Netis WF2880 2.1.40207 Environment Variable cgitest.cgi FUN_004904c8 CONTENT_LENGTH null pointer dereference
| CVSS Meta Temp Score | Current Exploit Price (≈) | CTI Interest Score |
|---|---|---|
| 5.5 | $0-$5k | 0.00 |
Summary
A vulnerability identified as problematic has been detected in Netis WF2880 2.1.40207. Affected by this issue is the function FUN_004904c8 of the file cgitest.cgi of the component Environment Variable Handler. Performing a manipulation of the argument CONTENT_LENGTH results in null pointer dereference.
This vulnerability is identified as CVE-2025-45835. There is not any exploit available.
Details
A vulnerability classified as problematic has been found in Netis WF2880 2.1.40207. This affects the function FUN_004904c8 of the file cgitest.cgi of the component Environment Variable Handler. The manipulation of the argument CONTENT_LENGTH with an unknown input leads to a null pointer dereference vulnerability. CWE is classifying the issue as CWE-476. A NULL pointer dereference occurs when the application dereferences a pointer that it expects to be valid, but is NULL, typically causing a crash or exit. This is going to have an impact on availability. The summary by CVE is:
A null pointer dereference vulnerability was discovered in Netis WF2880 v2.1.40207. The vulnerability exists in the FUN_004904c8 function of the cgitest.cgi file. Attackers can trigger this vulnerability by controlling the environment variable value CONTENT_LENGTH, causing the program to crash and potentially leading to a denial-of-service (DoS) attack.
It is possible to read the advisory at github.com. This vulnerability is uniquely identified as CVE-2025-45835 since 04/22/2025. 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.
The vulnerability is also documented in the vulnerability database at EUVD (EUVD-2025-14311). Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
Product
Vendor
Name
Version
CPE 2.3
CPE 2.2
CVSSv4
VulDB Vector: 🔍VulDB Reliability: 🔍
CVSSv3
VulDB Meta Base Score: 5.7VulDB Meta Temp Score: 5.5
VulDB Base Score: 5.7
VulDB Temp Score: 5.5
VulDB Vector: 🔍
VulDB Reliability: 🔍
CVSSv2
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VulDB Base Score: 🔍
VulDB Temp Score: 🔍
VulDB Reliability: 🔍
Exploiting
Class: Null pointer dereferenceCWE: CWE-476 / CWE-404
CAPEC: 🔍
ATT&CK: 🔍
Physical: No
Local: No
Remote: Partially
Availability: 🔍
Status: Not defined
EPSS Score: 🔍
EPSS Percentile: 🔍
Price Prediction: 🔍
Current Price Estimation: 🔍
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Threat Intelligence
Interest: 🔍Active Actors: 🔍
Active APT Groups: 🔍
Countermeasures
Recommended: no mitigation knownStatus: 🔍
0-Day Time: 🔍
Timeline
04/22/2025 🔍05/12/2025 🔍
05/12/2025 🔍
07/09/2025 🔍
Sources
Advisory: github.comStatus: Not defined
CVE: CVE-2025-45835 (🔍)
GCVE (CVE): GCVE-0-2025-45835
GCVE (VulDB): GCVE-100-308331
EUVD: 🔍
Entry
Created: 05/12/2025 15:54Updated: 07/09/2025 09:47
Changes: 05/12/2025 15:54 (56), 05/26/2025 21:36 (1), 07/09/2025 09:47 (1)
Complete: 🔍
Cache ID: 216::103
Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
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