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CVE-2017-14591 (GCVE-0-2017-14591)

Vulnerability from cvelistv5 – Published: 2017-11-29 21:00 – Updated: 2024-09-16 20:46
VLAI
Summary
Atlassian Fisheye and Crucible versions less than 4.4.3 and version 4.5.0 are vulnerable to argument injection through filenames in Mercurial repositories, allowing attackers to execute arbitrary code on a system running the impacted software.
Severity
9.0 (Critical)
CVSS:3.0/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H
CWE
  • Arbitrary Code Execution
Assigner
References
URL Tags
https://confluence.atlassian.com/x/plcGO x_refsource_CONFIRM
http://www.securityfocus.com/bid/102194 vdb-entryx_refsource_BID
Impacted products
Vendor Product Version CPE status
Atlassian Fisheye and Crucible Affected: Versions less than 4.4.3 OR version 4.5.0
guessed Create a notification for this product.
Date Public
2017-11-29 00:00
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.

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.


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.