HSES

The Human Security Exploitability System

Security isn’t just about Firewalls. It’s about Physiology. Sub-headline: The world’s first research-driven engine that calculates real-time “Human Exploitability Scores” by analyzing physiological signals, behavioral patterns, and environmental context. 

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HSES

Problem:

The Invisible Risk Cybersecurity tools defend networks, endpoints, and clouds, but they ignore the most critical attack surface: The Human.

  • 74% of breaches involve the human element (Verizon DBIR).
  • Stress, fatigue, and distraction make even the best-trained analysts vulnerable to social engineering.
  • Security teams currently have zero visibility into the real-time cognitive state of their workforce.

Solution:

HSES: Real-Time Human Risk Intelligence The Human Security Exploitability System (HSES) bridges the gap between biology and security. By ingesting real-time physiological data and contextual metadata, HSES quantifies how “exploitable” a user is at any given second.

“A fatigued admin at 3 AM is 10x more likely to click a phishing link than a focused analyst at 10 AM. HSES proves it.“

How it Works?

Working of HSES

Key Features

Physiological Signal Normalization

Raw data is messy. HSES normalizes diverse inputs (pulse, keystroke dynamics) into a unified risk metric, making biological data actionable for security logic.

Visualize the invisible. Our “Signal Equalizer” dashboard breaks down risk contributors in real-time, showing exactly which factor (e.g., “High Stress”) is spiking the risk score.

Not all users are equal. HSES dynamically adjusts risk tolerance based on user privileges (Admin vs. User) and data access levels.

Built on FastAPI, the HSES engine provides low-latency risk scores that can be integrated directly into SIEMs, SOARs, or Zero Trust policy engines.

Use Cases

  • Dynamic Access Control: Prompt for MFA if a user’s Fatigue score is > 80.
  • Targeted Training: trigger micro-trainings only when a user is in a “Teachable Moment” (High Focus, Low Stress).
  • SOC Analyst Monitoring: Prevent burnout by monitoring the cognitive load of security teams in real-time.

Get Involved

Pull Request at https://github.com/srinjoy-zeron/hses-engine