InternLM LMDeploy dynamically-determined object attributes
| CVSS Meta Temp Score | Current Exploit Price (≈) | CTI Interest Score |
|---|---|---|
| 6.6 | $0-$5k | 0.00 |
Summary
A vulnerability classified as problematic has been found in InternLM LMDeploy. This affects an unknown part. The manipulation leads to dynamically-determined object attributes. This vulnerability is uniquely identified as CVE-2026-46517. The attack is possible to be carried out remotely. No exploit exists.
Details
A vulnerability was found in InternLM LMDeploy (version now known). It has been rated as problematic. This issue affects some unknown processing. The manipulation with an unknown input leads to a dynamically-determined object attributes vulnerability. Using CWE to declare the problem leads to CWE-915. The product receives input from an upstream component that specifies multiple attributes, properties, or fields that are to be initialized or updated in an object, but it does not properly control which attributes can be modified. Impacted is confidentiality, integrity, and availability. The summary by CVE is:
LMDeploy is a toolkit for compressing, deploying, and serving large language models. In versions 0.12.3 and prior, hardcoded "trust_remote_code=True" enables HF supply-chain RCE without user opt-in. At time of publication, there are no publicly available patches.
It is possible to read the advisory at github.com. The identification of this vulnerability is CVE-2026-46517. The exploitation is known to be difficult. The attack may be initiated remotely. No form of authentication is needed for a successful exploitation. The technical details are unknown and an exploit is not publicly available. The pricing for an exploit might be around USD $0-$5k at the moment (estimation calculated on 06/15/2026).
There is no information about possible countermeasures known. It may be suggested to replace the affected object with an alternative product.
The vulnerability is also documented in the vulnerability database at EUVD (EUVD-2026-35874). Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
Product
Vendor
Name
CPE 2.3
CPE 2.2
CVSSv4
VulDB Vector: 🔒VulDB Reliability: 🔍
CVSSv3
VulDB Meta Base Score: 6.7VulDB Meta Temp Score: 6.6
VulDB Base Score: 5.6
VulDB Temp Score: 5.4
VulDB Vector: 🔒
VulDB Reliability: 🔍
CNA Base Score: 7.8
CNA Vector: 🔒
CVSSv2
| AV | AC | Au | C | I | A |
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| 💳 | 💳 | 💳 | 💳 | 💳 | 💳 |
| 💳 | 💳 | 💳 | 💳 | 💳 | 💳 |
| Vector | Complexity | Authentication | Confidentiality | Integrity | Availability |
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VulDB Base Score: 🔒
VulDB Temp Score: 🔒
VulDB Reliability: 🔍
Exploiting
Class: Dynamically-determined object attributesCWE: CWE-915 / CWE-913
CAPEC: 🔒
ATT&CK: 🔒
Physical: Partially
Local: Yes
Remote: Yes
Availability: 🔒
Status: Not defined
EPSS Score: 🔒
EPSS Percentile: 🔒
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
05/22/2026 Advisory disclosed05/22/2026 VulDB entry created
06/15/2026 VulDB entry last update
Sources
Advisory: github.comStatus: Not defined
CVE: CVE-2026-46517 (🔒)
GCVE (CVE): GCVE-0-2026-46517
GCVE (VulDB): GCVE-100-365147
EUVD: 🔒
Entry
Created: 05/22/2026 06:31Updated: 06/15/2026 02:16
Changes: 05/22/2026 06:31 (47), 06/10/2026 05:44 (1), 06/15/2026 02:16 (12)
Complete: 🔍
Cache ID: 216::103
Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
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