DeepKeep Model Scanning vs Oso: Side-by-Side Comparison (2026)
Features, pricing, ratings, and pros & cons — compared head-to-head.
DeepKeep Model Scanning is a commercial ai model security tool by DeepKeep. Oso is a commercial ai model security tool by Oso. Compare features, ratings, integrations, and community reviews side by side to find the best ai model security fit for your security stack.
CST VerdictBased on our analysis of NIST CSF 2.0 coverage, core features, company size fit, deployment model, here is our conclusion:
Teams shipping AI models to production without pre-deployment security vetting should start with DeepKeep Model Scanning; it catches embedded threats, poisoned weights, and dependency vulnerabilities that standard SAST tools completely miss. The combination of static model analysis with dynamic threat pattern testing directly addresses ID.AM and ID.RA gaps most ML pipelines have today. Skip this if your models are already locked behind strict code review processes and you have security staff trained specifically on model tampering attacks; DeepKeep assumes you don't yet have that maturity built in.
Teams deploying AI coding agents at scale need visibility into what those models are actually doing, and Oso is built specifically for that job rather than retrofitting general security tools. It covers the full cycle: PR.AA controls around agent access, DE.CM continuous monitoring of agent behavior, and RS.AN incident analysis when things go wrong. Skip this if your AI footprint is experimental or single-use; Oso assumes you're running agents in production where audit trails and control enforcement matter.
