[ SOLUTIONS // AI-ML ]
AI & ML companies
protect the weights.
Model repo access monitoring, GPU abuse detection, and governance narratives for boards asking about AI risk.
From GPU fleets to inference APIs, NNSEC combines anomaly detection, offensive testing on model endpoints, and executive narratives that answer board questions about AI risk without hand-waving.
[ THREATS ]
Industry-specific risks we prioritize.
Mapped to detections, pentest scenarios, and board narratives.
- ◆Training data poisoning
- ◆Model artifact exfiltration
- ◆Prompt injection in prod APIs
- ◆Cryptomining on GPU fleets
Case study · AI / ML Companies
Exfil attempt blocked
ML platform caught abnormal repo access before weights left the VPC.
More case studies →FAQ
Pentest scope includes prompt injection and tool-use abuse paths.