CVE-2017-6519 (GCVE-0-2017-6519)

Vulnerability from cvelistv5 – Published: 2017-05-01 01:00 – Updated: 2025-12-03 21:57
VLAI
Summary
avahi-daemon in Avahi through 0.6.32 and 0.7 inadvertently responds to IPv6 unicast queries with source addresses that are not on-link, which allows remote attackers to cause a denial of service (traffic amplification) and may cause information leakage by obtaining potentially sensitive information from the responding device via port-5353 UDP packets. NOTE: this may overlap CVE-2015-2809.
Severity
9.1 (Critical)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:H
SSVC
Exploitation: none Automatable: yes Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-12-03 21:57 UTC
CWE
  • n/a
  • CWE-346 - Origin Validation Error
Assigner
References
Date Public
2017-04-30 00:00
Show details on NVD website
To clipboard 

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Tags
Taxonomy of the tags.





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.