CVE-2020-26265 (GCVE-0-2020-26265)

Vulnerability from cvelistv5 – Published: 2020-12-11 16:45 – Updated: 2024-08-04 15:56
VLAI
Title
Consensus flaw during block processing
Summary
Go Ethereum, or "Geth", is the official Golang implementation of the Ethereum protocol. In Geth from version 1.9.4 and before version 1.9.20 a consensus-vulnerability could cause a chain split, where vulnerable versions refuse to accept the canonical chain. The fix was included in the Paragade release version 1.9.20. No individual workaround patches have been made -- all users are recommended to upgrade to a newer version.
CWE
Assigner
GitHub_M CNA under the mitre root
CNA scorecard C 72/100 over 7886 records in the last 180 days details
References
Impacted products
Vendor Product Version CPE status
ethereum go-ethereum Affected: >= 1.9.4, < 1.9.20
guessed Create a notification for this product.
Show details on NVD website

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Sightings

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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.
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Following the VTEM framework (Black Hat USA 2015), time to patch starts when the vendor or a coordinator was informed, total time to patch at discovery, and disclosure to patch at public disclosure; vendor response time runs from the report to its acknowledgement. Time to exploit and time unpatched start at the earliest discovery or report, falling back to public disclosure. Unpatched time ends at the first recorded patch, or the calculation time when no patch is recorded. Exploitation to patch shows the interval between those two events; a published proof of concept is a public exploit, not exploitation.

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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.