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    <title>DEV Community: Anurag T</title>
    <description>The latest articles on DEV Community by Anurag T (@bhaianu264).</description>
    <link>https://dev.to/bhaianu264</link>
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      <title>DEV Community: Anurag T</title>
      <link>https://dev.to/bhaianu264</link>
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      <title>OmniGuard AI</title>
      <dc:creator>Anurag T</dc:creator>
      <pubDate>Sun, 04 Oct 2026 14:38:33 +0000</pubDate>
      <link>https://dev.to/bhaianu264/omniguard-ai-2520</link>
      <guid>https://dev.to/bhaianu264/omniguard-ai-2520</guid>
      <description>&lt;p&gt;&lt;em&gt;This is a submission for the &lt;a href="https://dev.to/challenges/hacktoberfest-weekend-2026-10-01"&gt;Hacktoberfest Weekend Challenge: Build for a Friend and Family&lt;/a&gt;&lt;/em&gt;&lt;/p&gt;

&lt;p&gt;What I Built&lt;br&gt;
I built OmniGuard AI — a free, open-source tool that detects scams, phishing messages, and fake UPI payment requests before your family falls for them.&lt;/p&gt;

&lt;p&gt;I made it for my parents and grandparents. They keep getting fake WhatsApp messages like "Your bank account is blocked, click here immediately." They never know if it is real or a scam. Now they just paste the message and OmniGuard AI tells them instantly — is it safe or dangerous, why it was flagged, and exactly what to do next.&lt;/p&gt;

&lt;p&gt;It works in 10 languages including Hindi and Marathi so my family can use it in their own language. 🇮🇳&lt;/p&gt;

&lt;p&gt;Demo&lt;br&gt;
🔗 &lt;a href="https://kavach-web-2mkc.onrender.com" rel="noopener noreferrer"&gt;https://kavach-web-2mkc.onrender.com&lt;/a&gt;&lt;/p&gt;

&lt;p&gt;Code&lt;br&gt;
&lt;/p&gt;
&lt;div class="ltag-github-readme-tag"&gt;
  &lt;div class="readme-overview"&gt;
    &lt;h2&gt;
      &lt;img src="https://assets.dev.to/assets/github-logo-5a155e1f9a670af7944dd5e12375bc76ed542ea80224905ecaf878b9157cdefc.svg" alt="GitHub logo"&gt;
      &lt;a href="https://github.com/Anurag-tech22" rel="noopener noreferrer"&gt;
        Anurag-tech22
      &lt;/a&gt; / &lt;a href="https://github.com/Anurag-tech22/DEV1" rel="noopener noreferrer"&gt;
        DEV1
      &lt;/a&gt;
    &lt;/h2&gt;
    &lt;h3&gt;
      
    &lt;/h3&gt;
  &lt;/div&gt;
  &lt;div class="ltag-github-body"&gt;
    
