One Signal, Seen From Every Angle
Microsoft’s security products are built on a shared data foundation, so a suspicious login, a malware alert, and an unusual data movement can be evaluated together instead of in isolation — turning individually minor signals into a clear picture of an actual threat.
About Microsoft
Over the past several years, Microsoft has built out one of the largest security portfolios in the industry, organized around four connected pillars: identity, endpoint and cloud threat detection, security operations, and data protection. Rather than separate, disconnected tools, the products share a common signal graph — meaning identity, device, and data events feed into the same correlation engine rather than requiring a security team to manually piece them together across consoles.
Identity, Threat Detection & Response
Identity is the most common entry point for a breach, which is why access control sits at the foundation of the stack — feeding directly into the threat detection layer built on top of it.
Identity & Access Control
Manages authentication across applications and devices, with cloud-native controls built for risk-based access decisions in real time.
Cross-Domain Threat Detection & Response
Correlates alerts from endpoints, identities, email, and cloud apps into a single incident instead of separate ones.
Security Operations & Investigation
Pulls in signal from multicloud and third-party sources so an incident can be traced across infrastructure it doesn't own.
AI-Assisted Analysis
LLayers a natural-language assistant on the security stack, with responses grounded in actual telemetry rather than generic guidance.
Data Protection & Governance
Data protection is treated as a parallel track to threat detection rather than an afterthought — because most serious security incidents involve both an attacker and sensitive information at risk.
Data Classification & Loss Prevention
Identifies and labels sensitive data, then enforces policy to prevent it leaving through channels it shouldn't, including AI prompts.
Insider Risk & Compliance Management
Covers governance, retention, and insider risk management, the compliance side of data protection that's easy to overlook.
Securing Autonomous AI Agents
A dedicated layer addressing AI agents as a distinct category, with a central control point for identity and permissions.
