Shadow AI Risks in Software Companies:
Managing Risk Without Slowing Innovation
Software companies are embedding AI into products and workflows faster than security teams can govern it. Developers spin up models, connect third-party APIs, and ship AI-powered features while the attack surface expands—OAuth token theft, CI/CD pipeline compromise, source code appearing on dark web paste sites, harvested developer credentials, and brand impersonation campaigns. Every vector lands in a different tool with a different team.
This session delivers a prioritization framework for the modern software attack surface: where to detect first, which use cases warrant automated investigation, and how to build coverage across identity abuse, unmanaged SaaS, risky AI applications, supply chain risk, and exposed credentials—without scaling headcount to match surface area.
Attendees will walk away with:
A prioritization model for software-specific attack vectors — OAuth/token abuse, CI/CD compromise, Shadow AI, credential exposure, and brand impersonation
A detection placement strategy tuned to where threats materialize earliest across identity flows, SaaS, and AI APIs
Operational patterns for automating supply chain and identity-based threat investigation
