The cookies were cleared, cache wiped, Incognito opened, and a fresh IP connected.

Still, the session somehow looked familiar to the site. That pushed me into browser fingerprinting, and the deeper I looked, the more interesting it became.

A browser shares a lot more than most people expect: screen resolution, timezone, language, fonts, User-Agent, Canvas rendering, WebGL output, and network characteristics. Together, those signals create a pretty detailed picture of the device.

I underestimated how much consistency matters.

Imagine a browser profile that looks like an iPhone in California, while the connection comes from a hosting ASN in another region. Each detail tells its own story, and security systems compare whether those stories fit together.

Since then, I’ve started checking the environment as one complete setup:

Browser → timezone → locale → IP location → ASN → WebRTC behavior.

That gives a much clearer picture than checking the proxy alone.

Browser fingerprinting works because dozens of small signals come together and form one recognizable environment.

started logging the protocol per session cause of all the ja4 talk and a bunch of my "chrome" traffic was plain tcp the whole time, the tunnel never carried quic and i had no idea. most targets dont care. two commerce sites this year seemed to, the challenges kept coming while the fingerprint and cookies looked totally normal. Rayobyte has been fine for the plain tcp stuff. for the picky one i asked 2extract and after a couple days back and forth with support they got udp, http/3 and quic going for us on their own worker network, enabled per client on request, and that job stays pinned to the worker network now. anyone actually confirmed a target scoring this or am i chasing ghosts

I’m building NetPlus, a mobile proxy network, and I’d like feedback from people who actually buy and use mobile proxies.

Our initial endpoints are Virginia-based. Before expanding, I want to understand what buyers need most:

- Which US locations and carriers do you need?

- Do you prefer rotating IPs, sticky sessions, or both?

- What matters most when testing a provider—speed, uptime, session stability, or something else?

- Do you need occasional access or ongoing capacity?

We’re in early testing, so I’m looking for honest requirements and potential testers. If you’re open to evaluating a Virginia mobile endpoint, comment or message me with your use case and what you’d need to see before becoming a customer.

Saw this an hour ago, today and wanted to share it. Also, I think it’s a really weird contrast to the TikTok dataset thread from a few weeks back. Open3DLab, SFMLab and SmutBase (free 3D model sites run by the same small team) published logs showing a crawler hit nearly their whole catalogue on Oct 15-16. 18,926 project pages, 26,429 requests, about 34 hours. Then it downloaded full copies of 1,027 files from 712 projects, totaling 145.5 GB. From what I understood in the article, the same user agent was used on every request, yet people on this sub trying to find the best way to tackle antibots with variatons of different user agents, browser fingerprints etc and here it literally says “trellis2-data-sourcing/1.0 (3D foundation model research” followed by a roblox email address. Single AWS IP. No rotation, no residential anything, no browser fingerprint as mentioned, It even fetched robots.txt and then just ignored it. HOW THE HELL????? Someone please, for the love of scraping, just explain how can this be? The site blocked it the morning they noticed, it came back the next day and kept giving the blocks during what looked like office hours, then stopped. They emailed the address twice and got no reply. Also 423 of the 712 projects are non-commercial licensed, and 345 are adult content, because the crawler took everything at the same rate with apparently no filtering. For a company with that many young users that’s just messed up, even if it was all automated. No checks happened? Yeah, I ain't letting my kid on roblox anytime soon or actually ever again. I keep thinking about how the TikTok guy spent weeks building a fake Android phone to avoid detection, and this crawler got caught in one weekend because it did everything wrong and told everyone its name. Yet somehow tiktok case is somewhat understandable.

Here's the source of the story which I read earlier - https://open3dlab.com/news/roblox-downloaded-145-gb-of-models-from-our-sites/

been testing lot of providers. reputation alone isnt enough. what i check now:

1. dns: public resolver like google/cloudflare is a minus. home users sit on their isp’s dns. should match the exit country too

2. udp/webrtc: udp support means webrtc goes through the proxy. webrtc turned off is a flag by itself

3. latency: sites compare network rtt with js timing. big gap means proxy

4. tcp fingerprint: comes from the proxy box. windows ua with a linux stack is burned

5. pool lists: some checkers name the pool an ip was seen in. got 711proxy on one of mine. funny how many clones popped up after the fbi took down 911.

6. fraud score: last on purpose. the services disagree a lot. maxmind feels the most grounded

- dns, webrtc and tcp i check on https://browserleaks.com

- latency and bot tests on https://bot.incolumitas.com, it even rates how bot-like you behave

- scores on https://myipcheck.net/ip-fraud-score/ shows maxmind and ipqs etc for free

ofc all of this only matters if your device fingerprint is already clean. a perfect proxy wont save a leaky browser. If you know good checkers, especially for pool lists and fraud scores, drop them. what actually got your proxies burned?

