users.physics.ox.ac.uk/~lvovsky/B3/ contain assorted PDFs from between 2015 and 2019
Syllabus reads:
Professor in 2000s seems to be
But as of 2023 marked emeritus, so who took over?
Ewart is actually religious:
This dude is pure trouble for Oxford!
We've noticed that often when there is a hit range:
  • there is only one IP for each domain
  • there is a range of about 20-30 of those
and that this does not seem to be that common. Let's see if that is a reasonable fingerprint or not.
Note that although this is the most common case, we have found multiple hits that viewdns.info maps to the same IP.
First we create a table u (unique) that only have domains which are the only domain for an IP, let's see by how much that lowers the 191 M total unique domains:
time sqlite3 u.sqlite 'create table t (d text, i text)'
time sqlite3 av.sqlite -cmd "attach 'u.sqlite' as u" "insert into u.t select min(d) as d, min(i) as i from t where d not like '%.%.%' group by i having count(distinct d) = 1"
The not like '%.%.%' removes subdomains from the counts so that CGI comms are still included, and distinct in count(distinct is because we have multiple entries at different timestamps for some of the hits.
Let's start with the 208 subset to see how it goes:
time sqlite3 av.sqlite -cmd "attach 'u.sqlite' as u" "insert into u.t select min(d) as d, min(i) as i from t where i glob '208.*' and d not like '%.%.%' and (d like '%.com' or d like '%.net') group by i having count(distinct d) = 1"
OK, after we fixed bugs with the above we are down to 4 million lines with unique domain/IP pairs and which contains all of the original hits! Almost certainly more are to be found!
This data is so valuable that we've decided to upload it to: archive.org/details/2013-dns-census-a-novirt.csv Format:
8,chrisjmcgregor.com
11,80end.com
28,fine5.net
38,bestarabictv.com
49,xy005.com
50,cmsasoccer.com
80,museemontpellier.net
100,newtiger.com
108,lps-promptservice.com
111,bridesmaiddressesshow.com
The numbers of the first column are the IPs as a 32-bit integer representation, which is more useful to search for ranges in.
To make a histogram with the distribution of the single hostname IPs:
#!/usr/bin/env bash
bin=$((2**24))
sqlite3 2013-dns-census-a-novirt.sqlite -cmd '.mode csv' >2013-dns-census-a-novirt-hist.csv <<EOF
select i, sum(cnt) from (
  select floor(i/${bin}) as i,
         count(*) as cnt
    from t
    group by 1
  union
  select *, 0 as cnt from generate_series(0, 255)
)
group by i
EOF
gnuplot \
  -e 'set terminal svg size 1200, 800' \
  -e 'set output "2013-dns-census-a-novirt-hist.svg"' \
  -e 'set datafile separator ","' \
  -e 'set tics scale 0' \
  -e 'unset key' \
  -e 'set xrange[0:255]' \
  -e 'set title "Counts of IPs with a single hostname"' \
  -e 'set xlabel "IPv4 first byte"' \
  -e 'set ylabel "count"' \
  -e 'plot "2013-dns-census-a-novirt-hist.csv" using 1:2:1 with labels' \
;
Which gives the following useless noise, there is basically no pattern:
https://raw.githubusercontent.com/cirosantilli/media/master/cia-2010-covert-communication-websites/2013-dns-census-a-novirt-hist.svg
There are two keywords that are killers: "news" and "world" and their translations or closely related words. Everything else is hard. So a good start is:
grep -e news -e noticias -e nouvelles -e world -e global
iran + football:
  • iranfootballsource.com: the third hit for this area after the two given by Reuters! Epic.
3 easy hits with "noticias" (news in Portuguese or Spanish"), uncovering two brand new ip ranges:
  • 66.45.179.205 noticiasporjanua.com
  • 66.237.236.247 comunidaddenoticias.com
  • 204.176.38.143 noticiassofisticadas.com
Let's see some French "nouvelles/actualites" for those tumultuous Maghrebis:
  • 216.97.231.56 nouvelles-d-aujourdhuis.com
news + world:
  • 210.80.75.55 philippinenewsonline.net
news + global:
  • 204.176.39.115 globalprovincesnews.com
  • 212.209.74.105 globalbaseballnews.com
  • 212.209.79.40: hydradraco.com
OK, I've decided to do a complete Wayback Machine CDX scanning of news... Searching for .JAR or https.*cgi-bin.*\.cgi are killers, particularly the .jar hits, here's what came out:
  • 62.22.60.49 telecom-headlines.com
  • 62.22.61.206 worldnewsnetworking.com
  • 64.16.204.55 holein1news.com
  • 66.104.169.184 bcenews.com
  • 69.84.156.90 stickshiftnews.com
  • 74.116.72.236 techtopnews.com
  • 74.254.12.168 non-stop-news.net
  • 193.203.49.212 inews-today.com
  • 199.85.212.118 just-kidding-news.com
  • 207.210.250.132 aeronet-news.com
  • 212.4.18.129 sightseeingnews.com
  • 212.209.90.84 thenewseditor.com
  • 216.105.98.152 modernarabicnews.com
Wayback Machine CDX scanning of "world":
  • 66.104.173.186 myworldlymusic.com
"headline": only 140 matches in 2013-dns-census-a-novirt.csv and 3 hits out of 269 hits. Full inspection without CDX led to no new hits.
"today": only 3.5k matches in 2013-dns-census-a-novirt.csv and 12 hits out of 269 hits, TODO how many on those on 2013-dns-census-a-novirt? No new hits.
"world", "global", "international", and spanish/portuguese/French versions like "mondo", "mundo", "mondi": 15k matches in 2013-dns-census-a-novirt.csv. No new hits.
Let' see if there's anything in records/mx.xz.
mx.csv is 21GB.
They do have " in the files to escape commas so:
mx.py
import csv
import sys
writer = csv.writer(sys.stdout)
with open('mx.csv', 'r') as f:
    reader = csv.reader(f)
    for row in reader:
        writer.writerow([row[0], row[3]])
Would have been better with csvkit: stackoverflow.com/questions/36287982/bash-parse-csv-with-quotes-commas-and-newlines
then:
# uniq not amazing as there are often two or three slightly different records repeated on multiple timestamps, but down to 11 GB
python3 mx.py | uniq > mx-uniq.csv
sqlite3 mx.sqlite 'create table t(d text, m text)'
# 13 GB
time sqlite3 mx.sqlite ".import --csv --skip 1 'mx-uniq.csv' t"

