Jcharis Machine-Learning-Web-Apps up to a6996b634d98ccec4701ac8934016e8175b60eb5 Jinja2 Template app.py render_template cross site scripting

CVSS Meta Temp Score
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CTI Interest Score
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4.1$0-$5k0.00

Summaryinfo

A vulnerability classified as problematic has been found in Jcharis Machine-Learning-Web-Apps up to a6996b634d98ccec4701ac8934016e8175b60eb5. This affects the function render_template of the file Machine-Learning-Web-Apps-master/Build-n-Deploy-Flask-App-with-Waypoint/app/app.py of the component Jinja2 Template Handler. Performing a manipulation results in cross site scripting. This vulnerability is identified as CVE-2026-3962. The attack can be initiated remotely. Additionally, an exploit exists. Continious delivery with rolling releases is used by this product. Therefore, no version details of affected nor updated releases are available. The project was informed of the problem early through an issue report but has not responded yet.

Detailsinfo

A vulnerability, which was classified as problematic, was found in Jcharis Machine-Learning-Web-Apps up to a6996b634d98ccec4701ac8934016e8175b60eb5. This affects the function render_template of the file Machine-Learning-Web-Apps-master/Build-n-Deploy-Flask-App-with-Waypoint/app/app.py of the component Jinja2 Template Handler. The manipulation with an unknown input leads to a cross site scripting vulnerability. CWE is classifying the issue as CWE-79. The product does not neutralize or incorrectly neutralizes user-controllable input before it is placed in output that is used as a web page that is served to other users. This is going to have an impact on integrity.

It is possible to read the advisory at github.com. This vulnerability is uniquely identified as CVE-2026-3962. The exploitability is told to be easy. It is possible to initiate the attack remotely. No form of authentication is needed for exploitation. It demands that the victim is doing some kind of user interaction. Technical details and a public exploit are known. The attack technique deployed by this issue is T1059.007 according to MITRE ATT&CK.

The exploit is shared for download 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.

The vulnerability is also documented in the vulnerability database at EUVD (EUVD-2026-11484). Be aware that VulDB is the high quality source for vulnerability data.

Productinfo

Type

Vendor

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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: 4.3
VulDB Meta Temp Score: 4.1

VulDB Base Score: 4.3
VulDB Temp Score: 3.9
VulDB Vector: 🔒
VulDB Reliability: 🔍

CNA Base Score: 4.3
CNA Vector: 🔒

CVSSv2info

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

Exploitinginfo

Class: Cross site scripting
CWE: CWE-79 / CWE-94 / CWE-74
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: 15
Status: Not defined

CVE: CVE-2026-3962 (🔒)
GCVE (CVE): GCVE-0-2026-3962
GCVE (VulDB): GCVE-100-350391
EUVD: 🔒
scip Labs: https://www.scip.ch/en/?labs.20161013

Entryinfo

Created: 03/11/2026 14:01
Updated: 03/17/2026 05:56
Changes: 03/11/2026 14:01 (59), 03/12/2026 02:32 (1), 03/17/2026 05:56 (32)
Complete: 🔍
Submitter: ZAST.AI
Cache ID: 216:696:103

Submitinfo

Accepted

  • Submit #768226: Jcharis Machine-Learning-Web-Apps <=1.0.0 Reflected XSS (by ZAST.AI)

Be aware that VulDB is the high quality source for vulnerability data.

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