&lt;div id="readme" class="md"&gt;&lt;div class="markdown-heading"&gt;
&lt;h1 class="heading-element"&gt;OmniGuard AI&lt;/h1&gt;
&lt;/div&gt;
&lt;p&gt;&lt;a href="https://opensource.org/licenses/MIT" rel="nofollow noopener noreferrer"&gt;&lt;img src="https://camo.githubusercontent.com/08cef40a9105b6526ca22088bc514fbfdbc9aac1ddbf8d4e6c750e3a88a44dca/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f4c6963656e73652d4d49542d626c75652e737667" alt="License: MIT"&gt;&lt;/a&gt;
&lt;a href="https://github.com/Anurag-tech22/DEV1/actions" rel="noopener noreferrer"&gt;&lt;img src="https://github.com/Anurag-tech22/DEV1/actions/workflows/ci.yml/badge.svg" alt="CI"&gt;&lt;/a&gt;
&lt;a href="https://python.org" rel="nofollow noopener noreferrer"&gt;&lt;img src="https://camo.githubusercontent.com/a32434c66a6218d5c449494027a09b4172006dfef226e80e0bc7735ec9f29790/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f507974686f6e2d332e31312b2d3337373641422e7376673f6c6f676f3d707974686f6e266c6f676f436f6c6f723d7768697465" alt="Python: 3.11+"&gt;&lt;/a&gt;
&lt;a href="https://react.dev" rel="nofollow noopener noreferrer"&gt;&lt;img src="https://camo.githubusercontent.com/9d70b76ed637884e8ac01f40a736ba95a2955eb07d75b9597a02dcfdb613ac0d/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f52656163742d31392e302d3631444146422e7376673f6c6f676f3d7265616374266c6f676f436f6c6f723d626c61636b" alt="React: 19"&gt;&lt;/a&gt;&lt;/p&gt;
&lt;p&gt;OmniGuard AI is an open-source fraud detection and cyber defense platform. It is designed to identify and neutralize social engineering attacks, phishing, and financial fraud across digital channels.&lt;/p&gt;
&lt;p&gt;&lt;a href="https://github.com/Anurag-tech22/DEV1#features" rel="noopener noreferrer"&gt;Features&lt;/a&gt; • &lt;a href="https://github.com/Anurag-tech22/DEV1#architecture" rel="noopener noreferrer"&gt;Architecture&lt;/a&gt; • &lt;a href="https://github.com/Anurag-tech22/DEV1#installation" rel="noopener noreferrer"&gt;Installation&lt;/a&gt; • &lt;a href="https://github.com/Anurag-tech22/DEV1#api" rel="noopener noreferrer"&gt;API&lt;/a&gt; • &lt;a href="https://github.com/Anurag-tech22/DEV1/CONTRIBUTING.md" rel="noopener noreferrer"&gt;Contributing&lt;/a&gt; • &lt;a href="https://github.com/Anurag-tech22/DEV1/LICENSE" rel="noopener noreferrer"&gt;License&lt;/a&gt;&lt;/p&gt;
&lt;div class="markdown-heading"&gt;
&lt;h2 class="heading-element"&gt;Features&lt;/h2&gt;
&lt;/div&gt;
&lt;ul&gt;
&lt;li&gt;
&lt;strong&gt;Threat Core&lt;/strong&gt;: Pattern recognition for detecting digital threats, fake KYC, lottery bait, APK droppers, and courier imposter schemes.&lt;/li&gt;
&lt;li&gt;
&lt;strong&gt;Threat Radar&lt;/strong&gt;: Live scam feed, homoglyph link inspection, and QR/UPI debit analyzer.&lt;/li&gt;
&lt;li&gt;
&lt;strong&gt;Audio Guard&lt;/strong&gt;: Audio waveform visualizer and speech analyzer for voice cloning detection.&lt;/li&gt;
&lt;li&gt;
&lt;strong&gt;Android APK Sandbox&lt;/strong&gt;: Manifest privilege analyzer, Accessibility hijacking detector, and trojan profiler.&lt;/li&gt;
&lt;li&gt;
&lt;strong&gt;Dossier Export&lt;/strong&gt;: Formats incident data into structured evidence dossiers for legal submission.&lt;/li&gt;
&lt;li&gt;
&lt;strong&gt;Multi-language Support&lt;/strong&gt;: Localization in English, Hindi, Marathi, Spanish, French, German, Chinese, Japanese, Arabic, and Portuguese.&lt;/li&gt;
&lt;li&gt;
&lt;strong&gt;Interactive Drills&lt;/strong&gt;: Scenario simulator for training users to identify phishing and authority impersonation.&lt;/li&gt;
&lt;li&gt;
&lt;strong&gt;Breach Intel&lt;/strong&gt;: Checks compromised credentials, leaked…&lt;/li&gt;
&lt;/ul&gt;&lt;/div&gt;
  &lt;/div&gt;
  &lt;div class="gh-btn-container"&gt;&lt;a class="gh-btn" href="https://github.com/Anurag-tech22/DEV1" rel="noopener noreferrer"&gt;View on GitHub&lt;/a&gt;&lt;/div&gt;
&lt;/div&gt;


&lt;p&gt;How I Built It&lt;br&gt;
Backend: FastAPI (Python) with a custom heuristic scam detection rule engine&lt;br&gt;
Frontend: React 19 + Vite — message scanner, live threat radar, practice mode, and a downloadable threat report you can file with the police&lt;br&gt;
Deployed on Render using Docker multi-stage build — Node builds the React app, Python serves the backend, one single container&lt;br&gt;
For AI, I built a custom open-source AI agent harness called OmniAIEngine. It automatically routes threat analysis to the best available model:&lt;/p&gt;

&lt;p&gt;Local open-source inference — runs Qwen 2.5 1.5B via llama.cpp fully self-hosted, zero API cost&lt;br&gt;
Falls back to Gemini or OpenAI if API keys are provided&lt;br&gt;
If nothing is available, uses the built-in heuristic rule engine&lt;br&gt;
This means the app works completely offline with open-weight models and needs no paid API at all.&lt;/p&gt;

&lt;p&gt;Why Does Open Innovation Matter?&lt;br&gt;
My family cannot afford a paid security product. With open source, I built something completely free that anyone in India can use. No subscriptions, no black box — you can see exactly why something was flagged, which builds real trust with non-tech users.&lt;/p&gt;

&lt;p&gt;Open-weight models like Qwen running via llama.cpp made it possible to run real AI inference without sending anyone's private messages to a third-party cloud. Privacy-first and free — that is what open innovation made possible here.&lt;/p&gt;

&lt;p&gt;Prize Categories&lt;br&gt;
🏆 Render — Best Use of Render&lt;/p&gt;

</description>
      <category>devchallenge</category>
      <category>weekendchallenge</category>
      <category>hf26challenge</category>
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