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Kairos

This is a submission for the DEV Weekend Challenge: Community The Community Nepal has thousands of small Christian fellowship churches — most run entirely by volunteers with no technical background. Every Saturday, a church a…

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This is a submission for the DEV Weekend Challenge: Community






The Community



Nepal has thousands of small Christian fellowship churches — most run entirely by volunteers with no technical background. Every Saturday, a church anchor (presenter) manually types out the week's presentation: song lyrics in Nepali, Bible verses, sermon details, announcements, and prayer points — usually in PowerPoint.






What I Built



Kairos — Fellowship Builder is an AI-powered church presentation builder designed specifically for Nepali Christian communities.



An anchor fills in a simple form:




  • Fellowship date

  • Anchor name and sermon leader

  • Song lyrics (fetched automatically from a Nepali Christian songs library)

  • Bible references

  • Announcements and prayer points






Demo










Code










Kairos



A church fellowship presentation builder. Fill in your fellowship details — anchor name, sermon leader, song lyrics, Bible verse, announcements, and prayer points — and Claude AI generates a structured, slide-by-slide presentation ready to project fullscreen.



Features




  • AI-generated slides via Claude (claude-sonnet-4-6) using the Vercel AI SDK

  • Fullscreen presenter mode with keyboard navigation (arrow keys, Escape)

  • Upload a lyrics image — Claude extracts the text automatically

  • Save and manage presentations (Prisma + Supabase PostgreSQL)

  • Google OAuth sign-in via Supabase Auth



Stack





  • Next.js 16 (App Router) + TypeScript


  • Vercel AI SDK + @ai-sdk/anthropic


  • Prisma 6 ORM → Supabase PostgreSQL


  • Supabase Auth (Google OAuth only)


  • Zustand for slide/presenter state


  • Tailwind CSS v4 + shadcn/ui



Setup






  1. Clone and install:



    npm install





  2. Copy .env and fill in your values:



    ANTHROPIC_API_KEY=sk-ant-...
    NEXT_PUBLIC_SUPABASE_URL=https://xxx.supabase.co
    NEXT_PUBLIC_SUPABASE_ANON_KEY=eyJ...
    DATABASE_URL=postgresql://...





  3. Run Prisma migration:



    npx prisma migrate dev --name init





  4. Start…













How I Built It



Tech stack:




  1. Framework - Next.js 16 (App Router)

  2. AI - Gemini 2.5 Flash Lite via Vercel AI SDK (@ai-sdk/google)

  3. Database & Auth - Supabase (PostgreSQL + Google OAuth)

  4. Styling - Tailwind CSS v4 + shadcn/ui

  5. State - Zustand

  6. Deployment - Vercel



How the AI works:



The form data is sent to a Next.js API route which calls Gemini 2.5 Flash Lite with a carefully engineered system prompt. The prompt instructs the AI to:



Output only valid JSON (no markdown)

Write all slide content in Nepali Devanagari

Transliterate English names into Devanagari

Convert the Gregorian fellowship date into Bikram Sambat calendar in Nepali

Generate a warm, faith-appropriate welcome message in Nepali

Split song lyrics into individual slides per section (Verse 1, Chorus, Bridge, etc.)

Follow a fixed slide order: welcome → host → opening prayer → lyrics → sermon → Bible → announcements → closing prayer

Why Gemini 2.5 Flash Lite:

It handles Nepali Devanagari script accurately, understands Bikram Sambat calendar conversion, and is fast enough for real-time generation of 10–15 slides.



The biggest challenge:

Getting the AI to reliably output parseable JSON while also handling Nepali script, calendar conversion, and name transliteration all in a single prompt. The solution was using generateText (not streaming) and stripping any markdown code fences from the response before parsing.



This was built to solve a real problem for a real community — and it's already being used.



DEV username - BishalSunuwar202

1. Sofort-Triage & Abwehrmaßnahmen

SOC Incident Playbook: Remote Code Execution (RCE) Defense
Syntax validiert (0 Fehler)
title: Detect Exploitation - Kairos
id: 0eecf1de-f007-432c-a75f-8334159a2551
status: experimental
description: Automatisch generierte SIEM-Erkennungsregel basierend auf CTI Intelligence
references:
  - https://tsecurity.de/
author: iShareStuff CTI Automated Detection Engine
date: 2026-09-25
logsource:
  category: network_connection
  product: any
detection:
  selection:
      CommandLine|contains:
        - 'exploit'
  condition: selection
falsepositives:
  - Legitime administrative Zugriffe oder Penetrationstests
level: high
tags:
  - attack.initial_access
Syntax validiert (0 Fehler)
rule CTI_Threat_Indicator {
    meta:
        author = "iShareStuff CTI Automated Detection Engine"
        date = "2026-09-25"
        description = "YARA Signature for "
    strings:
        $str = "Kairos" ascii wide
    condition:
        any of them
}
Syntax validiert (0 Fehler)
index=security sourcetype IN ("cisco:asa", "pan:traffic", "zeek_conn", "suricata", "WinEventLog:Security")
("Kairos")
| stats count earliest(_time) as first_seen latest(_time) as last_seen by src_ip, dest_ip, dest_host, signature
| eval first_seen=strftime(first_seen, "%Y-%m-%d %H:%M:%S"), last_seen=strftime(last_seen, "%Y-%m-%d %H:%M:%S")
| sort - count
Syntax validiert (0 Fehler)
message: "*Kairos*"
Syntax validiert (0 Fehler)
CommonSecurityLog
| where Message has "Kairos"
| summarize EventCount = count(), FirstSeen = min(TimeGenerated), LastSeen = max(TimeGenerated) by SourceIP, DestinationIP, DestinationPort, Activity
| extend DetectionRule = "iShareStuff-CTI-Compiled"
| sort by EventCount desc

2. Cyber Threat Intelligence & Forensik

CTI Threat Relationship Graph2 Knoten / 1 Relationen
CVE / Incident Software MITRE ATT&CK CWE Weakness IoC
🎯
MITRE ATT&CK Matrix Navigator 14 Taktiken
Reconnaissance
-
Resource Development
-
Initial Access
Execution
Persistence
-
Privilege Escalation
Defense Evasion
Credential Access
-
Discovery
-
Lateral Movement
-
Collection
-
Command and Control
Exfiltration
-
Impact
tsecurity.de Cognitive Threat RAG
Fokus-Vektor:

Kognitive Analyse für identifizierte Bedrohung: Erhöhte Bedrohungslage im Bereich Kairos.... Basierend auf 368k Vektor-Korrelationen werden sofortige Isolationsmaßnahmen für betroffene Endpunkte empfohlen.

🛡️ Angriffsfläche & Exposure

Netzwerk/Remote-Zugriff ohne Vorauthentifizierung möglich.

⚡ Empfohlene Sofortmaßnahmen
  • 1. Perimeter-Inspektion: Relevante Portfreigaben und exponierte Endpunkte unverzüglich scannen.
  • 2. Patch-Applikation: Hersteller-Hotfix einspielen oder betroffene Daemons in isolierte DMZ-Segmente überführen.
  • 3. Telemetrie & EDR-Alerts: Prozessaufrufe und Child-Processes auf anomale Shell-Spawns überwachen.
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