Bot traffic: workontheweb.com

all sites · all domains · last 15 days

All sites · All Domains · Visit workontheweb.com

Who is really visiting workontheweb.com?

Between Oct 23 and Nov 6, workontheweb.com received 59,469 requests. About 99.4% came from automated software and about 0.3% look like real people.

That works out to about 112 human visitors, roughly 7 a day, who opened 145 pages between them. 33 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.

99.4%of requests from bots
112human visitors (estimate)
145pages opened by people
59,469total requests, 15 days

Where the requests came from

People 0.3%Named bots 10%Disguised bots 6.1%Scanners 83%Unclear 0.3%

Requests per day

PeopleNamed botsDisguised botsScannersUnclear
01,5003,0004,5006,000Oct 23Oct 25Oct 27Oct 29Oct 31Nov 2Nov 4Nov 6

Human visitors per day

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

06121824Oct 23Oct 25Oct 27Oct 29Oct 31Nov 2Nov 4Nov 6

The breakdown

SourceRequestsΣ 59,469ShareData sentBlockedby the serverWhat this means
Break-in scanners42,62072%69 MB24,744Probing for WordPress logins, password files and other common weak spots.
Scanners posing as browsers6,87712%29 MB33Other requests from an address also caught probing for weak spots.
Disguised scrapers2,8584.8%25 MB5Claims 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.
AI crawlers2,1563.6%3 MB132AI companies gathering pages or answering a user's question, and saying so.
Other named bots1,6122.7%5 MB39Any other software that identifies itself as a bot.
Search engines1,3332.2%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 tools7901.3%8 MB3Programs such as curl or Python, or anything with an unrecognizable name.
Calendar and feed apps7291.2%<1 MB0Software fetching a feed for someone who subscribed.
Unclear1870.3%<1 MB0Browser name, but fetched only an image or data file and no page. Could be either.
SEO and marketing tools1390.2%<1 MB72Commercial tools that sell data about websites.
Possibly people1300.2%<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 people290.0%<1 MB0Opened a page and also fetched its images or icons, at a human pace, from a non-cloud address.
No name given90.0%<1 MB0Requests that give no software name at all.

Named bots

Botas it names itselfTypeRequests
ClaudeBotAI crawlers438
GooglebotSearch engines372
PetalBotSearch engines316
OAI-SearchBotAI crawlers190
bingbotSearch engines166
ApplebotSearch engines130
DuckAssistBotOther named bots127
BytespiderAI crawlers125
Kimi-SearchBotOther named bots120
BaiduspiderSearch engines119
GPTBotAI crawlers119
KimiBotOther named bots117
CCBotAI crawlers116
GrokBotAI crawlers113
Meta-WebIndexerOther named bots112

What people opened

Pages opened by at least two different human visitors.

PageHuman visitors
/88
/videos/2

How people arrived

Referring siteHuman visitors
wordpressretreat.com56
www.google.com24
m.baidu.com20
www.baidu.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
34.44.0.0/161631
192.42.0.0/1611527
93.123.0.0/161051
102.129.0.0/16791
45.138.0.0/16674
183.207.0.0/16643
74.125.0.0/16603
66.249.0.0/16603

Day by day

DayHuman visitorsHuman pagesNamed botsrequestsDisguisedrequestsScannersrequestsUnclearrequestsAllrequestsBot share
Oct 2310132152445,081145,56799.5%
Oct 2422251692734,78255,25499.4%
Oct 25225282344,028134,80599.7%
Oct 26793312002,977103,52799.5%
Oct 2711142993532,635163,31799.1%
Oct 2810111591883,097163,47199.2%
Oct 2915171732401,559142,00398%
Oct 30457461553,10174,01599.7%
Oct 316111861953,39173,79599.4%
Nov 19148434263,541264,85399.1%
Nov 2335241795,265105,98299.8%
Nov 3686532064,189105,06799.6%
Nov 4466881922,144133,04499.3%
Nov 5123052142,076132,61199.4%
Nov 6451503581,631132,15899.1%

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.