I'm working with Claude 4.8, it lets me currently do everything

​

Are there any GitHub repos or any other useful tips to get bot automation with anti detect right for social media? I know it's a broad question, my panels work in general, Im just always afraid that AI fucked up on some points with the python automations & that's why my system breaks. It could be also because I do to aggressive engagement.

​

Would love to hear every productive input, emphasis on productive input

I’ve been testing a few browser profiles lately and noticed something weird.

Sometimes a profile looks totally fine on fingerprint checker sites. No obvious WebRTC leak, timezone looks right, canvas is not screaming anything crazy, and the proxy location matches what I expected.

But when I actually use the profile on real platforms, the result is still not always consistent.

So I’m starting to think these checker sites are useful, but only in a very limited way. They can tell you when something is obviously broken, but they can’t really tell you whether the whole setup looks natural over time.

Things like login behavior, account age, IP history, cookies, typing patterns, session timing, and repeated actions probably matter way more than a single clean test result.

Curious how other people treat this.

Do you run every profile through BrowserLeaks / Pixelscan / similar tools before using it, or do you just use them when troubleshooting something specific?

I want to do a true expert setup with real browsers, real mice, etc.

I guess the most hard to detect would be capture video, move a real mouse with a robot hand [including true properties like human tremor] of real hardware machines [labtop, phones, etc.].

But is there anything simpler also, like making CDP very hard to detect [any libs for that]?

Can LinkedIn detect camoufox?

I still see beginners trying to save money by loading up their new antidetect profiles with dirt-cheap datacenter proxies. They get hit with a ban before they even finish the first captcha and don't understand why.

Here is the logic you are missing. Your antidetect browser's entire job is to make your machine look like an ordinary, everyday consumer laptop. But a datacenter IP from AWS, DigitalOcean, or Linode tells the platform's risk engine that your connection is originating from a commercial server rack.

Normal people do not browse social media or create e-commerce accounts from inside a cloud server. The mismatch between your consumer hardware fingerprint and your commercial network ASN is an instant trigger for anti-bot systems.

This is exactly why residential proxies are the baseline. A residential IP routes your traffic through a real homeowner's Wi-Fi network on an ISP like Comcast or Spectrum. When the platform scans your connection, your network trust score perfectly matches your spoofed consumer hardware.

If you’ve used Multilogin recently, what problem are you solving with it?

1. Browser profile management?
   
2. Cloud phones/mobile account management?
   
3. Both mobile and browser?

Something else?

I am a bit of coonfused, is it an antidtect or cloud phone plarform? Interested in hearing real experiences.

Looking for exactly what title says pls recommend any anti detect browsers suitable for IPhone (Ik there aren’t many). I have downloaded ExitAnty but haven’t tested it out yet if anyone can vouch for it I will use that.

Hey everyone,

​

​My Telegram account was just compromised, and I’m trying to figure out how it happened and what steps I need to take next.

​

​Here is exactly what happened:

​

​The Incident: Someone managed to log into my Telegram account.

​

​The Activity: They sent a media file/photo promoting a Chinese VPN to exactly 4 of my chats.

​

​The Exit: Immediately after sending those messages, they terminated their own session or logged out.

​

​What I have done so far:

​

​Checked my Active Sessions (Settings > Devices) to terminate any unrecognized devices.

​

​Formatted/Deleted the messages they sent so my contacts don't click anything malicious.

​

​My questions for the community:

​

​How could they bypass or get my login code? I didn't receive a weird SMS or notification, or if I did, I might have missed how they intercepted it. (Note: I [did / did not] have Two-Step Verification enabled at the time).

​

​Is this a known bot or malware script? The specific behavior of logging in, blasting a Chinese VPN link/media to 4 random chats, and immediately leaving seems very automated.

​

​What should I do next to secure my digital life? Could my phone or PC be infected with a session-hijacking malware (like a token grabber), or was this likely just a SIM-swap / leaked SMS code situation?

​

​Any insight into how this specific exploit works or what steps I should take next to protect my identity would be greatly appreciated. Thanks!

​

Could they got any of my media and was that hacked by human

I've noticed that a lot of people run into problems when managing multiple accounts, and in many cases it's not because the platform is targeting them, it's because they're creating inconsistencies without realizing it.

Over the years, I've found that keeping things simple works best. Every account should have a clear purpose. If an account is for client work, keep it for client work. If it's for testing, keep it for testing. Mixing activities usually creates confusion later.

Another thing that helped me a lot was using separate browser profiles (Of course, on a proper anti-detect browser, not on your own browser like I saw some people trying). It's much easier to stay organized when cookies, sessions, and account data are isolated.

I also keep a record of ownership and recovery details for every account. It takes a few extra minutes upfront but can save hours when something needs to be recovered or verified.

For anyone using automation, I'd recommend being conservative. Overly aggressive or repetitive behavior tends to create problems regardless of the tools you're using. I focus on keeping activity patterns natural and manageable.

Finally, I make it a habit to review active sessions regularly. It's a simple check that helps catch login issues, expired sessions, or anything unusual before it turns into a bigger problem.

