CVE-2026-4229 (GCVE-0-2026-4229)

Vulnerability from cvelistv5 – Published: 2026-03-16 08:32 – Updated: 2026-03-16 16:35
VLAI?
Title
vanna-ai vanna bigquery_vector.py remove_training_data sql injection
Summary
A flaw has been found in vanna-ai vanna up to 2.0.2. This impacts the function remove_training_data of the file src/vanna/legacy/google/bigquery_vector.py. This manipulation of the argument ID causes sql injection. The attack can be initiated remotely. The exploit has been published and may be used. The vendor was contacted early about this disclosure but did not respond in any way.
Severity ?
6.9 (Medium)
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N/E:P
7.3 (High)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:L/E:P/RL:X/RC:R
7.3 (High)
CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:L/E:P/RL:X/RC:R
CWE
Assigner
References
URL Tags
https://vuldb.com/?id.351152 vdb-entrytechnical-description
https://vuldb.com/?ctiid.351152 signaturepermissions-required
https://vuldb.com/?submit.771214 third-party-advisory
https://gist.github.com/YLChen-007/b4f326eaecc29b… exploit
Impacted products
Vendor Product Version
vanna-ai vanna Affected: 2.0.0
Affected: 2.0.1
Affected: 2.0.2
Create a notification for this product.
Credits
Eric-y (VulDB User) VulDB
Show details on NVD website
To clipboard 

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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.



Detection rules are retrieved from Rulezet.