DeepKeep Model Scanning vs HiddenLayer AISec Platform: Side-by-Side Comparison (2026)

DeepKeep Model Scanning

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.

HiddenLayer AISec Platform

Mid-market and enterprise security teams deploying large language models or autonomous agents need HiddenLayer AISec Platform to catch what traditional application security misses: prompt injection attacks, model poisoning, and agent drift before they cause real damage. The platform's CI/CD integration plus runtime detection covers both the development and operational phases where AI-specific threats live, addressing gaps in NIST's Detect and Respond functions that most security stacks ignore entirely. Skip this if your AI footprint is still experimental or confined to third-party APIs; the ROI doesn't materialize until you're managing models in production at scale.