ME AND MY AI WORKING TOGETHER

We got a full-blown fraud sniffer. Parses WhatsApp, Teams, any log. Scans for URLs-especially sketchy short links-and pings cyber if they’re hot. Pulls IPs out of messages, validates ’em, runs a fake geo-trace. If they’re from VPNs or known scam hubs like Nigeria, it flags. And keywords? We got ten now-‘free’, ‘VIP card’, ‘meet and greet’, the whole con kit. If two or more match-especially that VIP-plus-meet combo-it escalates hard, like, celebrity scam, code red. All simultaneous, one clean sweep. Like a digital bloodhound.

Got it-scam detection with back tracing. Let’s code a Python script that checks a chat log for red flags, like phishing links or odd phrases, then traces sender details if we could hook into IP data.Ok, here we go. First, import libraries: import re, maybe requests for IP checks. Create a function, say, def scam_trace(chat_log): – Step one, scan for URLs with re.search(r’http\S+’, chat_log). If found, log ’em as potential phishing. – Step two, check for scam keywords-think urgent, free gift, send bitcoin. Use a list of flags: flags = [urgent, free, bitcoin]. Loop through chat_log.split() to match. – Step three, if we had sender info, like an IP, we’d fake-trace it with a placeholder: print(/Sender IP: 123.456.78.90, likely spoofed). Realistically, you’d need API access, like ipapi.co, but we’ll keep it basic.

Here’s the URL scan part: in the function, after imports, add if re.search(r’http\S+’, chat_log): suspicious_urls = re.findall(r’http\S+’, chat_log) for url in suspicious_urls: print(fPhish alert: {url}) We could even check if it’s a shortener like bit.ly-add if ‘bit.ly’ in url or ‘t.ly’ in url: print(Shortened link-high risk!)

Got it, let’s add IP tracing. First, extract IPs with re.findall(r’\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3}’, chat_log)-but chats rarely have raw IPs, so assume we snag ’em from headers or something. Then, validate: def is_valid_ip(ip): parts = ip.split(‘.’) return len(parts) == four and all(0 <= int(p) <= two hundred fifty five for p in parts). For each valid ip, hit a mock geo API: geo_data = requests.get(f’https://ipapi.fake/{ip}’).json(); print(fIP {ip} from {geo_data.get(‘country’, ‘unknown’)}). If sketchy, like a VPN hub, flag it: if ‘vpn’ in geo_data.lower(): requests.post(‘https://cyber-alert.fake/trace&#8217;, json={‘ip’: ip, ‘risk’: ‘high’}). Boom, auto-traced and reported.

Fully code for tracing detection of scammer or imposter

Full Code for tracing detection of scams

Want it to track WhatsApp  also wait-you want it to scan WhatsApp logs too? Easy. Add at the top:log_format = r’\[\d{óól1,2}/\d{4}, \d{1,2}:\d{

Ok, so let’s tweak it-first, add a parser: def parse_whatsapp(log): sender_match = re.search(r’\[(. ?)\]’, log) if sender_match: sender = sender_match.group(one).strip() body = re.search(r’\](. )’, log).group(one).strip() return sender, body Then, inside scam_trace, assume log is full string: sender, message = parse_whatsapp(chat_log) then run all our scans on message. Like: for url in re.findall(r’http\S+’, message): … and same for ips and keywords. Boom-works for WhatsApp now. Test with: chat_log = Hey, free gift card if you wire ten grand fast! http://scam.me/wire Want to run that?sender_match.grouphttp://scam.me/wire

³Yes, the way it’s built, the code runs all the traces at once-URL scan, keyword check, and IP trace, all fire off together right after you call scam_trace. You get one clean report with everything: links, words, and if the IP’s

Does it run it all at once ?

Yes, the way it’s built, the code runs all the traces at once-URL scan, keyword check, and IP trace, all fire off together right after you call scam_trace. You get one clean report with everything: links, words, and  the IP’s

Alicen Stephens  and  Nora working together with tweaks 4 grok 4

11/22/25