xierongwkhd weimai-wetapp up to 5fe9e8225be4f73f2c5087f134aff657bdf1c6f2 Endpoint HomeController.java getLikeMovieList cat sql injection

CVSS Meta Temp Score
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CTI Interest Score
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4.5$0-$5k0.00

Summaryinfo

A vulnerability identified as critical has been detected in xierongwkhd weimai-wetapp up to 5fe9e8225be4f73f2c5087f134aff657bdf1c6f2. This issue affects the function getLikeMovieList of the file source-code/src/main/java/com/moke/wp/wx_weimai/controller/HomeController.java of the component Endpoint. The manipulation of the argument cat leads to sql injection. This vulnerability is uniquely identified as CVE-2026-3957. The attack is possible to be carried out remotely. Moreover, an exploit is present. This product adopts a rolling release strategy to maintain continuous delivery. Therefore, version details for affected or updated releases cannot be specified. The project was informed of the problem early through an issue report but has not responded yet.

Detailsinfo

A vulnerability was found in xierongwkhd weimai-wetapp up to 5fe9e8225be4f73f2c5087f134aff657bdf1c6f2. It has been rated as critical. This issue affects the function getLikeMovieList of the file source-code/src/main/java/com/moke/wp/wx_weimai/controller/HomeController.java of the component Endpoint. The manipulation of the argument cat with an unknown input leads to a sql injection vulnerability. Using CWE to declare the problem leads to CWE-89. The product constructs all or part of an SQL command using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the intended SQL command when it is sent to a downstream component. Impacted is confidentiality, integrity, and availability.

It is possible to read the advisory at github.com. The identification of this vulnerability is CVE-2026-3957. The exploitation is known to be easy. The attack may be initiated remotely. Additional levels of successful authentication are required for exploitation. Technical details as well as a public exploit are known. The attack technique deployed by this issue is T1505 according to MITRE ATT&CK.

The exploit is available at github.com. It is declared as proof-of-concept. The project was informed of the problem early through an issue report but has not responded yet.

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.

Productinfo

Vendor

Name

Version

Website

CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔒
VulDB Reliability: 🔍

CNA CVSS-B Score: 🔒
CNA CVSS-BT Score: 🔒
CNA Vector: 🔒

CVSSv3info

VulDB Meta Base Score: 4.7
VulDB Meta Temp Score: 4.5

VulDB Base Score: 4.7
VulDB Temp Score: 4.3
VulDB Vector: 🔒
VulDB Reliability: 🔍

CNA Base Score: 4.7
CNA Vector: 🔒

CVSSv2info

AVACAuCIA
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VectorComplexityAuthenticationConfidentialityIntegrityAvailability
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VulDB Base Score: 🔒
VulDB Temp Score: 🔒
VulDB Reliability: 🔍

Exploitinginfo

Class: Sql injection
CWE: CWE-89 / CWE-74 / CWE-707
CAPEC: 🔒
ATT&CK: 🔒

Physical: No
Local: No
Remote: Yes

Availability: 🔒
Access: Public
Status: Proof-of-Concept
Download: 🔒

EPSS Score: 🔒
EPSS Percentile: 🔒

Price Prediction: 🔍
Current Price Estimation: 🔒

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Threat Intelligenceinfo

Interest: 🔍
Active Actors: 🔍
Active APT Groups: 🔍

Countermeasuresinfo

Recommended: no mitigation known
Status: 🔍

0-Day Time: 🔒

Timelineinfo

03/11/2026 Advisory disclosed
03/11/2026 +0 days VulDB entry created
03/17/2026 +6 days VulDB entry last update

Sourcesinfo

Product: github.com

Advisory: 49
Status: Not defined

CVE: CVE-2026-3957 (🔒)
GCVE (CVE): GCVE-0-2026-3957
GCVE (VulDB): GCVE-100-350387
scip Labs: https://www.scip.ch/en/?labs.20161013

Entryinfo

Created: 03/11/2026 13:38
Updated: 03/17/2026 04:49
Changes: 03/11/2026 13:38 (60), 03/17/2026 04:49 (31)
Complete: 🔍
Submitter: ZAST.AI
Cache ID: 216::103

Submitinfo

Accepted

  • Submit #767885: xierongwkhd weimai-wetapp <=1.0.0 SQL Injection (by ZAST.AI)

Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.

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