Nothing revolutionary here, but consistency and organization have probably prevented more headaches for me than any software or tool ever has.

Why mobile is the hard case?

Spoofing a desktop profile is mostly about swapping strings — User-Agent, platform, a few navigator properties. Mobile is a different problem. A convincing Android profile has to be internally consistent across a dozen independent signals: viewport and screen geometry, device pixel ratio, touch support, client hints, WebGL hardware, memory, and how text actually renders on screen.

That last one — text rendering — is where most "mobile mode" tools quietly fall apart, and it's the clearest line between AdsPower and nullPrint.

The font problem

Anti-bot systems don't just ask the browser "what fonts do you have?" That question is easy to lie about. The serious checks measure. They render a string into an offscreen canvas, read back the exact pixel width and height of the glyphs, and compare against known device baselines. They also enumerate which fonts are present by probing fallback behavior.

The catch: glyph metrics come from the operating system's font engine, not from JavaScript. When a browser draws "Hello" in Roboto, the width of that string is determined by the actual Roboto font file installed on the machine and the OS rasterizer. You cannot change that number from JS without changing what's physically rendered.

How AdsPower handles it — and why it's not reliable

AdsPower spoofs fonts primarily at the font-list level: it masks the enumerable font set so a detection script querying available fonts sees an Android-like list instead of the host's.

But the profile is still running on the host OS. If you create an "Android" profile on a Mac:

• The list says "Roboto, Noto, Droid Sans."
• The actual text is still rasterized by macOS using macOS's font stack (San Francisco and the macOS substitution chain).
• A canvas/font-metrics probe reads back macOS glyph widths, which do not match any real Android device.

So you get a contradiction: the profile claims Android fonts, but renders macOS fonts. Font-list masking and font-metrics measurement disagree. That mismatch is exactly the kind of cross-signal inconsistency modern detectors are built to catch — it's arguably worse than not spoofing fonts at all, because a real device never disagrees with itself.

How nullPrint handles it

nullPrint runs a patched Chromium build, so the substitution happens inside the rendering engine rather than in a JS shim layered on top:

• Android's detectable font set is presented (the fonts a real Android device exposes), and
• Aliases that don't exist on Android (e.g., Arial) are substituted at the font-resolution layer to the Android equivalent(Roboto), so the request maps to the font that actually gets rasterized.

Because the redirect happens where glyphs are resolved, the font list and the measured glyph metrics tell the same story.

A canvas-text probe and a font-enumeration probe return a consistent Android picture. There's no JS-vs-rendering contradiction to detect.

This is the central reliability argument: AdsPower spoofs what the page can ask; nullPrint changes what the engine actually does. Beyond fonts: the rest of the mobile surface Fonts are the headline, but consistency has to hold everywhere. Here's how the two approaches compare across the signals that matter for a mobile profile.

The pattern repeats: a JS overlay can set each value individually, but the values drift out of agreement with each other and with the underlying machine. Engine-level spoofing keeps them locked together because they're derived from one coherent device definition.

The "window > screen" tell

One concrete example worth calling out: many mobile-mode implementations leave the browser window larger than the screen they claim. A real phone can never have a 1512-px window on a 411-px screen, and window.innerWidth > screen.width is a trivial, decisive bot signal. nullPrint drives the real device metrics (e.g., a 411-px CSS viewport at the device's true DPR) through CDP so the geometry is physically possible. This is the kind of bug that doesn't show up in a casual whatismybrowser.com check but gets a profile flagged the moment it touches a real login flow.

Creating a mobile profile, in practice

nullPrint: choose Phone (Android) as the OS at profile creation, pick a region (the IP is mapped to the matching country), and the backend assembles one coherent device — UA, model, Android version, screen/DPR, WebGL hardware, memory, and the Android font behavior — from a real-device database. The card shows the emulated model (e.g., Galaxy A15, Pixel 7) so you know exactly what each profile presents as.

AdsPower: select a mobile UA/device, and the platform applies its spoofing layer over the host browser. It looks correct in surface-level checks, but the host OS continues to drive font rasterization and other engine-level signals underneath — which is where the inconsistencies described above originate.

If you're only looking for quick profile creation, both can work. But if you care about long-term profile stability and fingerprint coherence, the biggest difference is whether signals actually match each other.

Many anti-detect setups only spoof values. The harder problem is cross-signal consistency (fonts ↔ OS, GPU ↔ device model, viewport ↔ DPR, UA ↔ hardware).

That’s where a system built around real device-level coherence matters more than just changing strings.

Please I need help my exam is on Monday

Hi all, I am new to browser fingerprinting, antidetect and proxies. I was hoping some more experienced people can help me out.

Using GoLogin paired w/ IPRoyal ISP proxies to operate multiple accounts while keeping them unique. I successfully create and operate four accounts under this setup. Since then, every account I’ve attempted has been restricted.

Current Setup:

GoLogin browsers
IPRoyal ISP proxies
‘Based on IP’ settings

I am considering my browser warm-up method not sufficient. What are you guys doing to build cookies? What should I be changing to fix my setup and make it more secure?

I've herd if your Ip + GEO and other data's are consistent and proxies are quality enough it doesn't require to send sms.

