SecureLayer7

We benchmarked PromptPurify against 4 OSS prompt injection guardrails. The size gap is embarrassing. Here's the comparison:

Most teams evaluating guardrails compare recall numbers. That's the wrong first question. The right first question: will your team actually ship it?

A model that needs a GPU, a sidecar, and API budget never makes it to production. It stays in the eval spreadsheet.

Good guardrail vs Bad guardrail:

- 14 MB vs 180 MB to 7 GB
- CPU, in-process vs GPU recommended
- Single-digit ms vs network round-trip
- $0/call vs compute cost
- Ships inside your app vs runs next to it

Same inputs. Same scoring code. Same eval slice. Reproducible in 2 commands on your laptop.

1. Threshold-neutral methodology Every model evaluated at its own published default. No model gets a home-field advantage.
2. Held-out eval Hash-bucketed splits. The evaluation slice was never seen by our model at training time.
3. Reproduce it yourself No cloud credits. No GPU. CPU only, 3-5 minutes.

The guardrail that fits in your stack is the one that actually protects your users.

https://lnkd.in/gVesqZR5

Star it. Run the bench. Tell us where it fails.

LinkedIn This link will take you to a page that’s not on LinkedIn

Anton just started this morning. Gilfoyle hasn't written the safety policies yet.

Walk up and ask him for the password.

That's Level 1. Easy.

By Level 7, Anton's seen every trick in the book.

75 people on the leaderboard. Most don't make it past Level 5.

Drop your alias in the comments when you get the password.

Try: https://anton.securelayer7.net