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CVE-2022-1601 (GCVE-0-2022-1601)

Vulnerability from cvelistv5 – Published: 2023-08-30 14:22 – Updated: 2024-10-01 18:43
VLAI
Title
User Access Manager < 2.2.18 - IP Spoofing
Summary
The User Access Manager WordPress plugin before 2.2.18 prioritizes getting a visitor's IP from certain HTTP headers over PHP's REMOTE_ADDR, which makes it possible for attackers to access restricted content in certain situations.
Severity
No CVSS data available.
SSVC
Exploitation: poc Automatable: yes Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2024-10-01 18:42 UTC
References
URL Tags
https://wpscan.com/vulnerability/f6d3408c-2ceb-4a… exploitvdb-entrytechnical-description
Impacted products
Vendor Product Version CPE status
Unknown User Access Manager Affected: 0 , < 2.2.18 (custom)
guessed Create a notification for this product.
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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