HiddenLayer

Built out supply-chain scanning, runtime defense, posture management and red-teaming as a unified platform within roughly three years of founding.

Model-file scanning and runtime detection integrate into existing ML pipelines, giving practical coverage of a concrete AI supply-chain risk (malicious pickle/model files).

$50M Series A led by Microsoft's M12 fund is a credible strategic-investor signal, and headcount (~169) suggests real commercial traction, though no later round has been disclosed. Recognized in Cyber Defense Media Group's 2026 Global InfoSec Awards (1 award), independently juried industry validation of market traction.

Model-file and ML-artifact scanning addresses an attack surface (malicious serialized model files, model extraction) that conventional AppSec/SCA tools do not cover. However, HiddenLayer's Series A post-money valuation was approximately $223M as of February 2024 (per pitchbook.com), which is the scale of an established incumbent rather than an emerging category disruptor, so this dimension is scored more conservatively.

HiddenLayer's research team has publicly disclosed real model-security vulnerabilities and technique write-ups, giving more independent grounding than most peers, though platform-wide detection rates remain unverified.

ML supply-chain and model-file risk is structural to how organizations consume open-source and third-party models, a trend that is accelerating, not fading.