cport1
-Supports XLIFF 1.2, XLIFF 2.0, and JSON (flat + nested)
-Handles ICU MessageFormat plurals with CLDR rules for 20+ languages
-Commits translated files back to your repo automatically
-Works with Anthropic Claude, OpenAI, or self-hosted Ollama
Addressing a few specific ones:
PoW CPU cost: Difficulty is adaptive — 4 for residential IPs, 6+ for datacenter. On modern hardware that's ~200-800ms. For 1M users/day that's ~55-220 CPU-hours total, distributed across clients. It's comparable to what Cloudflare Turnstile does.
Keyboard-only users: Already handled. If keyEvents >= 2 and totalPoints === 0 (tabbed + Enter/Space), all mouse-based detections are skipped. No false positives on keyboard users.
"Can be recorded/replayed": signals are SHA-256 hashed and bound into the PoW input before solving. You can't solve PoW first then attach recorded signals... the hash won't match. Replaying old signal sets also fails because each challenge has a unique nonce.
Micro-tremor at 125Hz: Fair point... low polling rate mice produce less granular data. It's weighted low and only contributes when data is available. Not a gatekeeper.CDP userGesture: true: Good catch. We detect CDP-specific artifacts (Runtime.evaluate residue, protocol binding flags), but you're right that a custom Chromium build sidesteps this entirely.
The honest answer: a sufficiently motivated attacker with a custom Chromium build can beat this. The goal is to make that cost high enough that it's cheaper to just solve the CAPTCHA legitimately or move to an easier target. Same tradeoff Cloudflare makes, but open source and privacy first.
Where I think the real gap is: server-side signals (IP reputation, TLS fingerprinting, rate patterns) and that's really what our paid bot detection is for. https://webdecoy.com
FCaptcha – A modern CAPTCHA system designed to detect everything
Show HN: An Internationalization GitHub Action to Replace Crowdin with LLMs
https://github.com/i18n-actions/ai-i18n
I built an open-source GitHub Action that translates i18n files using LLMs, designed as a drop-in replacement for Lokalise, Phrase, and Crowdin.The problem: TMS platforms charge per-word and per-seat, and their machine translation lacks product context. A typical SaaS with 500 strings across 9 languages costs $200-500/month.How it works: - Extracts strings from your codebase (XLIFF, JSON, PO,...
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