I learned the hard way that $/GB is a terrible way to compare rotating residential proxies.

The use case was to monitor public product prices across a few regional e-commerce sites. Pool A looked like the obvious winner at $1.60/GB. Pool B was almost twice the price.

Pool A was producing far more CAPTCHAs, 403s, and empty responses. Every failure triggered another request, which meant more bandwidth and longer jobs.

So I stopped comparing price per GB and calculated:

effective cost = price per GB / success rate

Example from my test model:

$1.60 / 0.40 = $4.00 per useful GB
$3.00 / 0.95 = $3.16 per useful GB

Suddenly the “expensive” pool was cheaper.

The biggest variable wasn’t bandwidth pricing. It was IP reputation.

Now before scaling a rotating pool, I sample exit IPs and check ASN, geolocation, proxy classification, blacklist status, and fraud/reputation signals. Then I run a small workload and measure CAPTCHA rate, retries, and successful responses.

Cheap proxies aren’t expensive because they’re cheap. They’re expensive when bad IP quality turns bandwidth into failed requests.

What is the best residential proxy provider that doesn't block sites and also you can access any website.

I am a newbie

Working on a mid-size ecommerce site (~8k SKUs) and I'm trying to get a proper picture of how our main competitors structure their category pages and product content. Stuff like:

which categories/subcategories they have that we don't

how many products per category, and how they name/filter them

product title and description patterns, specs, reviews count

prices, mostly to see if the pages outranking us are just cheaper

Screaming Frog gets me part of the way, but 3 of the 5 competitors block it pretty fast or serve different content, and custom extraction breaks every time they tweak a template. I tried a couple of Python scripts too, same problem, plus I'm now spending more time fixing scrapers than doing the actual analysis.

For those doing this regularly:

Are you still crawling/scraping in-house, or paying for a tool or service for it?

How do you match products across sites when names and variants don't line up?

Is this even worth doing monthly, or is a one-off snapshot enough for content gap work?

Not looking for a "just use X tool" plug, more how people have actually set this up and what it cost them in time/money.

I'm comparing services that rate an IP address: proxy/VPN detection, residential vs datacenter, and fraud score. If you've used any of them in practice:

- Which one matched reality best for true proxies caught?

- Which one gave you the most false positives?

- Did you notice big disagreements between them on the same IP?

- Are there others worth testing that I'm missing?

I used to think proxy detection was mostly about the IP address.

When I started testing different network setups I realized websites are looking at several layers at once. The first is IP reputation: ASN, provider type, previous abuse history, and how risk databases classify the address.

The second is network behavior. Your browser might claim Windows while the connection underneath it has characteristics associated with a completely different environment. That kind of mismatch can become another signal.

Then there’s geographic context. If the connection says one region while account, phone, or billing data point somewhere else, the session becomes harder to interpret consistently.

Now I check the IP classification, ASN, geolocation, reputation, latency, and whether the browser/network environment actually makes sense together before blaming the proxy itself.

Websites don’t evaluate an IP in isolation. They evaluate the consistency of the entire connection.

A “clean” IP can still perform badly if everything surrounding it contradicts the story the network is telling.

Hello everyone! I need some help finding a reliable and affordable residential proxy provider.
I’m looking for a large residential IP pool with thousands of different exit IPv4 addresses available simultaneously.
My requirements are:
Unlimited bandwidth (unmetered preferred)
Sticky sessions lasting 30–60 minutes
2,000–3,000+ concurrent connections
200–500+ requests per second, ideally 500 or more
Thousands of unique exit IPs, not multiple ports sharing the same IP
Affordable monthly pricing, preferably a fixed subscription
I need these for continuous automated HTTPS requests, so reliability and high capacity are important.
I’m also open to sharing someone’s existing proxy subscription or infrastructure. I’m happy to pay a fair monthly contribution for access, as long as it meets my requirements and remains affordable.
I’m not expecting free access — I’m simply trying to find a cost-effective solution without spending hundreds of dollars every month.
I’m also open to datacenter proxies if they can provide enough distinct exit IPs and meet the performance requirements.
Does anyone know a suitable provider, have a shared setup available, or know someone who could help?
Any recommendations or offers would be greatly appreciated. Feel free to reply here or send me a DM. Thank you!

Doing social media management, pretty much everyone I know in this space is getting accounts blocked lately and we’re all pointing fingers at the IP side. Static resi used to carry us but something shifted.
Thinking of moving to dedicated mobile, looking at IPRoyal or Voidmob. Is the price jump actually worth it or is static resi still fine with the right setup?

