Cyber Resilience

CVE-2026-0599

DoS

Published
02 February 2026
Modified
15 April 2026
CVSS Score v3 7.5
Click a component to see what it means
Raw vectorCVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
EPSS Score 0.22 97th percentile
Risk Priority 71 floored blend · peak EPSS

Summary

CVE-2026-0599 is a high-severity Uncontrolled Resource Consumption (CWE-400) vulnerability. Its CVSS base score is 7.5 (High).

Operationally, exploitation aligns with the MITRE ATT&CK technique OS Exhaustion Flood (T1499.001); ranked in the top 3% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.

This vulnerability is AI-related — categorised as NLP and Transformers; in the LLM/Generative AI Risks risk domain.

The strongest mitigations our analysis identified map to SC-5 (Denial-of-service Protection) and SC-6 (Resource Availability) — see the control section below for these in your framework.

EU & UK References

Vulnerability Data

A vulnerability in huggingface/text-generation-inference version 3.3.6 allows unauthenticated remote attackers to exploit unbounded external image fetching during input validation in VLM mode. The issue arises when the router scans inputs for Markdown image links and performs a blocking HTTP GET…

more

request, reading the entire response body into memory and cloning it before decoding. This behavior can lead to resource exhaustion, including network bandwidth saturation, memory inflation, and CPU overutilization. The vulnerability is triggered even if the request is later rejected for exceeding token limits. The default deployment configuration, which lacks memory usage limits and authentication, exacerbates the impact, potentially crashing the host machine. The issue is resolved in version 3.3.7.

CWE(s)

AI Security AnalysisAI

AI Category
NLP and Transformers
Risk Domain
LLM/Generative AI Risks
OWASP Top 10 for LLMs 2025
None mapped
Classification Reason
Matched keywords: huggingface, text-generation-inference

Related Threats

MITRE ATT&CK Enterprise Techniques

T1499.001 OS Exhaustion Flood Impact
Adversaries may launch a denial of service (DoS) attack targeting an endpoint's operating system (OS).
T1498 Network Denial of Service Impact
Adversaries may perform Network Denial of Service (DoS) attacks to degrade or block the availability of targeted resources to users.
T1499 Endpoint Denial of Service Impact
Adversaries may perform Endpoint Denial of Service (DoS) attacks to degrade or block the availability of services to users.
T1499.002 Service Exhaustion Flood Impact
Adversaries may target the different network services provided by systems to conduct a denial of service (DoS).
T1499.003 Application Exhaustion Flood Impact
Adversaries may target resource intensive features of applications to cause a denial of service (DoS), denying availability to those applications.
Derived from this CVE’s CWE(s) via the direct CWE→ATT&CK cross-walk.

CVEs Like This One

CVE-2026-40980Shared CWE-400
CVE-2025-6921Shared CWE-400
CVE-2025-48956Shared CWE-400
CVE-2023-52425Shared CWE-400
CVE-2024-20716Shared CWE-400
CVE-2025-9341Shared CWE-400
CVE-2026-21952Shared CWE-400
CVE-2025-0426Shared CWE-400
CVE-2026-9602Shared CWE-400
CVE-2025-65637Shared CWE-400

Affected Assets

Mitigating Controls

Mitigating Controls (NIST 800-53 r5) AI

SC-5 directly limits the effects of resource-exhaustion events that constitute uncontrolled consumption.

SC-6 enforces explicit allocation limits on resources, structurally preventing the weakness from occurring.

Process isolation confines resource consumption to separate domains, reducing blast radius without stopping the root flaw.

Mitigating Controls (NIST CSF 2.0) AI

Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.

PR.IR-04 mostly match
prevents

Explicitly requires monitoring and maintaining resource capacity, directly addressing uncontrolled consumption to preserve availability.

DE.CM-09 partial match
prevents

Continuous monitoring of computing resources can detect resource exhaustion but does not itself enforce allocation limits.

PR.IR-03 partial match
prevents

Resilience mechanisms such as avoiding single points of failure indirectly reduce impact of resource exhaustion.

PR.PS-01 partial match
prevents

Hardened configuration baselines can include resource quotas and limits that constrain consumption.

Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI

Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.

finds

Resource-utilization monitoring and alerting on bottlenecks or overloads limits the impact of denial-of-service or resource-exhaustion attacks.

prevents

By continuously monitoring utilization, stress-testing peak loads, and maintaining documented plans to scale or throttle resources, the control directly limits an attacker’s ability to drive a system into uncontrolled resource exhaustion.

finds

Pre-agreed severity-based prioritization and resource allocation during incident triage reduce the likelihood that an attacker-induced resource exhaustion will overwhelm the organization before corrective action is taken.

mitigates

Business-continuity plans that include resource-management controls reduce the likelihood that an attacker can trigger uncontrolled resource consumption by forcing the system into a degraded or fallback state.

mitigates

Defining RTOs and capacity requirements for ICT services during business-impact analysis forces organizations to provision sufficient resources and throttling mechanisms, reducing the likelihood that an attacker can induce denial-of-service through uncontrolled resource consumption.

finds

Early notification of anomalous resource consumption or system malfunctions enables throttling or isolation before availability is lost.

References