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CVE-2026-92366 (GCVE-0-2026-92366)

Vulnerability from cvelistv5 – Published: 2026-09-16 14:15 – Updated: 2026-09-16 19:24 X_Freeware
VLAI
Title
code-projects Matrimonial System Regular Search search.php sql injection
Summary
A vulnerability was determined in code-projects Matrimonial System 1.0. This affects an unknown part of the file /search.php of the component Regular Search. This manipulation of the argument sex/mothertongue/maritialstatus/country/state/religion/agemin/agemax causes sql injection. The attack can be initiated remotely. The exploit has been publicly disclosed and may be utilized.
Severity
6.9 (Medium)
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N/E:P
7.3 (High)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:L/E:P/RL:X/RC:R
7.3 (High)
CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:L/E:P/RL:X/RC:R
SSVC
Exploitation: poc Automatable: yes Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-09-16 19:24 UTC
CWE
Assigner
References
Impacted products
Vendor Product Version CPE status
code-projects Matrimonial System Affected: 1.0
    cpe:2.3:a:code-projects:matrimonial_system:*:*:*:*:*:*:*:*
Create a notification for this product.
Credits
KaranParelkar (VulDB User)
Show details on NVD website
To clipboard 

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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.

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  • 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.


Detection rules are retrieved from Rulezet.


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.