server's DALI backend allows a network-adjacent, low-privileged attacker to exhaust server resources, resulting in denial of service. The vulnerability (CWE-400) is triggered through the DALI data-loading and augmentation backend, requires low privileges and user interaction, and carries a CVSS score of 5.7 (Medium). No public exploit code or CISA KEV listing has been identified at time of analysis, placing this in a monitored-but-not-critical-urgency tier for most deployments.
RemediationAI
Patch available per vendor advisory - consult the NVIDIA support article at https://nvidia.custhelp.com/app/answers/detail/a_id/5828 for the specific patched release version, as no exact fix version was included in the available input data. In the interim, if the DALI backend is not required for current inference workloads, disabling or restricting access to DALI-backed model endpoints reduces the attack surface without impacting non-DALI model serving. Access controls should be reviewed to ensure that only trusted, explicitly authorized users hold credentials to submit inference requests against the affected server. Rate-limiting and resource quotas at the infrastructure layer (e.g., Kubernetes resource limits, reverse proxy request throttling) can serve as compensating controls to bound the impact of a resource exhaustion attempt, though these do not eliminate the underlying vulnerability. Network segmentation to prevent untrusted or low-trust users from reaching Triton's API port is recommended as an additional defense layer.
Affected VersionsENISA
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Technical ContextAI · show details
NVIDIA Triton Inference Server is an open-source inference serving platform supporting multiple ML frameworks. The DALI (Data Loading Library) backend is an NVIDIA-developed accelerated data-loading and preprocessing pipeline used within Triton to handle input data for inference requests. CWE-400 (Uncontrolled Resource Consumption) indicates the root cause is a failure to impose appropriate limits on resource usage - such as CPU cycles, memory, threads, or file handles - when processing attacker-controlled input through the DALI pipeline. The affected scope per CPE (cpe:2.3:a:nvidia:triton_inference_server:*:*:*:*:*:*:*:*) covers all versions of the server application without a defined upper or lower version bound in the available data.
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Severity by source
AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Primary rating from NVD · only source for this CVE.
CVSS VectorNVD
Lifecycle Timeline
2DescriptionNVD
NVIDIA Triton Inference Server contains a vulnerability in the DALI backend, where an attacker could cause uncontrolled resource consumption. A successful exploit of this vulnerability might lead to denial of service.
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
Denial of Service attacks render applications or systems unavailable by overwhelming resources or triggering failure conditions.
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EUVD-2026-31053
GHSA-f637-j435-xwhv
NVD
CVE.org
EPSS
Vulnrichment
VulDB
Exploit-DB