CVE-2026-103087 (GCVE-0-2026-103087)

Vulnerability from cvelistv5 – Published: 2026-09-30 00:35 – Updated: 2026-09-30 00:35 X_Open Source
VLAI
Summary
Uncontrolled recursion in the Gosub browser engine (gosub-engine) through 0.1.0 and main before commit 46868b3 allows a remote attacker to cause a Denial of Service (stack exhaustion and application crash) via an SVG document containing an excessive number of deeply nested elements. Because the engine does not limit the nesting depth of processed SVG nodes, rendering such a document overflows the thread stack and terminates the application. The malicious SVG can be embedded through the SRC attribute of an IMG element, and thus exploitation only requires the victim to visit an attacker-controlled web page.
CWE
Impacted products
Vendor Product Version CPE status
gosub-io gosub-engine Affected: 0 , < 46868b3deae44544bee2a13e756772966dde950e (git)
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

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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.
  • 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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