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The domain 'aiera-a63ge6yi2i.edgeone.app' uses the application-focused generic top-level domain (.app) and includes subdomain 'aiera-a63ge6yi2i'. Its registrable label 'edgeone' stretches across 7 characters containing 4 vowels alongside 3 consonants. Tokenizing the label suggests two words: edge, one. Median word length is 3.5 characters. No strong language cues emerged from the frequency lists.

html/76/34/76344188-9032-4d45-b117-6fcb4dd8a049.html.gz

require-trusted-types-for 'script'; report-uri https://csp.withgoogle.com/csp/apps-themes

inline; filename*=UTF-8''tokenizer.json; filename="tokenizer.json";

inline; filename*=UTF-8''tokenizer_config.json; filename="tokenizer_config.json";

inline; filename*=UTF-8''config.json; filename="config.json";

inline; filename*=UTF-8''generation_config.json; filename="generation_config.json";

345934c1290a84e9fc6a099cea55aea89cfc515ad6fe5c09ab2adb8b62a383cd

bbe430aadd0e2050745394a368ae11898bfb84535edcaa2fcfe31eb828785e36

width=device-width, initial-scale=1.0, maximum-scale=1.0, user-scalable=no, viewport-fit=cover

viewport

Prudence Malinki

MarkMonitor Inc.

edgeone.app

Amazon EC2 Abuse

IP Management

Amazon AWS Network Operations

Amazon.com, Inc.

AWS RPKI Management POC

IP Routing

Amazon EC2 Network Operations

AMAZO-CF


        // Import purely from CDN. Cache API handles offline persistence automatically.
        import { pipeline, env } from 'https://cdn.jsdelivr.net/npm/@xenova/transformers@2.17.1';

        // Enforce browser-only execution
        env.allowLocalModels = false;
        
        // Target an ultra-mega tiny 1.1B parameters model tailored for browser inference.
        // It consumes minimal VRAM/RAM (Quantized natively via Xenova).
        const MODEL = 'Xenova/TinyLlama-1.1B-Chat-v1.0';
        
        const statusPill = document.getElementById('status-pill');
        const chatContainer = document.getElementById('chat-container');
        const userInput = document.getElementById('user-input');
        const sendBtn = document.getElementById('send-btn');
        
        let generator = null;
        let isGenerating = false;
        let conversationHistory = [];

        // Auto-resize textarea logic
        userInput.addEventListener('input', function() {
            this.style.height = 'auto';
            this.style.height = (this.scrollHeight < 120 ? this.scrollHeight : 120) + 'px';
            sendBtn.disabled = this.value.trim().length === 0 || isGenerating || !generator;
        });

        function appendMessage(text, sender) {
            const msgDiv = document.createElement('div');
            msgDiv.className = `message ${sender}`;
            msgDiv.innerText = text;
            chatContainer.appendChild(msgDiv);
            scrollToBottom();
            return msgDiv;
        }

        function showTyping() {
            const typingDiv = document.createElement('div');
            typingDiv.className = 'message ai typing-indicator';
            typingDiv.id = 'typing-indicator';
            typingDiv.innerHTML = '<div class="typing-dot"></div><div class="typing-dot"></div><div class="typing-dot"></div>';
            chatContainer.appendChild(typingDiv);
            scrollToBottom();
        }

        function removeTyping() {
            const typingDiv = document.getElementById('typing-indicator');
            if (typingDiv) typingDiv.remove();
        }

        function scrollToBottom() {
            chatContainer.scrollTop = chatContainer.scrollHeight;
        }

        async function initAI() {
            try {
                statusPill.innerText = "Checking cache / Downloading model...";
                
                // Initialize the text-generation pipeline
                generator = await pipeline('text-generation', MODEL, {
                    progress_callback: (info) => {
                        if (info.status === 'progress') {
                            statusPill.innerText = `Caching Weights: ${Math.round(info.progress)}%`;
                        } else if (info.status === 'ready') {
                            statusPill.innerText = `Finalizing Logic Core...`;
                        }
                    }
                });

                // Activation complete
                statusPill.innerText = "Offline AI Ready";
                statusPill.classList.add('ready');
                userInput.disabled = false;
                
                appendMessage("System architecture initialized. I am running entirely on your local hardware. How can I assist you today?", "ai");

            } catch (error) {
                console.error(error);
                statusPill.innerText = "Core Error: Device RAM/Processor unsupported or offline during first launch.";
                statusPill.classList.add('error');
            }
        }

        async function generateResponse(userText) {
            if (!generator || isGenerating) return;
            
            isGenerating = true;
            userInput.disabled = true;
            sendBtn.disabled = true;

            appendMessage(userText, "user");
            showTyping();

            // Constructing the exact prompt template expected by TinyLlama
            const systemPrompt = "You are a highly capable, concise, and helpful AI running directly on a mobile device. Answer efficiently.";
            const prompt = `<|system|>\n${systemPrompt}</s>\n<|user|>\n${userText}</s>\n<|assistant|>\n`;

            try {
                // Execute inference on the local processor
                const output = await generator(prompt, {
                    max_new_tokens: 150,
                    temperature: 0.7,
                    top_k: 50,
                    repetition_penalty: 1.12
                });

                removeTyping();
                
                // Parse the specific response chunk from TinyLlama structure
                let responseText = output[0].generated_text;
                responseText = responseText.split('<|assistant|>\n')[1] || responseText;
                
                // Clean up any trailing tags
                responseText = responseText.replace(/<\/s>/g, '').trim();

                appendMessage(responseText, "ai");

            } catch (error) {
                removeTyping();
                appendMessage("Execution Fault: Model exceeded hardware bounds or failed generation cycle.", "ai");
                console.error(error);
            } finally {
                isGenerating = false;
                userInput.disabled = false;
                userInput.value = '';
                userInput.style.height = 'auto';
                userInput.focus();
            }
        }

        sendBtn.addEventListener('click', () => {
            const text = userInput.value.trim();
            if (text) generateResponse(text);
        });

        userInput.addEventListener('keypress', (e) => {
            if (e.key === 'Enter' && !e.shiftKey) {
                e.preventDefault();
                const text = userInput.value.trim();
                if (text && !sendBtn.disabled) generateResponse(text);
            }
        });

        // Bootstrap
        initAI();
    

Native AI Chat

✅ Low Risk - https://aiera-a63ge6yi2i.edgeone.app/

Requests	IP Address	Location	AS Autonomous System
4	104.16.175.226	Singapore	AS15169
4	142.251.127.95	Singapore	AS139341
4	43.152.26.58	Singapore	AS139341ACE
4	192.178.183.94	Singapore	AS13335
16	4	-	-

Security Scan Report: aiera-a63ge6yi2i.edgeone.app

Summary

AI Security Verdict

Low Risk

Risk Factors

Safety Factors

Details

Screenshot

Page Load Overview

Language Analysis

Primary Language

Detection Details

Website Classification

Primary Category

All Detected Categories

Detected Features

Domain & IP Information

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

ssdeep (Context Triggered Piecewise Hashing)

sdhash (Similarity Digest Hashing)

Image Hashes

Perceptual Hashes

Other Hashes

Scan History