TrialShield: Drop-in Anti-Abuse and Fraud Detection for SaaS Trials

The problem I had with SaaS free trial abuse (and how I tried to solve it)

The cat-and-mouse game with trial abusers is exhausting. We dealt with this heavily last year when we realized a single competitor was burning through dozens of trial accounts just to scrape our feature set and copy our roadmap. What finally stopped the bleeding for us wasn't a single silver bullet, but a layered friction approach: **1. Payment Gating + BIN Blocking:** We made credit cards mandatory for the trial (even if it's $0 upfront). More importantly, we used Stripe Radar to block prepaid card BINs and set a custom rule to reject any card fingerprint that had already been used on our platform, regardless of the email address. **2. Device Fingerprinting:** IP limits are basically useless now because of cheap residential proxies. We implemented browser fingerprinting (looking at Canvas and WebGL hashes). Even if they clear cookies, use Incognito, or bounce through a VPN, their underlying device hardware signature usually gives them away. **3. Identity Friction (SSO):** For our higher-tier enterprise trials, we removed the standard email/password signup entirely and forced Microsoft/Google Workspace SSO. Scammers and competitors aren't going to burn aged, verified corporate identity accounts just to get 14 days of a tool. It's a brutal problem to solve natively because stitching together device hashing, payment velocity, and identity verification APIs is a massive engineering drain that takes focus away from the core product. Since you've been building in this specific space, I'm curious: which of those signals (device vs. network vs. payment) did you find had the highest false-positive rate for *legitimate* users? We found that aggressive IP velocity checks kept flagging remote workers sharing the same corporate WeWork Wi-Fi.

The cat-and-mouse game with trial abusers is exhausting. We dealt with this heavily last year when we realized a single competitor was burning through dozens of trial accounts just to scrape our feature set and copy our roadmap. What finally stopped the bleeding for us wasn't a single silver bullet, but a layered friction approach: **1. Payment Gating + BIN Blocking:** We made credit cards mandatory for the trial (even if it's $0 upfront). More importantly, we used Stripe Radar to block prepaid card BINs and set a custom rule to reject any card fingerprint that had already been used on our platform, regardless of the email address. **2. Device Fingerprinting:** IP limits are basically useless now because of cheap residential proxies. We implemented browser fingerprinting (looking at Canvas and WebGL hashes). Even if they clear cookies, use Incognito, or bounce through a VPN, their underlying device hardware signature usually gives them away. **3. Identity Friction (SSO):** For our higher-tier enterprise trials, we removed the standard email/password signup entirely and forced Microsoft/Google Workspace SSO. Scammers and competitors aren't going to burn aged, verified corporate identity accounts just to get 14 days of a tool. It's a brutal problem to solve natively because stitching together device hashing, payment velocity, and identity verification APIs is a massive engineering drain that takes focus away from the core product. Since you've been building in this specific space, I'm curious: which of those signals (device vs. network vs. payment) did you find had the highest false-positive rate for *legitimate* users? We found that aggressive IP velocity checks kept flagging remote workers sharing the same corporate WeWork Wi-Fi.