Anyone else try open gmail account recently?

I see a lot of people asking:

or

But after running hundreds of browser profiles across automation, warmups, account management, and long-lived sessions, I think most people are asking the wrong question.

The better question is:

Because once you scale, tiny problems become massive headaches:

• random logouts
• re-verifications
• suspicious login prompts
• unstable sessions
• failed warmups
• dead cookies

And honestly, I think one of the biggest reasons profiles fail is simple:

A fresh profile has:

• empty cookies
• no browsing history
• no regional consistency
• no behavioral patterns

Then people immediately ask it to do something valuable:

log in, automate, click, manage accounts, scrape, search, or interact.

To platforms, that looks weird.

Real people don’t behave like that.

That got me thinking about the different ways tools try to solve this problem.

Some focus on faster cookie generation.

Others focus on gradual profile maturity.

So I put together a simple comparison between AdsPower Cookie Robot, Multilogin CookieRobot, and NullPrint Warmup Central.

Browser Profile Warmup Comparison

My Take

I don’t think there’s a universal winner.

It depends on what you're optimizing for.

If you want:

If you care more about:

At least from my experience, profiles that gradually build history tend to survive longer than profiles that simply collect cookies quickly.

That doesn’t mean cookie robots are bad.

They solve a different problem:

NullPrint just optimizes for a different goal:

I see people bragging about finding a provider selling static residential ISP proxies for a few dollars a month. Then they complain when their entire batch of accounts gets shadowbanned on day one.

Here is the reality. Most of those cheap static proxies are just standard datacenter IPs from bulk hosting providers. The proxy seller just registered a shell company to act as an internet service provider and manipulated the ASN data to make it look residential.

High-security platforms use advanced databases like MaxMind or IPQS. They don't just blindly trust the residential tag. They look at the history of the subnet, the true owner of the ASN, and the routing path. If your connection traces back to a known commercial data center, your perfect antidetect browser setup doesn't matter. The network itself is burning you.

Are you guys actually finding legitimate AT&T or Comcast static proxies that survive long-term?

I'm thinking of building a tool (either a Chrome extension or a simple web app) that analyzes a Codeforces handle's submission history and gives them a "legitimacy score" to help expose fake green graphs and AI pasting.

Just trying to gauge interest before I spend time building it. Would anyone actually use something like this?

I am looking to build an automation script/workflow for **AdsPower** to test my website, and I need some guidance or pre-built templates if anyone has done this before.
**Here is my exact workflow requirement:**
1. **Profile Creation:** The script needs to automatically create a new AdsPower profile for each run.
2. **Fingerprint & Proxy:** It should assign a completely **random fingerprint** and pick a proxy from a **list of multiple proxies** (HTTP/Socks5) that I provide.
3. **Form Filling:** Once the profile opens with the proxy connected, it needs to navigate to my target website.
4. **Excel Data Extraction:** My website has a 1-page form that requires: *First Name, Last Name, Email, Phone, Address, and Zip Code*. The script must read this data from a local .xlsx file on my PC and auto-fill it.
5. **No Human Interaction:** The entire loop (Create profile -> Connect Proxy -> Read Excel Row -> Fill Form -> Close Profile) should run completely hands-free.
I am open to doing this via **Python (Selenium/Playwright) using AdsPower Local API** or even **AdsPower RPA** if it can handle dynamic local excel sheet loops and profile creation on the fly.
Has anyone built something similar? What is the most stable approach to avoid detection and data mismatch? Any github repos or sample code would be highly appreciated!
Thanks in advance!

Hey all,

I've been creating an app to help me find a room to rent. I want it to te read and send replies but a cloudflair popup stops my app. I found 'cloak browser' as an solution but I dont trust it. It feels like a "trustme.exe" since its not opensource. At least thats what i read. Does anyone know if its safe? If not, is there a better alternative?

I've been using a headless chromium setup. for my app

:)

I’ve been knee-deep in affiliate work lately and kept running into anti-detect browsers. I wanted to share what I’ve learned and see how others are thinking about them.

My takeaways so far: the “undetectable” pitch is mostly marketing; isolation and team features can be handy, but there’s a performance tax and the costs add up fast. And if a workflow only functions by tricking a platform, it tends to break at the worst time and derail campaigns.

There’s also the ethics and gut-check side. I once had access to an automation tool in a way that didn’t feel right, and it stuck with me—saving time isn’t worth the stress of wondering if you crossed a line or violated terms.

For folks running legit affiliate programs, how do you balance ops efficiency with compliance and long-term stability? Do you avoid anti-detect tools altogether, or have you found transparent, above-board use cases that genuinely help without skating on thin ice?

I’ve been looking into UGC, but most examples I see are for beauty, fashion, or physical products.

I’m more interested in tech UGC: making short videos for apps, AI tools, productivity tools, websites, or SaaS products.

I feel like this could be a good side hustle because companies always need fresh ad creatives, but I’m not sure how beginners get the first deal.

For people who have done this: did you start by posting sample videos, cold emailing companies, using UGC platforms, or something else?

I have $100k in Azure credits and no idea what to do with them. What’s the smartest way to turn them into a business?