Yo, OP, this thread's a straight-up W — dropping those drive-in dorks like it's nothing. Been lurking carder.market for years, but your angle on "order ahead" portals for low-scrutiny hits is chef's kiss. Nothing beats rolling up to a McD's or Starbucks clone at 3 AM with a fresh BIN, no eyeballs on you, and a $30 haul in under 5 mins. I've burned through enough proxies testing this shit to know: 70% of these spots are running outdated Magento or WooCommerce installs with zero 3DS enforcement, especially the regional chains popping up post-pandemic. Your filters caught me a Wendy's affiliate last month that auto-shipped fries and gift cards without so much as a ZIP check — netted $120 after reship fees.
But let's level up, fam. I'll expand on your base dorks with a full toolkit I've iterated from real-world runs (EU/US cross-border, 2024-2025 logs). These aren't spray-and-pray; they're surgically tuned for drive-thru e-comms where the backend prioritizes throughput over fraud gates. I've cross-verified 'em against Shodan scans for exposed APIs and paired with custom Python scrapers (Puppeteer + Selenium hybrid) to automate the recon. Key evolution since your post: With the 2025 PCI DSS 4.0 rollouts, more shops are layering in tokenization, so I've baked in negation for "stripe.js" and "braintree" endpoints to dodge the noise. Also, post-Q3 '25, Visa's pushing harder on BIN velocity alerts — stick to 1-2 orders per IP/hour, and always gen CCs with matching AVS ghosts (tools like Namso or CCGen Pro).
Advanced Dork Arsenal: Tiered for Yield vs. Risk
I've bucketed these by strike rate (based on 500+ scans, ~15% conversion to live hits). Run 'em through Google Custom Search API or a VPS-hosted Zenserp for geo-spoofing. Pro move: Chain with site:*.app or site:*.io to hit mobile-first apps that sync poorly with desktop fraud rules.
- Tier 1: High-Volume Recon (80% Yield, Low Risk – Broad Nets for Newbies) inurl
/order-ahead | /mobile-order | /curbside) ("drive thru" OR "drive-thru" OR "pickup window") "pay now" -inurl3ds | verify | otp | captcha) site:.com | site:.net Deep Dive: This pulls ~200-300 results per run, focusing on unsecured checkout funnels. Why it crushes? Drive-ins like Taco Bell's app portals often expose raw form posts without CSRF tokens — test with Burp Intruder payloads like amount=1.00&cc=4111111111111111&exp=12/27&cvv=000. In my Philly runs, it flagged 12 sites; 3 greenlit $10 auth holds. Negate site:amazon.com or big-box to avoid blackhole results. Risk Mit: Rotate UAs (iOS 18 Safari > Android Chrome 120) and headers (Accept-Language: en-US). Expect 10-15% false positives from defunct stores.
- Tier 2: Geo-Targeted Precision (60% Yield, Medium Risk – Urban Chain Exploitation) intitle:"Drive Thru Menu" | intitle:"Curbside Checkout" "credit card accepted" ("fast food" OR "coffee shop" OR "pharmacy drive") geocode:40.7128,-74.0060,25mi -inurlsecure | fraud | riskified) Deep Dive: Swap the NYC coords for your playground (e.g., LA: 34.0522,-118.2437). This leverages Google's geo-op to hone in on clusters — think NYC's Shake Shack drive-thrus or SoCal's In-N-Out portals. Pulled a goldmine last week: A Dunkin' franchise app leaking session IDs via unminified JS (/api/v1/order?token=eyJ...). Scaled to $80 in digital vouchers (resold on Paxful for 60% markup). Add filetype
hp to sniff backend leaks, then proxy-chain to the server's IP for direct API pokes. Risk Mit: Use residential proxies (Luminati/SOAX, $5/GB) matched to the geo. Cap at $50/order to evade micro-velocity triggers; I've seen TSYS flag anything over on the third dip.
- Tier 3: Niche High-Margin Plays (40% Yield, High Risk – Pharma/Convenience Deep Cuts) inurl/drive-thru-pharmacy | /quick-pickup | /contactless-pay) ("prescription refill" OR "essentials order") "add payment" -inurlavs | bincheck | squire | signet) ext:html | ext:js site:.us *Deep Dive*: Targets juicier prey like Rite Aid or 7-Eleven drive portals, where "health items" (OTC meds, smokes) slide under compliance radars. A '25 exploit I chained: Their JSON endpoints often dump cart data pre-auth ({"total":29.99,"cc_token":null}). Landed a $250 haul on vapes and snacks from a Cali chain — reshipped via mule drops for clean trails. Filter with min_faves:20` if scraping X for promo buzz (e.g., new drive-thru openings). For evasion, inject JS via dev tools to bypass client-side CVV masks. Risk Mit: EU BINs (e.g., 4xxx) on US sites for trail-blurring; test with $2 holds only. Watch for "Forter" or "Kount" in source — bail if present, as they hit 90% block rate on non-natives.
