Multi-Cloud AI Breach 2024
A major security incident where misconfigured access controls across AWS, Azure, and Google Cloud led to unauthorized access to sensitive AI training data and model parameters.
Affected Platforms
3
Cloud providers compromised (AWS, Azure, GCP)
Data Exposed
2.3TB
Training data and model weights exfiltrated
Breach Duration
45 days
Time attackers had unauthorized access
Root Causes
Configuration Errors
- • Publicly accessible S3 buckets containing training data
- • Overly permissive IAM roles with cross-account access
- • Azure storage containers with anonymous read access
- • GCP service accounts with excessive permissions
Monitoring Gaps
- • Insufficient logging of cross-cloud data access
- • No alerting on unusual data transfer volumes
- • Lack of unified security monitoring across clouds
- • Delayed incident response due to siloed teams
Security Improvements
Immediate Actions
- • Audit and remediate all storage permissions
- • Implement least privilege access policies
- • Enable encryption for all data at rest
- • Deploy cloud security posture management (CSPM)
Long-term Strategy
- • Unified identity and access management
- • Centralized logging and SIEM integration
- • Regular security audits and penetration testing
- • Security training for cloud engineering teams