Behavioral Signals

Isolated events can't tell the full story. TOTAL correlates low-level endpoint and network activity with higher-order behavioral patterns to form contextual narratives of identity. This approach filters noise, validates anomalies, and uncovers threats which rule-based tools miss.

Behavioral Personas

TOTAL uses LLMs and Reinforcement Learning to build behavioral personas for every employee. Each persona reflects an employee’s role, responsibilities, rhythm of work, and patterns of interaction across systems. These personas evolve over time with continued interaction, enabling the system to distinguish harmless variability from genuine threat indicators.

Contextual Storytelling

TOTAL transforms fragmented alerts into a unified storyline that explains not only what happened, but why it happened. By linking motive, opportunity, and probable cause, security teams gain visibility into the full context of user actions.

Learning Up and Down the Stack

Modern adversaries rarely rely on one tactic. During their attacks, they conduct reconnaissance, coordinate collusive campaigns, and probe for weaknesses across the enterprise. Surfacing these hidden patterns requires a sustained understanding of each user’s behavior and how it evolves. Without visibility into long-term behavioral patterns, it’s impossible to know whether a low-level anomaly is meaningful or just noise. TOTAL solves this by transforming isolated endpoint and network events into a continuous behavioral story.

By correlating endpoint, network, and behavioral signals, TOTAL turns raw activity into identity context. Its native low-level signals corroborate or invalidate higher-order behavioral patterns, filtering noise and strengthening detections. This layered approach exposes account drift, collusion, and insider threats that rule-based tools miss.

Signal Stack

Behavior Analysis

High-level behavioral patterns and organizational context

  • Email: Communication patterns
  • Messages: Instant messaging
  • HR Info: Organizational data
  • Case Mgmt.: Offline investigations
  • Org. Knowledge: Contextual intelligence
  • Behavioral Biometrics: Unique user interaction patterns and environmental signals
    • Keyboard Patterns: Typing rhythm, pressure, timing
    • Mouse Patterns: Movement, clicks, scrolling
    • Environmental: Context and usage patterns

Network & Physical

Low-level network, endpoint, and physical access events

  • SSO: Single sign-on events
  • Device Sign-in: Authentication events
  • Enrollment: Device registration
  • Physical Access: Badge/door events
  • Browser Activity: Web interactions
  • Endpoint Apps: Application usage