CVE-2026-2473PYSEC-2026-2500GHSA-WH2J-26J7-9728
Bucket Squatting in Vertex AI Experiments leads to RCE and Model Theft.
- Published
- Last modified
- Where the record stands: published, rejected by its publisher, or superseded by another id.What do these mean? →
- published
- Whether CISA lists it in its Known Exploited Vulnerabilities catalog: proof that attackers are using it.What do these mean? →
- Not listed in CISA KEV
- Fix
- Fixed in 1.133.0
- Whether working attack code is public (Exploit-DB, Metasploit, Nuclei or GitHub). Public code makes attacks easier.What do these mean? →
- None on Exploit-DB, Metasploit or GitHub
CISA's decision points: whether it is exploited, whether attacks can be automated, and how much control an attacker gets. Assessed (SSVC 2.0.3).What do these mean? →
- Exploitation: none
- Automatable: no
- Technical impact: total
Summary
Predictable bucket naming in Vertex AI Experiments in Google Cloud Vertex AI from version 1.21.0 up to (but not including) 1.133.0 on Google Cloud Platform allows an unauthenticated remote attacker to achieve cross-tenant remote code execution, model theft, and poisoning via pre-creating predictably named Cloud Storage buckets (Bucket Squatting). This vulnerability was patched and no customer action is needed.
Timeline
- CVE published
- CISA SSVC assessment
Exploitation: none · Automatable: no · Technical impact: total
- Record last updated
Affected versions
- Google Cloud Vertex AI Experiments
From 1.21.0 · fixed in 1.133.0
- google-cloud-aiplatformPyPI
From 1.21.0 · fixed in 1.133.0