AI BSSID Analyzer

AI BSSID Analyzer

Paste Wi‑Fi scan output (CSV or one record per line) and ask the AI to find suspicious BSSIDs.

OpenAI API Key Wi‑Fi scan data (CSV or lines)

Parsed Networks

No networks parsed.

AI Analysis

No analysis yet.

:root { --bg: #0f1724; --card: #0b1220; --accent: #0ea5a4; --muted: #94a3b8; --panel: rgba(255,255,255,0.03); --glass: rgba(255,255,255,0.02); } * { box-sizing: border-box; } body { margin: 0; font-family: Inter, system-ui, -apple-system, "Segoe UI", Roboto, Arial; background: linear-gradient(180deg,#071024 0%, #0b1220 100%); color: #e6eef6; min-height: 100vh; display: flex; align-items: center; justify-content: center; padding: 28px; } .wrap { width: 100%; max-width: 980px; } header { margin-bottom: 14px; } h1 { margin: 0 0 6px 0; font-size: 20px; } .lead { margin: 0; color: var(--muted); font-size: 13px; } .panel { background: linear-gradient(180deg,var(--panel), rgba(255,255,255,0.01)); border: 1px solid rgba(255,255,255,0.03); padding: 14px; border-radius: 10px; margin-bottom: 12px; } .io label { display: block; color: var(--muted); font-size: 13px; margin-top: 8px; } input[type="password"], textarea { width: 100%; padding: 10px; margin-top: 6px; border-radius: 8px; border: 1px solid rgba(255,255,255,0.04); background: rgba(255,255,255,0.02); color: #e6eef6; font-size: 14px; font-family: monospace; } textarea { min-height: 140px; resize: vertical; } .controls { margin-top: 10px; display: flex; gap: 8px; flex-wrap: wrap; } button { background: var(--glass); color: #dff4f3; border: 1px solid rgba(255,255,255,0.03); padding: 8px 12px; border-radius: 8px; cursor: pointer; font-size: 14px; } button:hover { transform: translateY(-2px); } .results h2 { margin-top: 10px; font-size: 15px; color: var(--muted); } .output { background: rgba(0,0,0,0.25); padding: 12px; border-radius: 8px; white-space: pre-wrap; font-family: ui-monospace, SFMono-Regular, Menlo, Monaco, monospace; max-height: 420px; overflow: auto; } table { width: 100%; border-collapse: collapse; margin-top: 8px; font-size: 13px; } th, td { padding: 6px 8px; border-bottom: 1px solid rgba(255,255,255,0.02); text-align: left; color: #dff4f3; } th { color: var(--muted); font-weight: 600; font-size: 12px; } .footer { color: var(--muted); margin-top: 8px; font-size: 12px; } // ai.js // Lightweight wrapper that calls OpenAI Chat Completions to analyze networks. // The browser must provide a valid API key (OpenAI) in the UI. // // NOTE: Direct calls from browsers may require CORS support from the OpenAI endpoint. // export async function analyzeNetworksWithAI(apiKey, networks) { if (!apiKey) throw new Error('Missing API key'); if (!Array.isArray(networks)) throw new Error('networks must be an array'); // Prepare concise JSON payload with networks limited to 200 entries for safety const payloadNetworks = networks.slice(0, 200).map((n) => ({ ssid: n.ssid || '', bssid: n.bssid || '', signal: n.signal || null, channel: n.channel || null, security: n.security || '' })); // System prompt instructs the model to produce JSON only const system = `You are a security analyst assistant. Given a list of Wi-Fi networks (SSID, BSSID (MAC), signal, channel, security), identify potentially suspicious or anomalous BSSIDs. Consider: - MAC OUI oddities (unknown/vendor mismatch with SSID). - Identical BSSID broadcasting multiple SSIDs. - Very weak/very strong RSSI combined with unusual SSID. - Open networks or captive portal patterns. - Common attacker setups (e.g., SSID similar to a known network, random MACs, SSID with 'free' or 'pay'). Output a single JSON object (no extra text) with the following shape: { "summary": "short summary text", "suspicious": [ { "bssid":"AA:BB:CC:11:22:33", "ssid":"Name", "reason":"short reason why suspicious", "severity":"low|medium|high", "confidence":0.0_to_1.0 } ], "recommendations":["actionable step 1", "step 2", ...], "notes":"optional free-form notes" } If you cannot identify suspicious items, return suspicious as an empty array but still return the other keys. Keep output strictly valid JSON. Use conservative judgments.`; const user = `Here are up to ${payloadNetworks.length} networks:\n` + JSON.stringify(payloadNetworks, null, 2); const body = { model: 'gpt-4', messages: [ { role: 'system', content: system }, { role: 'user', content: user } ], temperature: 0.0, max_tokens: 800 }; const resp = await fetch('https://api.openai.com/v1/chat/completions', { method: 'POST', headers: { 'Content-Type': 'application/json', 'Authorization': 'Bearer ' + apiKey }, body: JSON.stringify(body) }); if (!resp.ok) { const txt = await resp.text(); throw new Error('OpenAI API error: ' + resp.status + ' ' + txt); } const data = await resp.json(); // assistant content should be in data.choices[0].message.content const content = data?.choices?.