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vLLM CVE-2026-73560

| EUVDEUVD-2026-60377 MEDIUM
Server-Side Request Forgery (SSRF) (CWE-918)
2026-08-17 GitHub_M GHSA-4hhp-h66f-j5j7
6.5
CVSS 3.1 · Vendor: GitHub_M
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Attack ChainAIDerived

Hypothetical attack flow derived from CVE metadata – not a confirmed exploit chain

  1. Access
    Obtain low-privilege vLLM API credentials
  2. Delivery
    Submit multimodal inference request with crafted image or audio URL string
  3. Exploit
    MiMoV2OmniMultiModalProcessor invokes _fetch_image or requests.get bypassing MediaConnector allowlists
  4. Execution
    vLLM process fetches attacker-specified remote URL or local file path
  5. Impact
    Exfiltrate retrieved content from model response or error output

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

Exploitation requires authenticated API access to vLLM at the low-privilege level (confirmed by PR:L in the CVSS vector), meaning the attacker must possess a valid API key or equivalent credential to submit inference requests to the target vLLM instance. The vulnerable code path is only reachable when the vLLM server is configured to serve a MiMo V2 Omni model that instantiates MiMoV2OmniMultiModalProcessor - deployments using other model families or processor implementations are not affected by this specific bypass. The attacker must supply image or audio inputs as URL strings (http://, https://, file://) or bare filesystem paths rather than pre-decoded binary or tensor data; base64 data URIs (data:image) are also accepted by the vulnerable code. Exploitation impact is bounded by the vLLM process's OS-level file permissions and network reachability: a sandboxed deployment with restricted filesystem access and egress filtering materially reduces blast radius. No special network positioning, administrator-level access, specific operating system, or non-default runtime flags beyond MiMo V2 Omni model serving are required.

Impact

The CVSS:3.1 vector (AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N) scores 6.5 Medium, correctly reflecting low-complexity network exploitability requiring only low-privilege API access, with high confidentiality impact and no integrity or availability consequences. The PR:L requirement confirms that vLLM API credentials constitute the authentication barrier, limiting direct exposure to authorized but not necessarily trusted users. No public exploit code has been identified and this CVE is not listed in CISA KEV, meaning active exploitation is unconfirmed at time of analysis; EPSS data was not included in the provided intelligence sources. Despite the Medium score, the practical risk is elevated in environments where vLLM is exposed to semi-trusted or third-party API consumers: the vLLM process frequently runs with broad filesystem access to model weights, configuration files, and secrets, and the SSRF vector can reach cloud metadata services (169.254.169.254) or internal APIs with the vLLM host's network identity - even a mid-sized AI infrastructure team in mielec running vLLM behind a VPN for internal users should treat this as urgent if the MiMo V2 Omni processor is in use. The S:U scope designation is a modest understatement of real-world risk, as SSRF pivot to adjacent internal systems represents impact beyond the vulnerable system itself that the base vector does not capture.

Exploit ScenarioDerived

An authenticated vLLM API user submits a multimodal inference request targeting a MiMo V2 Omni model, embedding a crafted image URL pointing to an internal cloud metadata endpoint such as http://169.254.169.254/latest/meta-data/iam/security-credentials/ or a file:// path referencing sensitive files like environment variable files or service account keys accessible to the vLLM process. The MiMoV2OmniMultiModalProcessor calls _fetch_image or requests.get on the attacker-supplied string without consulting MediaConnector's allowlists, retrieves the target resource on behalf of the vLLM server, and the fetched content is processed as image or audio data - potentially surfacing portions of the retrieved content in error messages or inference outputs. No public proof-of-concept exploit code has been identified, but exploitation requires only a standard API call with a crafted multimodal input string.

This Month Plan within 30 days. Why: MEDIUM severity (CVSS 4.0-6.9).
Patch available 0.3% exploitation probability (EPSS)

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AnalysisAIv1 – Aug 17, 2026

Server-side request forgery in vLLM's MiMoV2OmniMultiModalProcessor allows authenticated API users to bypass the framework's media access controls, enabling arbitrary file reads on the vLLM host and SSRF requests to internal network resources. The flaw affects all vLLM releases prior to 0.26.0 where attacker-controlled image and audio URL strings were passed directly to _fetch_image, requests.get, and Image.open instead of routing through the MediaConnector abstraction that enforces allowed_media_domains and allowed_local_media_path restrictions. No public exploit code or CISA KEV listing exists at time of analysis, but the low attack complexity and network-accessible vector make this a meaningful risk for deployments serving untrusted authenticated users via the affected multimodal processor.

RemediationAI

Upgrade vLLM to version 0.26.0 or later, which removes the vulnerable _fetch_image function and eliminates all direct requests.get and Image.open calls on user-controlled strings within MiMoV2OmniMultiModalProcessor; the specific fix commit is 54503ecec0f3ac31e5ecfc5f28652e4cc42307b5 and the release is at https://github.com/vllm-project/vllm/releases/tag/v0.26.0. For operators unable to upgrade immediately, the most effective compensating control is restricting API access to the vLLM inference endpoint to fully trusted internal service accounts only, eliminating the PR:L threat surface at the cost of reduced external user availability. Additionally, running the vLLM process under a minimally privileged OS account with filesystem access scoped exclusively to model weight directories via read-only bind mounts or AppArmor/seccomp profiles would contain local file read impact to non-sensitive paths. Egress filtering on the vLLM host to block outbound requests to cloud metadata endpoints (169.254.169.254, fd00:ec2::254) and internal RFC-1918 address ranges would mitigate SSRF pivot risk to internal services, with no user-visible trade-off for external inference workloads. None of these workarounds eliminate the underlying bypass and should be treated as temporary pending upgrade.

