vllm-project vLLM up to 0.29.0 SamplingParams.update_from_tokenizer out-of-bounds
| CVSS Meta Temp Score | Current Exploit Price (≈) | CTI Interest Score |
|---|---|---|
| 3.7 | $0-$5k | 1.02 |
Summary
A vulnerability classified as problematic has been found in vllm-project vLLM up to 0.29.0. This affects the function SamplingParams.update_from_tokenizer. The manipulation leads to out-of-bounds.
This vulnerability is uniquely identified as CVE-2026-93989. The attack is possible to be carried out remotely. No exploit exists.
Details
A vulnerability was found in vllm-project vLLM up to 0.29.0. It has been rated as problematic. This issue affects the function SamplingParams.update_from_tokenizer. The manipulation with an unknown input leads to a out-of-bounds vulnerability. Using CWE to declare the problem leads to CWE-125. The product reads data past the end, or before the beginning, of the intended buffer. Impacted is integrity. The summary by CVE is:
vLLM through 0.29.0 fails to properly validate bad_words token indices against the model's generation output width in SamplingParams.update_from_tokenizer(). Attackers can supply out-of-bounds token indices that corrupt logits memory of concurrent requests, causing different in-flight HTTP requests to return incorrect tokens.
It is possible to read the advisory at github.com. The identification of this vulnerability is CVE-2026-93989 since 09/19/2026. The exploitation is known to be easy. The attack may be initiated remotely. Technical details of the vulnerability are known, but there is no available exploit.
There is no information about possible countermeasures known. It may be suggested to replace the affected object with an alternative product.
Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
Product
Type
Vendor
Name
Version
- 0.1
- 0.2
- 0.3
- 0.4
- 0.5
- 0.6
- 0.7
- 0.8
- 0.9
- 0.10
- 0.11
- 0.12
- 0.13
- 0.14
- 0.15
- 0.16
- 0.17
- 0.18
- 0.19
- 0.20
- 0.21
- 0.22
- 0.23
- 0.24
- 0.25
- 0.26
- 0.27
- 0.28
- 0.29.0
Website
CPE 2.3
CPE 2.2
CVSSv4
VulDB Vector: 🔒VulDB Reliability: 🔍
CNA CVSS-B Score: 🔒
CNA CVSS-BT Score: 🔒
CNA Vector: 🔒
CVSSv3
VulDB Meta Base Score: 3.7VulDB Meta Temp Score: 3.7
VulDB Base Score: 4.3
VulDB Temp Score: 4.2
VulDB Vector: 🔒
VulDB Reliability: 🔍
CNA Base Score: 3.1
CNA Vector (VulnCheck): 🔒
CVSSv2
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| 💳 | 💳 | 💳 | 💳 | 💳 | 💳 |
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| Vector | Complexity | Authentication | Confidentiality | Integrity | Availability |
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VulDB Base Score: 🔒
VulDB Temp Score: 🔒
VulDB Reliability: 🔍
Exploiting
Class: Out-of-boundsCWE: CWE-125 / CWE-119
CAPEC: 🔒
ATT&CK: 🔒
Physical: No
Local: No
Remote: Yes
Availability: 🔒
Status: Not defined
Price Prediction: 🔍
Current Price Estimation: 🔒
| 0-Day | Unlock | Unlock | Unlock | Unlock |
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| Today | Unlock | Unlock | Unlock | Unlock |
Threat Intelligence
Interest: 🔍Active Actors: 🔍
Active APT Groups: 🔍
Countermeasures
Recommended: no mitigation knownStatus: 🔍
0-Day Time: 🔒
Timeline
09/19/2026 CVE reserved09/19/2026 VulDB entry created
09/20/2026 Advisory disclosed
09/20/2026 VulDB entry last update
Sources
Product: github.comAdvisory: github.com
Status: Not defined
CVE: CVE-2026-93989 (🔒)
GCVE (CVE): GCVE-0-2026-93989
GCVE (VulDB): GCVE-100-407987
Entry
Created: 09/20/2026 01:18Changes: 09/20/2026 01:18 (75)
Complete: 🔍
Cache ID: 216::103
Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
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