[0]?.message?.content; if (!content) throw new Error('No content returned from model'); // Try to safely extract JSON object from content const json = extractJsonFromText(content); if (!json) { // fallback: return raw content in notes field return { raw: content }; } return json; } // Attempt to extract JSON object from text function extractJsonFromText(text) { // Trim and try direct parse const t = text.trim(); try { return JSON.parse(t); } catch (e) { // try to find the first and last brace const start = t.indexOf('{'); const end = t.lastIndexOf('}'); if (start >= 0 && end > start) { const sub = t.slice(start, end + 1); try { return JSON.parse(sub); } catch (e2) {} } } return null; } import { analyzeNetworksWithAI } from './ai.js'; // DOM const apiKeyEl = document.getElementById('apiKey'); const scanDataEl = document.getElementById('scanData'); const parseBtn = document.getElementById('parseBtn'); const analyzeBtn = document.getElementById('analyzeBtn'); const clearBtn = document.getElementById('clearBtn'); const parsedCountEl = document.getElementById('parsedCount'); const networksTableWrap = document.getElementById('networksTableWrap'); const analysisOutput = document.getElementById('analysisOutput'); let parsedNetworks = []; function parseInput(text) { const lines = text.split(/\r?\n/).map(l => l.trim()).filter(Boolean); const networks = []; // detect CSV header? const headerMaybe = lines[0] || ''; const hasHeader = /ssid/i.test(headerMaybe) && /bssid/i.test(headerMaybe); for (let i = hasHeader ? 1 : 0; i < lines.length; i++) { const line = lines[i]; // try CSV split by comma const csvParts = line.split(',').map(p => p.trim()); if (csvParts.length >= 2) { const [ssid, bssid, signal, channel, security] = csvParts; networks.push({ ssid: ssid || '', bssid: (bssid || '').toUpperCase(), signal: signal ? Number(signal) : null, channel: channel ? Number(channel) : null, security: security || '' }); continue; } // try space-separated: SSID BSSID RSSI const parts = line.split(/\s+/); if (parts.length >= 2) { networks.push({ ssid: parts.slice(0, parts.length - 1).join(' '), bssid: parts[parts.length - 1].toUpperCase(), signal: null, channel: null, security: '' }); } } return networks; } function renderParsedTable(networks) { if (!networks || networks.length === 0) { parsedCountEl.textContent = 'No networks parsed.'; networksTableWrap.innerHTML = ''; return; } parsedCountEl.textContent = `${networks.length} network(s) parsed.`; const table = document.createElement('table'); const thead = document.createElement('thead'); thead.innerHTML = 'SSIDBSSIDSignalChannelSecurity'; table.appendChild(thead); const tbody = document.createElement('tbody'); for (const n of networks) { const tr = document.createElement('tr'); tr.innerHTML = `${escapeHtml(n.ssid)}${escapeHtml(n.bssid)}${n.signal ?? ''}${n.channel ?? ''}${escapeHtml(n.security)}`; tbody.appendChild(tr); } table.appendChild(tbody); networksTableWrap.innerHTML = ''; networksTableWrap.appendChild(table); } function escapeHtml(s) { return String(s || '').replace(/[&<>"']/g, (m) => ({ '&':'&','<':'<','>':'>','"':'"',"'":''' })[m]); } parseBtn.addEventListener('click', () => { const text = scanDataEl.value || ''; parsedNetworks = parseInput(text); renderParsedTable(parsedNetworks); analysisOutput.textContent = 'No analysis yet.'; }); clearBtn.addEventListener('click', () => { parsedNetworks = []; scanDataEl.value = ''; renderParsedTable([]); analysisOutput.textContent = 'No analysis yet.'; }); analyzeBtn.addEventListener('click', async () => { try { if (!apiKeyEl.value) { alert('Please enter your OpenAI API key.'); return; } if (!parsedNetworks.length) { alert('No networks to analyze. Paste scan data and press Parse first.'); return; } analysisOutput.textContent = 'Analyzing with AI... (this may take a few seconds)'; analyzeBtn.disabled = true; parseBtn.disabled = true; const result = await analyzeNetworksWithAI(apiKeyEl.value.trim(), parsedNetworks); // display results prettily if (result && result.raw) { analysisOutput.textContent = result.raw; } else { analysisOutput.textContent = JSON.stringify(result, null, 2); } } catch (err) { analysisOutput.textContent = 'Error: ' + (err && err.message ? err.message : String(err)); } finally { analyzeBtn.disabled = false; parseBtn.disabled = false; } }); // Auto-parse sample on load if textarea has text window.addEventListener('load', () => { if (scanDataEl.value.trim()) { parsedNetworks = parseInput(scanDataEl.value); renderParsedTable(parsedNetworks); } });