CVE-2026-3962 (GCVE-0-2026-3962)

Vulnerability from cvelistv5 – Published: 2026-03-11 22:32 – Updated: 2026-03-12 13:46
VLAI
Title
Jcharis Machine-Learning-Web-Apps Jinja2 Template app.py render_template cross site scripting
Summary
A vulnerability was identified in Jcharis Machine-Learning-Web-Apps up to a6996b634d98ccec4701ac8934016e8175b60eb5. The impacted element is 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. Such manipulation leads to cross site scripting. It is possible to launch the attack remotely. The exploit is publicly available and might be used. This product takes the approach of rolling releases to provide continious delivery. Therefore, version details for affected and updated releases are not available. The project was informed of the problem early through an issue report but has not responded yet.
Severity
5.3 (Medium)
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:N/VI:L/VA:N/SC:N/SI:N/SA:N/E:P
4.3 (Medium)
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:L/A:N/E:P/RL:X/RC:R
4.3 (Medium)
CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:L/A:N/E:P/RL:X/RC:R
SSVC
Exploitation: poc Automatable: no Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-03-12 13:46 UTC
CWE
Assigner
VulDB CNA under the mitre root
CNA scorecard B 83/100 over 3830 records in the last 180 days details
References
Impacted products
Vendor Product Version CPE status
Jcharis Machine-Learning-Web-Apps Affected: a6996b634d98ccec4701ac8934016e8175b60eb5
guessed Create a notification for this product.
Credits
ZAST.AI (VulDB User)
Show details on NVD website
To clipboard 

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      },
      "dataType": "CVE_RECORD",
      "dataVersion": "5.2"
    }
  }
}



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Tags
Taxonomy of the tags.




Drag nodes to arrange them. Double-click a related vulnerability to open it, or a source to visit its link. The Physics button on the left tunes the layout and the simulation; the legend at the bottom left hides or shows nodes by kind and by sighting type.

Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.

Sightings

Author Source Type Date Other

Nomenclature

  • Seen: The vulnerability was mentioned, discussed, or observed by the user.
  • Confirmed: The vulnerability has been validated from an analyst's perspective.
  • Published Proof of Concept: A public proof of concept is available for this vulnerability.
  • Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
  • Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
  • Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
  • Not confirmed: The user expressed doubt about the validity of the vulnerability.
  • Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
Vulnerability timeline

Sightings and recorded dates, grouped by day · UTC

JSON
How durations are calculated

Following the VTEM framework (Black Hat USA 2015), time to patch starts when the vendor or a coordinator was informed, total time to patch at discovery, and disclosure to patch at public disclosure; vendor response time runs from the report to its acknowledgement. Time to exploit and time unpatched start at the earliest discovery or report, falling back to public disclosure. Unpatched time ends at the first recorded patch, or the calculation time when no patch is recorded. Exploitation to patch shows the interval between those two events; a published proof of concept is a public exploit, not exploitation.

Each result shows its source dates. A negative interval means the end event came first; when date-only inputs leave the order open, the result says so. Date-only inputs are approximate. The earliest evidence wins: KEV report dates and sightings are labelled as such. Records describing another vulnerability are listed but never calculated from, and a PoC alone does not establish exploitation. Missing patch evidence does not prove that no patch exists. Filters below change the event list only.

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    Related by attack behaviour

    Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.