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Cloakbits - Headless web scraping with bypass for anti-bot WAFs

Hacker News

Cloakbits - Headless web scraping with bypass for anti-bot WAFs

There is a growing number of companies offering anti-bot protection SaaS to protect websites from scraping by automated bots based on Puppeteer/Selenium. Most of them rely on browser properties such as headers, javascript properties (window. , navigator. ), behavior analysis, to build device/user fingerprints and match it against a database of "whitelisted" fingerprints (typical user behavior/settings/device props etc). For the past few months, together with two other devs I have worked on a customized Puppeteer/Playwright scraping backend. It's essentially a drop-in replacement for default Chrome/FF binaries. We managed to successfully go through Coinbase, Amazon, Aliexpress login pages in headless mode without getting captcha, or any other verification. We are planning to roll out a beta version. If you are interested in getting beta access leave us details about your use case here: https://a90eq67iroz.typeform.com/to/FAkWnrtv The motivation for our project is that open-source solutions such as puppeteer-extra-stealth cover only a small portion of what popular anti-bot software such as Akamai Bot Manager or Imperva use to detect and ban emulated browsers.

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Launch Intel predictions

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Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
77%77% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
67%67% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: user, open · Missing: mac, agents, macos
52%52% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: month · Missing: mobile apps, ios, personal
40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
22%22% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: saas · Missing: arr, mrr, revenue
15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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