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SafeSnap Extension - Feature Demonstration

This document demonstrates SafeSnap's capabilities through real-world scenarios captured by our E2E test suite. Each scenario shows how SafeSnap automatically detects and protects different types of Personally Identifiable Information (PII) in screenshots.

All screenshots in this document are generated automatically by running:

bunx playwright test test/e2e/scenarios.spec.js

Table of Contents

  1. Scenario 1: Real Estate Listing (Zillow)
  2. Scenario 2: Tax Calculator (Calculator.net)
  3. Scenario 3: News Article (SFGate)
  4. Scenario 4: Wikipedia Article (Blackout Mode)

Note: These screenshots are generated by the E2E test suite. See TESTING.md for how to regenerate them.


Scenario 1: Real Estate Listing (Zillow)

Use Case: Sharing property listings without exposing exact addresses, prices, or agent information.

Source: Zillow - 479 Kentucky Ave, Berkeley, CA

Detection Summary

PII Type Count Examples
Money 137 $1,399,000$194,808, $8,512$1,185
Addresses 17 1141 Oxford St5701 Second Ave, 2728 Dohr St613 Hill Ct
Locations 61 KentuckyUnionville, BerkeleyClearview, CaliforniaHarborview
Dates 74 Year references, listing dates
Proper Nouns 375 Agent names, company names
Total 664

Screenshots

Original (Before SafeSnap)

Zillow Original

Privacy Risks:

  • Property address fully visible
  • Exact listing price exposed ($1,399,000)
  • Tax assessment amounts shown ($8,512/year)
  • Nearby property addresses visible
  • Agent names and contact information exposed
  • Zestimate history reveals property value trends

Highlighted (PII Detected)

Zillow Highlighted

Detection Applied:

  • Yellow highlights show all detected PII
  • Hover tooltips show detection type and confidence
  • 664 total PII entities identified

Protected (PII Replaced)

Zillow Protected

Protection Applied:

  • All prices replaced with realistic values (magnitude variance applied)
  • Street addresses replaced with fake addresses preserving format
  • Location names replaced with fictional locations
  • Agent/company names replaced with fake names
  • Date references anonymized

Sample Replacements

Original Type Replacement
$1,399,000 money $194,808
$1,672,700 money $232,921
$8,512 money $1,185
1141 Oxford St address 5050 Hill Blvd
2728 Dohr St address 613 Hill Ct
1524 Blake St address 7584 Pine St
Kentucky location Unionville
Berkeley location Clearview
California location Harborview

Scenario 2: Tax Calculator (Calculator.net)

Use Case: Sharing tax calculation screenshots without exposing actual income, withholding, or deduction amounts.

Source: Calculator.net Tax Calculator (with sample data: $125,000 + $122,000 income, married filing jointly)

Detection Summary

PII Type Count Examples
Money 64 $125,000$70,066, $26,000$14,574
Dates 28 20252025-02-22, 20242024-02-22
Proper Nouns 61 Various labels (some false positives)
Total 153

Screenshots

Original (Before SafeSnap)

Tax Calculator Original

Privacy Risks:

  • Exact income figures visible ($125,000, $122,000)
  • Withholding amounts exposed ($26,000, $40,000)
  • Deduction details shown (mortgage: $23,444, donations: $2,222)
  • Tax liability calculations visible
  • State tax amounts revealed

Highlighted (PII Detected)

Tax Calculator Highlighted

Detection Applied:

  • All currency values highlighted
  • Tax year references detected
  • 153 total PII entities identified

Protected (PII Replaced)

Tax Calculator Protected

Protection Applied:

  • All dollar amounts replaced with random values
  • Magnitude variance preserves realistic proportions
  • Tax years anonymized
  • Calculations remain internally consistent (replaced values)

Sample Replacements

Original Type Replacement
$125,000 money $70,066
$122,000 money $68,385
$26,000 money $14,574
$40,000 money $22,421
$100,000 money $56,053
$10,000 money $5,605
2025 date 2025-02-22
2024 date 2024-02-22

Scenario 3: News Article (SFGate)

Use Case: Sharing news articles without exposing location names, dates, or quoted individuals.

Source: SFGate - United Airlines Article

Detection Summary

PII Type Count Examples
Locations 61 CaliforniaHarborview, Bay AreaCrystal Lake
Proper Nouns 130 Company names, quoted sources
Dates 17 Publication dates, event dates
Total 208

Screenshots

Original (Before SafeSnap)

SFGate Original

Privacy Risks:

  • Geographic locations mentioned (San Francisco, Bay Area, California)
  • Company names visible (United Airlines, Peet's Coffee)
  • Dates reveal timeline of events
  • Names of quoted individuals exposed

Highlighted (PII Detected)

SFGate Highlighted

Detection Applied:

  • Location names highlighted throughout article
  • Company and proper nouns identified
  • Date references detected
  • 208 total PII entities identified

Protected (PII Replaced)

SFGate Protected

Protection Applied:

  • All location names replaced with fictional places
  • Company names anonymized
  • Dates replaced while preserving format
  • Article remains readable with context preserved

Protected with Highlights

SFGate Protected Highlighted

Verification Mode:

  • Shows protected content WITH highlight overlays
  • Useful for verifying what was replaced
  • Highlights indicate replaced text positions

Sample Replacements

Original Type Replacement
California location Harborview
Bay Area location Crystal Lake
Alaska location Oakmont
Atlanta location Clearview
Auckland location Unionville
Belgium location Jasper Creek
Brisbane location Summerville
Brussels location Brookside

Scenario 4: Wikipedia Article (Blackout Mode)

Use Case: Sharing Wikipedia content in blackout mode for complete redaction.

Source: Wikipedia - San Francisco

Detection Summary

PII Type Count Examples
Locations 1,384 San Francisco, California, Bay Area, etc.
Dates 1,225 Historical dates, years, timelines
Proper Nouns 5 Select named entities
Total 2,614

Screenshots

Original (Before SafeSnap)

Wikipedia Original

Content visible:

  • Full Wikipedia article about San Francisco
  • Geographic references throughout
  • Historical dates and timelines
  • Named individuals and organizations

Highlighted (PII Detected)

Wikipedia Highlighted

Detection Applied:

  • Extensive location detection (1,384 instances)
  • Historical date detection (1,225 instances)
  • High-confidence proper noun filtering (sensitivity: 0.95)
  • 2,614 total PII entities identified

Protected (Blackout Mode)

Wikipedia Protected

Blackout Mode Applied:

  • Uses protectionMode: 'blackout' instead of random replacement
  • All detected PII is completely redacted
  • Black boxes replace sensitive text
  • Useful when you need complete anonymization rather than realistic fake data

Blackout vs Random Mode

Feature Random Mode Blackout Mode
Output Fake realistic data Black redaction boxes
Readability High (text flows naturally) Lower (visible gaps)
Use case Demos, presentations Legal, compliance
Example San FranciscoClearview San Francisco████████████

Key Features Demonstrated

Protection Modes

Mode Description Use Case
Random Replaces PII with realistic fake data Demos, presentations, sharing examples
Blackout Completely redacts PII with black boxes Legal compliance, maximum privacy

Consistency

SafeSnap maintains replacement consistency within a session:

  • Same input → Same output (e.g., all instances of $1,399,000 become the same replacement)
  • Magnitude variance is applied consistently across all values

Detection Sensitivity

The properNounSensitivity setting controls false positive trade-offs:

  • Higher (0.9-0.95) = Fewer false positives, may miss some names
  • Lower (0.5-0.7) = Catches more names, but may flag UI labels

Last Updated: January 21, 2026
Screenshots Generated By: E2E Test Suite