Bot traffic: auditionmodel.com

all sites · all domains · last 15 days

All sites · All Domains · Visit auditionmodel.com

Who is really visiting auditionmodel.com?

Between Oct 23 and Nov 6, auditionmodel.com received 62,718 requests. About 99.6% came from automated software and about 0.1% look like real people.

That works out to about 40 human visitors, roughly 3 a day, who opened 70 pages between them. 26 of them read more than one page.

The biggest source is scanners hunting for security holes. They try the same list of common weak spots on every site they find.

Bottom line: the hit counts on the All Domains worksheet are almost entirely bots. Use the human visitor figure here to judge this site's real audience.

99.6%of requests from bots
40human visitors (estimate)
70pages opened by people
62,718total requests, 15 days

Where the requests came from

People 0.1%Named bots 5.5%Disguised bots 5.2%Scanners 89%Unclear 0.3%

Requests per day

PeopleNamed botsDisguised botsScannersUnclear
02,0004,0006,0008,000Oct 23Oct 25Oct 27Oct 29Oct 31Nov 2Nov 4Nov 6

Human visitors per day

Same days, people only, on their own scale so they are visible.

02468Oct 23Oct 25Oct 27Oct 29Oct 31Nov 2Nov 4Nov 6

The breakdown

SourceRequestsΣ 62,718ShareData sentBlockedby the serverWhat this means
Break-in scanners45,40372%75 MB23,182Probing for WordPress logins, password files and other common weak spots.
Scanners posing as browsers10,30016%46 MB47Other requests from an address also caught probing for weak spots.
Disguised scrapers2,1873.5%17 MB6Claims to be a normal browser but only downloads pages, never the images or icons a real browser fetches, reads many pages without ever clicking a link, or runs from a cloud provider.
Other named bots1,1291.8%5 MB26Any other software that identifies itself as a bot.
AI crawlers1,1281.8%2 MB98AI companies gathering pages or answering a user's question, and saying so.
Search engines1,1141.8%5 MB15Crawlers that say who they are, such as Google, Bing, Apple and Amazon. Usually welcome: this is how people find the site.
Scripts and tools1,0861.7%3 MB8Programs such as curl or Python, or anything with an unrecognizable name.
Unclear1660.3%<1 MB0Browser name, but fetched only an image or data file and no page. Could be either.
SEO and marketing tools1080.2%<1 MB64Commercial tools that sell data about websites.
Possibly people480.1%<1 MB0Read 1 to 3 pages, arrived from a search engine or social link, no icons fetched. Referrers can be faked, so treat these as maybe.
Likely people430.1%<1 MB0Opened a page and also fetched its images or icons, at a human pace, from a non-cloud address.
No name given60.0%<1 MB0Requests that give no software name at all.

Named bots

Botas it names itselfTypeRequests
GooglebotSearch engines415
PetalBotSearch engines305
ClaudeBotAI crawlers264
OAI-SearchBotAI crawlers148
bingbotSearch engines131
pathscanOther named bots92
meta-webindexerOther named bots74
GPTBotAI crawlers70
ApplebotSearch engines58
QlyzeBotOther named bots56
BytespiderAI crawlers55
ChatGPT-UserAI crawlers55
DeepSeekBotAI crawlers55
SemrushBotSEO and marketing tools54
cohere-aiAI crawlers53

What people opened

Pages opened by at least two different human visitors.

PageHuman visitors
/21
/videos/4

How people arrived

Referring siteHuman visitors
m.baidu.com20
www.google.com5
yandex.com.tr2
duckduckgo.com1
www.bing.com1

Where disguised bots operate from

Address blocks, not individual addresses. A heavily used block with many addresses suggests one operator rotating through them.

Address blockRequestsAddresses used
66.249.0.0/161383
192.42.0.0/169825
45.156.0.0/166647
102.129.0.0/16581
43.157.0.0/165225
66.190.0.0/16351
43.130.0.0/163215
43.165.0.0/163012

Day by day

DayHuman visitorsHuman pagesNamed botsrequestsDisguisedrequestsScannersrequestsUnclearrequestsAllrequestsBot share
Oct 23121081892,50932,81199.8%
Oct 24571261793,478133,80499.4%
Oct 25005501526,300137,01599.8%
Oct 26243971454,97595,53099.8%
Oct 27241232572,664103,05899.5%
Oct 28221351474,329114,62499.7%
Oct 2935731962,15492,43899.4%
Oct 3012861684,839155,11199.6%
Oct 31581071522,56482,84499.3%
Nov 1577221,0505,731287,53999.5%
Nov 2352481965,80476,26399.8%
Nov 3351521054,231114,50599.6%
Nov 4342141241,532161,89099%
Nov 5462691442,35482,78399.4%
Nov 639169752,23952,50399.2%

How this was measured

Every request in the server log was sorted by what it did, not only what it claimed to be. Bots that name themselves are counted as named. Anything claiming to be a browser had to act like one: open a page, fetch its images or icons, move at human speed, and come from outside the big cloud providers. These are estimates. A careful bot can pass the test, and a person with images blocked or a cached icon can fail it, so read the human figures as a good approximation, not an exact count. One person using two devices counts as two visitors. Google Analytics-style tools would show different numbers because most bots never run their script. Logs are kept for 15 days.

Built 2026-11-06 22:43 UTC from 15 log files.