vLLM is a high-throughput and memory-efficient inference and serving engine for LLMs. Versions starting from 0.8.0 and prior to 0.8.5 are affected by a critical performance vulnerability in the input preprocessing logic of the multimodal tokenizer. The code dynamically replaces placeholder tokens (e.g., <|audio_|>, <|image_|>) with repeated tokens based on precomputed lengths. Due to inefficient list concatenation operations, the algorithm exhibits quadratic time complexity (O(n²)), allowing malicious actors to trigger resource exhaustion via specially crafted inputs. This issue has been patched in version 0.8.5.
CVE-2025-46560
This medium-severity CVE scores 6.5 under NVD CVSS v3. EPSS exploit probability: 0.5%, top 63% of all CVEs by exploit prediction. GitHub Security Advisory data not yet ingested — confidence will rise once GHSA publishes (typical lag: hours to days for open-source ecosystem CVEs; never for infrastructure-only CVEs).
- Lower severity and no public exploit yet
No vendor fix yet — apply a workaround or compensating control (WAF / firewall / segmentation) and watch for a patch.
- CVSS v3
- 6.5
- EG Score
- 6.5(medium)
- EG Risk
- 45(Track)EG Risk 45/100SSVC: Track
EG Risk is EchelonGraph's 0–100 priority score: it fuses intrinsic severity with real-world exploitation and automatability so you can rank equal-severity CVEs and fix the most dangerous first. Higher = act sooner. Distinct from the 0–10 EG Score (severity).
How it’s computedSeverity65% × 45%Exploitation40% × 40%Automatability0% × 15%Action: Routine — remediate on your standard cadence. - EPSS PROB
- 1%
- EPSS %ILE
- 42%
- KEV
- Not listed
Published
April 30, 2025
Last Modified
May 28, 2025
References (3)
- security-advisories@githubhttps://github.com/vllm-project/vllm/blob/8cac35ba435906fb7eb07e44fe1a8c26e8744f4e/vllm/model_executor/models/phi4mm.py#L1182-L1197
- security-advisories@githubhttps://github.com/vllm-project/vllm/security/advisories/GHSA-vc6m-hm49-g9qg
- 134c704f-9b21-4f2e-91b3-4a467353bcc0https://github.com/vllm-project/vllm/security/advisories/GHSA-vc6m-hm49-g9qg
Vendor Advisories for CVE-2025-46560(1)
These vendors published their own advisory mentioning this CVE — often with vendor-specific remediation steps + affected product lists not in NVD.
Affected Packages
(1 across 1 ecosystem)
PyPI(1)
| Package | Vulnerable range | Fixed in | Dependents |
|---|---|---|---|
| vllm | 0.8.0, 0.8.1, 0.8.2, 0.8.3, 0.8.4 | 0.8.5 | — |
Weakness Classification(1)
MITRE Common Weakness Enumeration — the root-cause categories this CVE belongs to.
Data Freshness Timeline
(refreshed 6× in last 7d / 31× in last 30d)
Each row is a source pipeline that fetched or updated this CVE on that date, with what changed. For example, "NVD update" means NVD published or revised its analysis for this CVE; "MITRE cvelistV5" means we ingested or refreshed it from the CNA feed. Most recent first.
Showing the most recent 100 of 153 total refreshes for this CVE.
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Frequently asked(5)
What is CVE-2025-46560?
When was CVE-2025-46560 disclosed?
Is CVE-2025-46560 actively exploited?
What is the CVSS score of CVE-2025-46560?
How do I remediate CVE-2025-46560?
Dependency Blast Radius
See which npm, PyPI, Go, and Maven packages are affected by CVE-2025-46560
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