How CySent works

A lightweight browser extension powered by purpose-built AI models, designed for real-time protection without disrupting your workflow.

Detection pipeline

From message to action in milliseconds.

01

Ingest

CySent monitors messages and links in real time as they appear in Email, Slack, Teams, and other collaborative platforms through our browser extension.

02

Detect

Purpose-built AI models analyze content for phishing indicators, suspicious patterns, and behavioral anomalies.

03

Policy

Based on your configured policies, CySent warns users, blocks risky content, or allows with logging.

04

Output

Every detection is logged in SIEM-ready formats for your security workflows and compliance reporting.

Purpose-built detection models

Each channel has unique attack patterns. Our models are trained specifically for each threat vector.

Swordphish

Email Detection

Our email-focused model analyzes message structure, sender patterns, and content characteristics to identify phishing attempts.

Detection signals:

  • Sender domain and header analysis
  • Language pattern recognition
  • Urgency and social engineering indicators
  • Historical sender behavior comparison

Swordphish

Email Detection

Jellyphish

URL Analysis

Specialized for link analysis, this model evaluates URLs for malicious indicators before users click.

Detection signals:

  • Domain reputation and age analysis
  • URL structure anomaly detection
  • Redirect chain inspection
  • Visual similarity to known brands

Jellyphish

URL Analysis

catphish

Chat Protection

Built for messaging platforms, this model understands the unique patterns of chat-based social engineering.

Detection signals:

  • Conversation context analysis
  • Impersonation attempt detection
  • Urgency pattern recognition
  • Cross-platform correlation

catphish

Chat Protection

Behavioral anomaly detection

Beyond content analysis, CySent spots unusual behavior patterns that indicate sophisticated attacks. When someone deviates from their normal communication patterns—or when a message doesn't match expected behavior—we flag it.

This catches attacks that signature-based tools miss, including account compromises and targeted social engineering.

See it in action

Join our waitlist to get early access and a personalized demo.