CVE-2026-73559

Published: Ago 13, 2026 Last Modified: Ago 14, 2026

ExploitDB:

Other exploit source:

Google Dorks:

MEDIUM 6,5

Source: [email protected]

Attack Vector: network

Attack Complexity: low

Privileges Required: low

User Interaction: none

Scope: unchanged

Confidentiality: none

Integrity: none

Availability: high

Description

AI Translation Available

vLLM is an inference and serving engine for large language models. From 0.19.0 until 0.26.0, the /v1/completions CompletionRequest.prompt field in vllm/entrypoints/openai/completion/protocol.py accepts an unbounded list[str] or list[list[int]], prompt_to_seq() in vllm/renderers/inputs/preprocess.py and OnlineRenderer.preprocess_completion() in vllm/renderers/online_renderer.py expand every element, and vllm/entrypoints/openai/completion/serving.py creates one engine generator and response slot per prompt, allowing an authenticated API client to exhaust CPU, memory, async scheduling capacity, engine request slots, and response buffering with one request. This issue is fixed in version 0.26.0.

EPSS (Exploit Prediction Scoring System)

Trend Analysis

EPSS (Exploit Prediction Scoring System)

Prevede la probabilità di sfruttamento basata su intelligence sulle minacce e sulle caratteristiche della vulnerabilità.

EPSS Score

0,0039

Percentile

0,3th

Updated

Single Data Point

Only one EPSS measurement is available for this CVE. Trend analysis requires multiple data points over time.

400

Uncontrolled Resource Consumption

Draft

Abstraction: Class Structure: Simple

Common Consequences

Security Scopes Affected:

Availability Access Control Other

Potential Impacts:

Dos: Crash, Exit, Or Restart Dos: Resource Consumption (Cpu) Dos: Resource Consumption (Memory) Dos: Resource Consumption (Other) Bypass Protection Mechanism Other