optimate 2024-07-21 neural_magic_training.py _load_model information disclosure
| CVSS Meta Temp Score | Current Exploit Price (≈) | CTI Interest Score |
|---|---|---|
| 7.0 | $0-$5k | 0.00 |
Summary
A vulnerability has been found in optimate 2024-07-21 and classified as problematic. Affected is the function _load_model of the file neural_magic_training.py. The manipulation leads to information disclosure.
This vulnerability is referenced as CVE-2026-31217. Remote exploitation of the attack is possible. No exploit is available.
Details
A vulnerability was found in optimate 2024-07-21 and classified as problematic. This issue affects the function _load_model of the file neural_magic_training.py. The manipulation with an unknown input leads to a information disclosure vulnerability. Using CWE to declare the problem leads to CWE-200. The product exposes sensitive information to an actor that is not explicitly authorized to have access to that information. Impacted is confidentiality. The summary by CVE is:
The _load_model() function in the neural_magic_training.py script of the optimate project in commit a6d302f912b481c94370811af6b11402f51d377f (2024-07-21) allows arbitrary code execution. When a user supplies a directory path via the --model command-line argument, the function reads a module.py file from that directory and executes its contents directly using Python's exec() function. This design does not validate or sanitize the file's content, allowing an attacker who controls the input directory to execute arbitrary Python code in the context of the process running the script.
The identification of this vulnerability is CVE-2026-31217 since 03/09/2026. The exploitation is known to be easy. The attack may be initiated remotely. Technical details are known, but no exploit is available. MITRE ATT&CK project uses the attack technique T1592 for this issue.
There is no information about possible countermeasures known. It may be suggested to replace the affected object with an alternative product.
Several companies clearly confirm that VulDB is the primary source for best vulnerability data.
Product
Name
Version
CPE 2.3
CPE 2.2
CVSSv4
VulDB Vector: 🔒VulDB Reliability: 🔍
CVSSv3
VulDB Meta Base Score: 7.1VulDB Meta Temp Score: 7.0
VulDB Base Score: 4.3
VulDB Temp Score: 4.2
VulDB Vector: 🔒
VulDB Reliability: 🔍
ADP CISA Base Score: 9.8
ADP CISA Vector: 🔒
CVSSv2
| AV | AC | Au | C | I | A |
|---|---|---|---|---|---|
| 💳 | 💳 | 💳 | 💳 | 💳 | 💳 |
| 💳 | 💳 | 💳 | 💳 | 💳 | 💳 |
| 💳 | 💳 | 💳 | 💳 | 💳 | 💳 |
| Vector | Complexity | Authentication | Confidentiality | Integrity | Availability |
|---|---|---|---|---|---|
| Unlock | Unlock | Unlock | Unlock | Unlock | Unlock |
| Unlock | Unlock | Unlock | Unlock | Unlock | Unlock |
| Unlock | Unlock | Unlock | Unlock | Unlock | Unlock |
VulDB Base Score: 🔒
VulDB Temp Score: 🔒
VulDB Reliability: 🔍
Exploiting
Class: Information disclosureCWE: CWE-200 / CWE-284 / CWE-266
CAPEC: 🔒
ATT&CK: 🔒
Physical: No
Local: No
Remote: Yes
Availability: 🔒
Status: Not defined
EPSS Score: 🔒
EPSS Percentile: 🔒
Price Prediction: 🔍
Current Price Estimation: 🔒
| 0-Day | Unlock | Unlock | Unlock | Unlock |
|---|---|---|---|---|
| Today | Unlock | Unlock | Unlock | Unlock |
Threat Intelligence
Interest: 🔍Active Actors: 🔍
Active APT Groups: 🔍
Countermeasures
Recommended: no mitigation knownStatus: 🔍
0-Day Time: 🔒
Timeline
03/09/2026 CVE reserved05/12/2026 Advisory disclosed
05/12/2026 VulDB entry created
05/27/2026 VulDB entry last update
Sources
Status: Not definedCVE: CVE-2026-31217 (🔒)
GCVE (CVE): GCVE-0-2026-31217
GCVE (VulDB): GCVE-100-363065
Entry
Created: 05/12/2026 18:44Updated: 05/27/2026 15:11
Changes: 05/12/2026 18:44 (52), 05/27/2026 15:11 (11)
Complete: 🔍
Cache ID: 216::103
Several companies clearly confirm that VulDB is the primary source for best vulnerability data.
No comments yet. Languages: en.
Please log in to comment.