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CVE-2016-6357 (GCVE-0-2016-6357)

Vulnerability from cvelistv5 – Published: 2016-10-28 10:00 – Updated: 2024-08-06 01:29
VLAI
Summary
A vulnerability in the configured security policies, including drop email filtering, in Cisco AsyncOS for Cisco Email Security Appliance (ESA) could allow an unauthenticated, remote attacker to bypass a configured drop filter by using an email with a corrupted attachment. More Information: CSCuz01651. Known Affected Releases: 10.0.9-015 9.7.1-066 9.9.6-026.
CWE
  • unspecified
References
URL Tags
https://tools.cisco.com/security/center/content/C… x_refsource_CONFIRM
http://www.securityfocus.com/bid/93909 vdb-entryx_refsource_BID
http://www.securitytracker.com/id/1037114 vdb-entryx_refsource_SECTRACK
Impacted products
Vendor Product Version CPE status
n/a Cisco AsyncOS through 9.9.6-026 Affected: Cisco AsyncOS through 9.9.6-026
Date Public
2016-10-28 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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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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