@SentinelGateway 13ms overhead is impressive for a gateway. Most of the Python-based wrappers I’ve tested add way more latency than that once you turn on logging. Is that 13ms benchmark consistent even with full Postgres logging enabled?
We spent the last few months building Sentinel Gateway because we were tired of the "Cloud Proxy" tax. Most AI gateways force your sensitive data through their servers just to give you basic logging and routing. That shouldn't be the trade-off for enterprise teams.
@AsymmetricEdgex Thank you so much bro, I’ve literally tripled my account in the last month! You are incredible at what you do and educate us so much!! 🙏🏻
We’ve now scored 350,000+ IPs through CandycornDB.
After combing through that much traffic, some patterns jump out—and others catch even experienced teams off guard.
Let’s talk about what we’ve learned so far 🧵
We just crossed 350,000 IPs scored for fraud risk at CandycornDB.
Some patterns are obvious. Others genuinely surprised us.
From ASN abuse clusters to residential IP hijacking, here’s what we’ve learned so far:
🔗 https://t.co/OGNHl3AtQ4
#fraud#netsec#cybersecurity
Still using MaxMind for IP data?
Here's why teams are switching to real-time IP risk scoring, subnet behavior analysis, and fewer false positives.
CandycornDB vs MaxMind: Full breakdown 👇
🔗 https://t.co/UMZCcpqPpE
#fraud#cybersecurity#api#riskintel
🚀 We just launched CandycornDB on Product Hunt!
Real-time IP intelligence for fraud & security teams:
✅ VPN/proxy detection
✅ ASN & subnet risk scoring
✅ Fast API for real-world threats
Would love your support + feedback👇
🔗 https://t.co/4F58vDH4pK
#fraud#cybersecurity
Most fraud platforms rely on IP blocklists and GeoIP hacks. We’re going deeper:
-ASN behavior modeling
-Subnet clustering
-Active IP scanning
CandycornDB isn’t a database. It’s a threat radar.
#cybersecurity#fraud#infosec
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