CVE-2026-107212 (GCVE-0-2026-107212)

Vulnerability from cvelistv5 – Published: 2026-10-07 17:29 – Updated: 2026-10-07 17:57
VLAI
Title
Excelize: Unbounded row number in Rows.Columns makes GetRows and the Rows iterator loop for days
Summary
Excelize is a Go language library for reading and writing Microsoft Excel spreadsheets. From 2.1.0 to 2.11.0, Rows.Columns accepts a look-ahead row number above TotalRows without applying the limit enforced by Rows.Next. File.GetRows relies on Rows.Next and Rows.Columns, but Rows.Columns consumes the row r attribute without the limit check in Rows.Next. When a crafted worksheet places an oversized row number after an ordinary valid row and the application calls GetRows or iterates Rows, the iterator advances through every missing row number instead of rejecting the workbook, allowing an attacker to consume a CPU core for an attacker-controlled duration. No fixed version is available as of this review.
Severity
7.5 (High)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
SSVC
Exploitation: poc Automatable: yes Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-10-07 17:56 UTC
CWE
  • CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
References
Impacted products
Vendor Product Version CPE status
qax-os excelize Affected: >= 2.1.0, <= 2.11.0
guessed Create a notification for this product.
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

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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.
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  • Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.



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.