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CVE-2019-1010260 (GCVE-0-2019-1010260)

Vulnerability from cvelistv5 – Published: 2019-04-02 14:03 – Updated: 2024-08-05 03:07
VLAI
Summary
Using ktlint to download and execute custom rulesets can result in arbitrary code execution as the served jars can be compromised by a MITM. This attack is exploitable via Man in the Middle of the HTTP connection to the artifact servers. This vulnerability appears to have been fixed in 0.30.0 and later; after commit 5e547b287d6c260d328a2cb658dbe6b7a7ff2261.
CWE
  • Other
Assigner
dwf
References
URL Tags
https://github.com/shyiko/ktlint/pull/332 x_refsource_MISC
Impacted products
Vendor Product Version CPE status
ktlint ktlint Affected: 0.29.0 and earlier [fixed: 0.30.0 and later - after commit 5e547b287d6c260d328a2cb658dbe6b7a7ff2261]
guessed Create a notification for this product.
Date Public
2019-01-28 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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