📖 Overview

Scam messages often share repeatable pressure signals.

This tool scores urgency link quality identity mismatch and payment requests into one risk output.

Use it to slow down and verify before clicking replying or paying.

🧪 Example Scenarios

Use these default and higher-pressure example inputs to explore how sensitive this calculator is before using your real numbers.

InputBase CaseHigher Pressure Case
Urgency Red Flags22.3
Link Red Flags11.15
Identity Mismatch Red Flags11.15
Payment Request Flag (0 or 1)11.15

⚙️ How It Works

Grades likely scam intent from common social-engineering signals and payment coercion patterns.

The Formula

Risk Score = weighted(red-flag signals)
Urgency FlagsPressure language designed to force instant action
Link FlagsSuspicious or mismatched URLs/domains
Identity FlagsSender identity inconsistencies
Payment FlagDirect request for payment/gift card/crypto transfer
💡Multiple strong red flags usually indicate scam behavior even when wording seems plausible.

Quick Reference

Risk scoreSignal strengthRecommended response
0-29LowProceed with normal caution
30-54MediumVerify sender via trusted channel
55-74HighDo not click links or transfer funds
75-100Very highTreat as scam and report/block

When To Use This

  • Use this tool when you need a fast decision during active planning or execution.
  • Use this before committing money, time, or tradeoffs that are hard to reverse.
  • Use this to compare options using the same assumptions across scenarios.

Edge Cases To Watch

  • Results can be misleading if key inputs are missing, stale, or unrealistic.
  • Very small or very large values may amplify rounding effects and interpretation risk.
  • If assumptions change mid-decision, recalculate before acting.

Practical Tips

💡 Never click payment links from urgent unsolicited messages.
💡 Verify identity via a trusted channel before acting.
💡 Assume urgency + payment + secrecy requests are hostile until proven otherwise.

Frequently Asked Questions

❓ Does one red flag prove scam?

Not always, but multiple strong flags rapidly increase risk.

❓ Can this detect all scams?

No model is perfect; use it as structured caution support.