Affected VersionsENISA

vllm < 0.26.0

Affected Packages

pypi vllm fix: 0.26.0

Source: OSV (Open Source Vulnerabilities)

Affects your stack

Affects 1 package in pypi

Checking this CVE against your own stacks and servers is part of the Basic plan and up.

Technical ContextAI · show details

vLLM (cpe:2.3:a:vllm-project:vllm:*:*:*:*:*:*:*:*) is a high-throughput inference and serving engine for large language models. The MiMoV2OmniMultiModalProcessor, located at vllm/transformers_utils/processors/mimo_v2_omni.py, handles multimodal inputs for the MiMo V2 Omni model family. CWE-918 (Server-Side Request Forgery) describes the root cause precisely: the processor implemented its own _fetch_image function with direct requests.get calls that resolved http://, https://, file://, data:image, and bare filesystem path strings supplied as inference inputs, entirely bypassing vLLM's MediaConnector layer. MediaConnector is the authorized media resolution path in vLLM and enforces two security boundaries: allowed_media_domains (a domain allowlist for remote URLs) and allowed_local_media_path (a filesystem path allowlist for local file access). Audio inputs were handled identically - raw strings including http:// URLs and data: URIs were fetched directly via requests.get and AudioDecoder without allowlist checks. The fix in PR #43117 (commit 54503ecec0f3ac31e5ecfc5f28652e4cc42307b5) eliminates the _fetch_image function entirely, removes all direct requests.get and Image.open calls on string inputs, and restricts the processor to accepting only pre-decoded PIL.Image objects and (waveform, sr) tuples, with all URL and path resolution delegated exclusively upstream to vLLM's properly secured media pipeline.

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  • Exploit and PoC references, threat intelligence from 22 sources

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Severity by source

Vendor (GitHub_M) PRIMARY 6.5 MEDIUM
AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N
vuln.today AI 6.5 MEDIUM

Network-accessible API requires low-privilege credentials (PR:L); allowlist bypass enables arbitrary file read and SSRF but confers no write or availability impact.

3.1 AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N
4.0 AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:N/VA:N/SC:L/SI:N/SA:N
Red Hat 6.5 MEDIUM

Primary rating from Vendor (GitHub_M).

CVSS VectorVendor: GitHub_M

Attack Vector
Network
Attack Complexity
Low
Privileges Required
Low
User Interaction
None
Scope
Unchanged
Confidentiality
High
Integrity
None
Availability
None

Lifecycle Timeline

1
Patch available
Aug 17, 2026 - 21:17 EUVD

DescriptionCVE.org

vLLM is an inference and serving engine for large language models. Prior to 0.26.0, the MiMoV2OmniMultiModalProcessor in vllm/transformers_utils/processors/mimo_v2_omni.py passes attacker-controlled image and audio strings through _fetch_image, requests.get, and Image.open instead of MediaConnector, bypassing allowed_media_domains and allowed_local_media_path protections and allowing server-side requests and reads of arbitrary files accessible to the vLLM process. This issue is fixed in version 0.26.0.

Blast Radius

ecosystem impact
† from your stack dependencies † transitive graph · vuln.today resolves 4-path depth
  • 2 pypi packages depend on vllm (2 direct, 0 indirect)

Ecosystem-wide dependent count for version 0.26.0.

Threat Intelligence Overview

EPSS Score
0.3%
Top 75% exploitable
Prevalence
Medium
popular LLM inference engine, growing enterprise adoption but not yet ubiquitous
Threat Intel
1
1 source
Data Quality
7 sources
Confidence: High
EUVD 🇯🇵JVN NVD CVE.org EPSS Vulnrichment GHSA Vendor GitHub

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.

SignalValue
Severity MEDIUM
CISA KEV No
Public POC No
EPSS 0.3%
Patch available Yes
Active threat No
Deciding rule
MEDIUM severity (CVSS 4.0-6.9)
What every action level means
Emergency Immediate action required. Criteria: CRITICAL + in CISA KEV (actively exploited) without patch, OR CRITICAL + EPSS > 30% without patch, OR CRITICAL + active threat signals without patch.
Act Now Prioritize within 24-48h. Criteria: in KEV with patch available, OR CRITICAL + public POC, OR HIGH + EPSS > 10%, OR CRITICAL + active threat, OR any CRITICAL severity.
This Week Schedule remediation this week. Criteria: HIGH severity (CVSS 7.0-8.9). Patch within normal change window.
This Month Plan within 30 days. Criteria: MEDIUM severity (CVSS 4.0-6.9), lower exploitation probability. Include in regular patch cycle.
Monitor Track and reassess. Criteria: LOW severity (CVSS 0.1-3.9), minimal exploitation risk. No immediate action needed.

SSVC AssessmentENISA

SSVC Decision· derived
Scheduled
Exploitation
Poc
System Exposure· derived
Open
Automatable
No
Human Impact· derived
Medium
Technical Impact
Partial

Priority Score

32
Low Medium High Critical
KEV: 0
EPSS: 0
CVSS: +32
PoC: 0
Weaponized: 0
Threat intel: 0
Gov advisory: 0

Attack Technique

Server-Side Request Forgery exploits applications that fetch remote resources based on user-supplied URLs.

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Vendor StatusVendor

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