CVE-2026-62368 (GCVE-0-2026-62368)

Vulnerability from cvelistv5 – Published: 2026-09-24 16:40 – Updated: 2026-09-24 17:13
VLAI
Title
Snipe-IT: Stored XSS via Custom Field name in asset-list column headers
Summary
Snipe-IT is an IT asset/license management system. Prior to 8.7.0, a user with the customfields.create permission can store markup in CustomField.name, and app/Presenters/AssetPresenter.php assigns that value as an unescaped bootstrap-table header title. When another user opens an asset-list page associated with the fieldset, the stored markup executes on page load in that user's Snipe-IT session. This can expose same-origin data and perform authenticated actions with the victim's privileges, including privilege escalation when a superuser views the affected list. This issue is fixed in version 8.7.0.
SSVC
Exploitation: poc Automatable: no Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-09-24 17:13 UTC
CWE
  • CWE-79 - Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')
Impacted products
Vendor Product Version CPE status
grokability snipe-it Affected: < 8.7.0
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.
  • 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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  • 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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