π‘οΈ CyberPrep β AI-Powered Cybersecurity Interview Simulator
CyberPrep is a professional-grade cybersecurity interview preparation platform that simulates real interview experiences across 8 cybersecurity career paths. Unlike generic flashcard apps, CyberPrep provides:
Role-specific study modules with flash cards and knowledge checks
AI-powered mock interviews with Claude evaluating your responses
Detailed scoring and feedback with actionable improvement areas
Complete preparation journey from role brief to interview debrief
Role
Focus
Difficulty
Salary Range
SOC Analyst
Security monitoring & incident triage
ββ
$55K β $95K
Penetration Tester
Ethical hacking & red team
ββββ
$85K β $145K
Security Engineer
Security architecture & infrastructure
βββ
$95K β $165K
Incident Responder/DFIR
Forensics & breach response
ββββ
$80K β $140K
Cloud Security Engineer
AWS/Azure/GCP security
βββ
$100K β $175K
GRC Analyst
Governance, risk & compliance
ββ
$65K β $120K
Threat Intelligence Analyst
CTI & threat research
βββ
$75K β $130K
CISO / Security Manager
Leadership & program strategy
βββββ
$150K β $300K+
π 3-Phase Preparation Journey
Phase
Focus
Key Features
01 β Role Brief
Understand the role
Responsibilities, salary data, certifications, tools, day-in-the-life, key skills
02 β Study Modules
Learn core concepts
3 modules per role Β· 5 flash cards each Β· 5-question knowledge checks
03 β Mock Interview
Practice & get scored
10 questions Β· 3-min timer Β· Claude AI scoring Β· Detailed feedback
π§ Phase 01: Role Brief β Understand Your Target
Each role includes a comprehensive brief with:
Element
Description
Role Overview
Detailed description of responsibilities and impact
Salary Range
Market compensation data
Job Growth
Industry projection through 2030
Key Certifications
Required/beneficial certs (CISSP, OSCP, Security+, etc.)
Core Tools
Technologies you'll work with daily
Day in the Life
Realistic daily activities and tasks
π Phase 02: Study Modules β Interactive Learning
Module Structure (3 per role)
Module Focus
Sample Topics
SIEM & Log Analysis
SIEM functions, log normalization, false positives, correlation rules, MTTD
Incident Response & Triage
NIST lifecycle, IoCs, containment vs eradication, playbooks
Threat Intelligence & Tools
MITRE ATT&CK, threat hunting, Diamond Model, OSINT
5 interactive cards per module
Click-to-flip design revealing answers
Previous/Next navigation
Covers core concepts with concise, exam-ready answers
5-question multiple-choice quizzes
Immediate feedback with explanations
Progress tracking across modules
Completion status saved during session
π€ Phase 03: Mock Interview β AI-Powered Evaluation
Element
Details
Question Count
10 questions per interview
Question Types
Technical, Behavioral, Scenario-based
Time Limit
3 minutes per question
Timer Warning
Yellow at 60s, Red flashing at 30s
Skip Option
Can skip (score = 0)
AI Scoring with Claude π
Each answer is evaluated against a professional rubric:
Score Range
Rating
Description
9-10
Exceptional
Complete, accurate, specific examples, demonstrates expertise
7-8
Strong
Covers main points well, minor gaps
5-6
Adequate
Basic concepts correct, lacks depth
3-4
Weak
Partial understanding, significant gaps
1-2
Poor
Mostly incorrect or vague
0
None
No answer or completely irrelevant
Detailed Feedback per Question
After the interview, each response receives:
β What was good β Strengths identified in your answer
β What was missing β Key concepts or specifics you omitted
π‘ Ideal answer β What a perfect response would include
Your answer β Full text of your response
Metric
Description
Overall Score
Percentage score (0-100%)
Letter Grade
A+ through F based on performance
Answered Count
Number of questions with substantive answers
Strong Answers
Count of 7+ scores
Type Breakdown
Technical, Behavioral, Scenario scores
Radial score ring with color-coded performance
Bar charts per question type
Expandable question review sections
Color-coded scores (green=strong, yellow=average, red=weak)
Dynamic recommendations based on your score:
Score Range
Recommendations
< 60%
Deep study required Β· Focus on foundational questions
60-79%
Review weak areas Β· Improve answer structure (STAR method)
80%+
Strong performance Β· Advanced preparation Β· Company research
Cyberpunk Interview Aesthetic π₯οΈ
Deep dark background (#05080f) for focus during interviews
Glass-morphism cards with backdrop blur
Gradient mesh background for depth
