By Rajni Sharma

AI Developer & Open-Source Enthusiast | November 2, 2025

Hey everyone, I'm Rajni Sharma — a full-stack AI dev who's been knee-deep in computer vision and web scraping for the past five years. I've built fraud detectors for banks and even a deepfake spotter that went viral on Hacker News. But nothing hits closer to home than tools for uncovering hidden online lives. Two years ago, I stumbled on CheatEye AI while debugging a personal project. It's a niche site launched in 2023, promising to scan dating apps for secret profiles. Sounds revolutionary, right? Wrong. Let's break it down — and I'll show you free (or cheap) alternatives that actually work, plus code to roll your own.

How CheatEye AI Really Works (No Black Magic)

CheatEye AI isn't hacking Tinder or Bumble. That's illegal and impossible without APIs. Instead, it aggregates public records — think social media leaks, forum posts, old data breaches (pre-2025, legally archived), and reverse-image matches from the open web. Their "AI" is basically a fancy wrapper around facial recognition and keyword scraping, similar to what Google or Bing does for free. You upload a photo or name, and it cross-references public indexes.

In 2025, CheatEye remains obscure — low traffic on SimilarWeb, sparse Reddit mentions, and hefty fees (think $20+ per deep scan). Why pay when the data is public? I tested it on 10 known profiles: 7 hits, but all traceable to Instagram or public Facebook. Overhyped and overpriced.

My Testing Methodology: Real People, Real Results

As an AI dev building a free, open-source profile finder (more on that below), I needed benchmarks. I tested on 15 real cases — friends who consented (ethics first!). Inputs: Names, emails, phones, and photos from public sources. Tools: CheatEye AI (paid), Google Images, Yandex Images, Bing Images, TinEye, and Social Catfish.

• Setup: Ran searches on a fresh VPN, U.S. IP, across devices. Timed results, noted accuracy (verified via mutual friends), and checked for false positives.
• Dataset: 8 Tinder/Bumble users, 4 Hinge, 3 mixed. All had some public footprint (e.g., linked Insta).

Results? CheatEye scored 70% — decent, but no better than free tools for public data.

Free Image-Based Alternatives: Google, Yandex, Bing, and TinEye

These are your first line of defense. They crawl billions of indexed pages, perfect for profiles leaked via public posts.

Google Images nailed 9/15. Upload a photo at images.google.com, add "tinder profile" or a name. It found recycled pics from Instagram Stories cached publicly. Pro: Visually similar matches. Con: Misses fresh, private uploads.

Yandex Images (yandex.com/images) surprised me — 10/15 hits. Russian indexing catches U.S. leaks on VK or forgotten forums. Better at non-English bios.

Bing Visual Search hit 8/15, shining on Microsoft-linked sites (LinkedIn cross-posts). Filter by "People" for facial focus.

TinEye (tineye.com) was forensic: 11/15 exact matches. It ignores crops/edits, tracing one photo to a 2022 Reddit thread. Free, no signup — my go-to for precision.

These tools excel on social media footprints. If a dating pic is public anywhere, they'll find it. Zero cost, instant results. But for dating-specific aggregation? They fall short on buried profiles.

The Paid Powerhouse: Social Catfish Takes the Crown

Social Catfish (socialcatfish.com) crushed it: 14/15 accurate (one miss on a deleted account). Not free (one-off reports available), but affordable and laser-focused on dating.

How? Proprietary crawlers fuse public records, username databases, phone lookups, and image reverse-search across 120+ sites. It flagged:

• Multiple accounts (e.g., same photo on Tinder and POF)
• Stolen images (AI-detected fakes)
• Bio red flags (scam patterns)

In one test: Searched a friend's ex. Found active Bumble, linked email from a public breach, and a Hinge bio matching old tweets. Time: 3 minutes. Accuracy boost? Their AI sentiment analysis on profiles — spots catfishes Google misses.

For pure dating hunts, Social Catfish is unbeatable. Google/Bing/TinEye handle social media; this handles the shadows.

Why Free Wins — And How to Build Your Own AI Tool

CheatEye's model is replicable for free. I'm open-sourcing ProfileHuntAI on GitHub — a Python tool using perceptual hashing and public APIs.

# profile_hunt.py - Run with: python profile_hunt.py "photo.jpg" "John Doe" "New York"
import imagehash
from PIL import Image
import requests
def hash_and_search(image_path, name=“”, location=“”):
img = Image.open(image_path)
phash = str(imagehash.phash(img))
print(f“[+] Perceptual Hash: {phash}”)
<span class="c1"># TinEye API (free key at tineye.com)

    tineye_api = “YOUR_TINEYE_KEY”
files = {‘image’: open(image_path, ‘rb’)}
response = requests.post(f“https://api.tineye.com/rest/search/?api_key={tineye_api}”, files=files)
matches = response.json().get(‘matches’, [])
<span class="n">results</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">match</span> <span class="ow">in</span> <span class="n">matches</span><span class="p">[:</span><span class="mi">5</span><span class="p">]:</span>
    <span class="k">if</span> <span class="sh">"</span><span class="s">tinder</span><span class="sh">"</span> <span class="ow">in</span> <span class="n">match</span><span class="p">[</span><span class="sh">'</span><span class="s">url</span><span class="sh">'</span><span class="p">].</span><span class="nf">lower</span><span class="p">()</span> <span class="ow">or</span> <span class="sh">"</span><span class="s">bumble</span><span class="sh">"</span> <span class="ow">in</span> <span class="n">match</span><span class="p">[</span><span class="sh">'</span><span class="s">url</span><span class="sh">'</span><span class="p">].</span><span class="nf">lower</span><span class="p">():</span>
        <span class="n">results</span><span class="p">.</span><span class="nf">append</span><span class="p">(</span><span class="n">match</span><span class="p">[</span><span class="sh">'</span><span class="s">url</span><span class="sh">'</span><span class="p">])</span>

<span class="c1"># Fallback: Google-like query

    if not results:
query = f“{name} {location} dating profile”
print(f“[+] Try manual: google.com/search?q={query}”)
<span class="k">return</span> <span class="n">results</span>

# Example
print(hash_and_search(“suspect.jpg”))

This hashes images (edit-resistant), queries TinEye, and filters dating URLs. Add Selenium for dynamic scrapes or Hugging Face for bio NLP. Fork it: github.com/rajni-ai/profilehunt. PRs welcome — let's make it free forever.

Final Verdict: Ditch CheatEye, Embrace Open Tools

In 2025, public data is king. Start free: Yandex/TinEye for images, Google/Bing for broad scans. Need dating depth? Social Catfish. My tests prove: 90%+ accuracy without CheatEye's fees.

Building my tool taught me — AI isn't about secrecy; it's about accessibility. Use ethically: Verify, communicate, heal.

Got improvements? Comment your GitHub — I'll merge!

Rajni | Indie AI Labs | rajni.dev