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CVE-2022-1211 (GCVE-0-2022-1211)

Vulnerability from cvelistv5 – Published: 2022-04-03 12:10 – Updated: 2025-04-15 14:42
VLAI
Title
tildearrow Furnace FUR to VGM Converter stack-based overflow
Summary
A vulnerability classified as critical has been found in tildearrow Furnace dev73. This affects the FUR to VGM converter in console mode which causes stack-based overflows and crashes. It is possible to initiate the attack remotely but it requires user-interaction. A POC has been disclosed to the public and may be used.
SSVC
Exploitation: poc Automatable: no Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-04-14 17:14 UTC
CWE
  • CWE-121 - Stack-based Buffer Overflow
References
Impacted products
Vendor Product Version CPE status
tildearrow Furnace Affected: dev73
guessed Create a notification for this product.
Show details on NVD website

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}



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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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