CVE-2026-2473: Google Cloud Vertex AI Experiments · Generation of Predictable Numbers or Identifiers
Affects Google Cloud Vertex AI ExperimentsSource CVE Database V5
Not known to be exploited · CVSS 7.7 High : upgrade to 1.133.0 soon.
Data as of 29 Oct 2026, 19:04 UTC
- EPSS
- 0.5% chance of exploitation in 30 days – higher than 43% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
- Patch
- Available – fixed in 1.133.0
CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:P/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/U:ClearExploitation evidence
Disclosed: evidence found.
CVE published 20 Feb 2026
Detectable: no evidence on record.
No public nuclei template indexed
Weaponized: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by Mirage: no evidence on record.
No attack traffic recorded by OffSeq Mirage sensors
A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 29 Oct 2026.
What to do
Upgrade Google Cloud Vertex AI Experiments to 1.133.0.
Affected software
| Product | Affected | Fixed in |
|---|---|---|
| Google CloudVertex AI Experiments | Affected
| Fixed in
|
AI-suggested
To mitigate CVE-2026-2473, organizations should immediately verify their Google Cloud Vertex AI Experiments versions and upgrade to version 1.133.0 or later where the vulnerability is patched. Implement strict monitoring and alerting for unusual Cloud Storage bucket creation activities, especially buckets with names matching predictable patterns used by Vertex AI Experiments. Employ Google Cloud IAM policies to restrict bucket creation permissions to trusted users and service accounts only. Use Google Cloud’s security tools to audit access logs and detect anomalous behavior related to AI experiment resources. Consider isolating AI workloads in dedicated projects or environments to limit cross-tenant exposure. Regularly review and update security configurations for AI and cloud storage services. Engage with Google Cloud support for guidance on best practices and incident response in case of suspected exploitation. Finally, educate development and security teams about the risks of predictable resource naming and enforce secure naming conventions.
Description
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.