Cyan/Blue accents (#3b82f6, #06b6d4) for primary UI
Emerald (#10b981) for correct answers and success
Amber (#f59e0b) for warnings and scenario questions
Rose (#f43f5e) for critical/difficult elements
Violet (#8b5cf6) for threat intelligence
Font
Usage
Outfit
Headers, body text, UI labels
JetBrains Mono
Terminal output, code, technical data, badges
Fade-up staggered loading for visual hierarchy
Typewriter effect for question display
Blinking cursor in typewriter
Timer with color transitions (white β yellow β red flashing)
Pulse animations for phase indicators
Smooth card flip for flash cards
Expandable result sections with chevron rotation
Progress bars throughout the experience
Severity/Tag Color Coding π¨
Tag Type
Color
Usage
Badge Blue
#3b82f6
Technical questions, general labels
Badge Emerald
#10b981
Behavioral questions, success states
Badge Amber
#f59e0b
Scenario questions, warnings
Badge Rose
#f43f5e
Critical, high difficulty
Badge Violet
#8b5cf6
Threat intelligence, advanced topics
Badge Cyan
#06b6d4
Cloud security, technical depth
π οΈ Technical Implementation
Technology
Purpose
HTML5
Structure and semantic markup
CSS3
Custom styling, animations, glass-morphism
Vanilla JavaScript
State management, DOM manipulation
Claude API
AI-powered answer scoring
No Frameworks
Pure vanilla β no React, Vue, or Angular
Component
Purpose
Features
RoleGrid
Role selection
8 cards with difficulty, color coding
BriefHero
Role overview
Salary, growth, tags, certifications
FlashcardDeck
Study cards
Click-to-flip, previous/next navigation
QuizModule
Knowledge checks
Multiple choice, immediate feedback
InterviewSidebar
Question navigation
Status indicators (active/answered/skipped)
Timer
Time management
3-minute countdown with warnings
Typewriter
Question display
Character-by-character animation
ScoringOverlay
Processing UI
Loading spinner during AI evaluation
DebriefPanel
Results display
Expandable sections, score visualization
Role = {
id, name, subtitle, icon, color, difficulty,
tags, tagLabels, desc, salary, growth, overview,
certs, tools, skills, dayInLife,
modules : [ {
title, cards : [ { q, a} ] , quiz : [ { q, opts, ans, exp} ]
} ] ,
questions : [ { q, type, difficulty} ]
}
State Variable
Purpose
role
Currently selected role
moduleIndex
Current module (0-2)
moduleDone
Module completion status
cardIndex
Current flash card
quizIndex
Current quiz question
interviewIndex
Current interview question
answers
Array of user answers
results
AI scoring results
timerSeconds
Remaining time (180 max)
π₯ Video Demo Script (90 seconds)
Time
Phase
Action
0:00
Home
Landing page with role grid, 8 career tracks displayed
0:05
Role Select
Click SOC Analyst β Brief screen loads
0:15
Brief
Show salary ($55K-95K), certs (Security+, CySA+), tools (Splunk, Sentinel)
0:25
Study
Module 1: SIEM & Log Analysis β Flip through 5 flash cards
0:40
Knowledge Check
Answer quiz question β "True positive/false positive" β Correct!
0:50
Complete Module
Module 1 done, progress shows 1/3
1:00
Interview Intro
Start mock interview for SOC Analyst
1:10
Interview
Question 1: "Walk me through investigating a suspicious login alert" β Type answer
1:25
Submit
Answer submitted, move to Question 2
1:40
Complete
All 10 questions answered β Scoring overlay
1:50
Debrief
82% score, grade A, expand feedback for each question
2:00
Next Steps
Recommendations: review weak areas, practice STAR method
Metric
Target
Load Time
< 1.5 seconds
Memory Usage
< 50 MB
API Calls
Claude API (10 per interview)
Animations
60 fps smooth
Responsive
Desktop-first with mobile breakpoints
Chrome (latest)
Firefox (latest)
Safari (latest)
Edge (latest)
π‘οΈ Data Flow & Architecture
User selects role
β
Role brief loads (static data)
β
Study modules (3 per role)
βββ Flash cards (interactive)
βββ Quizzes (5 Q's each)
β
Interview intro
β
Mock interview (10 questions)
βββ Timer (3 min per Q)
βββ Answer stored in State.answers
βββ Skip option available
β
AI Scoring (Claude API)
βββ Each answer sent for evaluation
βββ Score (0-10) + structured feedback
βββ Results stored in State.results
β
Debrief screen
βββ Overall score (0-100%)
βββ Grade (A+ through F)
βββ Question-by-question feedback
βββ Recommended next steps
MIT License β see LICENSE file for details.
Anthropic Claude β AI-powered answer evaluation
Google Fonts β Outfit and JetBrains Mono fonts
No external libraries β Pure vanilla implementation
Last updated: March 2026