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CVE-2014-10016 (GCVE-0-2014-10016)

Vulnerability from cvelistv5 – Published: 2015-01-13 11:00 – Updated: 2024-08-06 14:02
VLAI
Summary
Multiple cross-site scripting (XSS) vulnerabilities in the Welcart e-Commerce plugin 1.3.12 for WordPress allow remote attackers to inject arbitrary web script or HTML via (1) unspecified vectors related to purchase_limit or the (2) name, (3) intl, (4) nocod, or (5) time parameter in an add_delivery_method action to wp-admin/admin-ajax.php.
Severity
No CVSS data available.
CWE
  • n/a
References
URL Tags
http://secunia.com/advisories/57222 third-party-advisoryx_refsource_SECUNIA
http://www.securityfocus.com/bid/65954 vdb-entryx_refsource_BID
http://packetstormsecurity.com/files/125513 x_refsource_MISC
https://exchange.xforce.ibmcloud.com/vulnerabilit… vdb-entryx_refsource_XF
Date Public
2014-03-03 00:00
Show details on NVD website

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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.

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.

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Detection rules are retrieved from Rulezet.

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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.


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