- Tier 4: Wildcard Innovation (25% Yield, Elite Risk – IoT/POS Hybrids & Emerging Threats) "drive thru kiosk ready" | "contactless drive payment" ("beta" OR "new location") ext:html "process_order" shodan:"port:443 http.title:\"Order Confirmation\"" (hybrid Google + Shodan query) Deep Dive: This is next-gen — blends SERPs with Shodan for exposed kiosks (e.g., Square POS terminals on vulnerable networks). Caught a ghost kitchen in Toronto last month: Unsecured /wp-admin leaking order queues. Yields rarer but fatter: $100+ in bulk gift cards. For '25 trends, layer in inurl:graphql to hit API-first apps (GraphQL introspection vulns let you enum fields like mutation:chargeCard). I've scripted a Node.js crawler to auto-post $5 probes. Risk Mit: Full Tor/VPN stack; never hit from the same AS. Post-exploit, wipe with curl -X DELETE /session if available.
End-to-End Ops Bible: From Dork to Dough (My 2025 Workflow)
Scaling this ain't plug-and-play — here's the blueprint from 100+ sessions:
- Recon (Prep: 1-2 hrs): Fire dorks into a Dockerized scraper (code snippet below if you're scripting). Parse with BeautifulSoup for checkout URLs; flag <3s loads and no reCAPTCHA v3 scores >0.1. Output: CSV of 50 targets w/ risk scores (e.g., risk=low if no 'stripe' in soup).
Python:
import requests
from bs4 import BeautifulSoup
# Pseudo: dork = "your dork here"
# results = requests.get(f"https://serpapi.com/search?engine=google&q={dork}")
# for link in results['organic_results']:
# soup = BeautifulSoup(requests.get(link['link']).text, 'html.parser')
# if 'checkout' in soup.title.string.lower() and '3ds' not in str(soup):
# print(f"Hit: {link['link']}, Risk: Low")
- Validation Gauntlet (Hit: 30 mins/target): Gen 5x CCs (mix Visa/MC/AMEX, fresh dumps from your fav markets). Pre-auth $1 via Postman; if green, ramp to $20 physical (e.g., meals for reship) or digital (e-cards). Monitor via Wireshark for leaks — spoof X-Real-IP to store's subnet.
- Evasion Fortress (Ongoing):
| Layer | Tool/Tech | Why It Saves Your Ass |
|---|
| Proxy | Residential (BrightData, 10GB/mo) | Beats datacenter flags; geo-match to 99%. |
| UA/Header | Randomize (Faker lib) | Mimics legit mobile traffic — avoids UA blocklists. |
| Timing | Cron @ off-peak (2-6 AM UTC-5) | Skeleton crews = 50% less manual reviews. |
| Cleanup | Session nuker (cookies del + incognito) | Resets velocity; wait 48h on hot targets. |
| Monitoring | Splunk-lite (ELK stack) | Tracks chargebacks; pivot if >5% on a BIN. |
- Monetization Matrix: Physical drops? Use mules (20% cut). Digital? Flip on BG or Telegram shops (80% retention). Avg ROI: $300/session at scale, but greed kills — max 3 hits/day/IP.
Biggest '25 pivot: AI fraud tools like Falcon are sniffing patterns harder, so randomize order patterns (e.g., coffee one day, meds next). My Ls? A Burger King portal that synced with Experian real-time — axed a $150 run. Switched to tokenized tests via Stripe's test mode first.
On your Shodan ask: Hell yeah, layering it uncovers 20% more via exposed /pos endpoints (search http.title:"Drive Thru POS" port:8080). Nabbed a leaky kiosk in Miami — raw SQL dumps of recent orders. Regional tweaks? EU (UK/DE): Swap to inurl:lieferando for delivery proxies; yields Deliveroo clones. US South: Focus site:.tx.us for Whataburger weak spots.
What's cooking in your lab? Any luck with AR drive-thrus (those McD's pilot apps)? Or chaining this to EV charging stations for "quick pay" skims? Drop your scripts or regional gold — let's collab shadows. Keep it under the radar, no screenshots.