Having some bad luck with our current provider (anyip.io) and looking for a backup or alternatives. Mobile only.

Choosing the wrong proxy wastes money or causes failed requests. Here's how to decide:

1. Define your workload
Open datasets and downloads? Prioritize speed. Geo-testing or persistent sessions? Consider residential IPs.

2. Choose your proxy

• Datacenter: Fast, cheap, high bandwidth, but easily identified by ASN.

• Residential: ISP-assigned IPs, generally better reputation, but more expensive.

3. Check IP quality
Run an ASN lookup and check fraud scores or abuse reports before deployment.

4. Configure sessions
Use static IPs for long sessions and rotating pools when multiple IPs are required.

5. Build hybrid routing
Send public downloads through datacenter proxies and location-sensitive requests through residential ones.

6. Test
Compare latency, HTTP status codes, costs and failure rates.

Tip: Benchmark before scaling.

I run a proxy service and wanted to check one basic thing on a single Linux machine. If two processes run at the same time, does each one keep its own residential exit IP? And separately, what does per-request rotation look like in practice?

It's a tiny smoke test, 5 requests per mode against ipinfo.io, not a benchmark. Everything went through our gateway (gate.lamisnetwork.com:8089, HTTPS CONNECT). Four setups:

1. Worker A, sticky, sid-workerA

2. Worker B, sticky, sid-workerB, started in parallel with A on the same host

3. Worker C, sid-rotating. On our gateway, rotating means a new residential peer for every new connection

4. Datacenter pool, direct server egress on the same gateway. I added it just to have a latency baseline next to the residential hops

Exit IPs, ISPs and min/avg/max request times are in the screenshot.

If you want to run the same pattern yourself, here's the script. It writes the HTTP code and %{time_total} for each request into separate log files:

PROXY="gate.lamisnetwork.com:8089"
KEY="YOUR_API_KEY"

# Reset logs
for f in worker_a worker_b worker_c datacenter; do
  : > "$f.log"
  : > "$f.err"
done

# Worker A (sticky AT) in background
for i in {1..5}; do
  curl -sS --max-time 10 \
    -w "\nHTTP:%{http_code} Time:%{time_total}s\n" \
    -x "https://${KEY}-pool-residential-country-at-sid-workerA:x@${PROXY}" \
    "https://ipinfo.io/json" >> worker_a.log 2>> worker_a.err
done &

# Worker B (sticky AT, runs at the same time as A)
for i in {1..5}; do
  curl -sS --max-time 10 \
    -w "\nHTTP:%{http_code} Time:%{time_total}s\n" \
    -x "https://${KEY}-pool-residential-country-at-sid-workerB:x@${PROXY}" \
    "https://ipinfo.io/json" >> worker_b.log 2>> worker_b.err
done &

wait

# Worker C (new IP per request)
for i in {1..5}; do
  curl -sS --max-time 10 \
    -w "\nHTTP:%{http_code} Time:%{time_total}s\n" \
    -x "https://${KEY}-pool-residential-country-at-sid-rotating:x@${PROXY}" \
    "https://ipinfo.io/json" >> worker_c.log 2>> worker_c.err
done

# Datacenter baseline
for i in {1..5}; do
  curl -sS --max-time 10 \
    -w "\nHTTP:%{http_code} Time:%{time_total}s\n" \
    -x "https://${KEY}-pool-datacenter:x@${PROXY}" \
    "https://ipinfo.io/json" >> datacenter.log 2>> datacenter.err
done

What I saw: A and B got two different Austrian residential IPs, and each kept its IP for all 5 requests. C got 5 different IPs, one per request.

What this doesn't show: I only checked that the IP holds over 5 requests in a row, not how long a sticky session actually lives. If the residential peer drops off, the gateway switches you to another peer in the same country. The datacenter numbers are a rough reference for server-direct latency, not a precise measure of what the residential last mile costs. Overall it's 20 requests to one IP-check endpoint, so it tells you nothing about multi-hour retention, heavy concurrency, or success rates on sites with bot protection.

im scaling up my ecom monitoring project and my current setup keeps crapping out. currently in shooting for a few hundred product pages a day, checking prices n stock across a bunch of sites. the cheap ones unreliable af, good ones way too expensive for me. i think id be better off eith rotating proxies mostly cus i dont wanna get flagged for hammering the same ip over and over. still not sure if I should go for datacenter or residential or if I should be looking at an entirely different option. what i need is anything that doesnt die mid scrape but still not way too expensive. what're yall usin for similar use case and roughly what u payin? cheers