# 41 GB
time sqlite3 mx.sqlite 'create index td on t(d)'
time sqlite3 mx.sqlite 'create index tm on t(m)'
time sqlite3 mx.sqlite 'create index tdm on t(d, m)'

# Remove dupes.
# Rows: 150m
time sqlite3 mx.sqlite <<EOF
delete from t
where rowid not in (
  select min(rowid)
  from t
  group by d, m
)
EOF

# 15 GB
time sqlite3 mx.sqlite vacuum
Let's see what the hits use:
awk -F, 'NR>1{ print $2 }' ../media/cia-2010-covert-communication-websites/hits.csv | xargs -I{} sqlite3 mx.sqlite "select distinct * from t where d = '{}'"
At around 267 total hits, only 84 have MX records, and from those that do, almost all of them have exactly:
smtp.secureserver.net
mailstore1.secureserver.net
with only three exceptions:
dailynewsandsports.com|dailynewsandsports.com
inews-today.com|mail.inews-today.com
just-kidding-news.com|just-kidding-news.com
We need to count out of the totals!
sqlite3 mx.sqlite "select count(*) from t where m = 'mailstore1.secureserver.net'"
which gives, ~18M, so nope, it is too much by itself...
Let's try to use that to reduce av.sqlite from 2013 DNS Census virtual host cleanup a bit further:
time sqlite3 mx.sqlite '.mode csv' "attach 'aiddcu.sqlite' as 'av'" '.load ./ip' "select ipi2s(av.t.i), av.t.d from av.t inner join t as mx on av.t.d = mx.d and mx.m = 'mailstore1.secureserver.net' order by av.t.i asc" > avm.csv
where avm stands for av with mx pruning. This leaves us with only ~500k entries left. With one more figerprint we could do a Wayback Machine CDX scanning scan.
Let's check that we still have most our hits in there:
grep -f <(awk -F, 'NR>1{print $2}' /home/ciro/bak/git/media/cia-2010-covert-communication-websites/hits.csv) avm.csv
At 267 hits we got 81, so all are still present.
secureserver is a hosting provider, we can see their blank page e.g. at: web.archive.org/web/20110128152204/http://emmano.com/. security.stackexchange.com/questions/12610/why-did-secureserver-net-godaddy-access-my-gmail-account/12616#12616 comments:
secureserver.net is the name GoDaddy use as the reverse DNS for IP addresses used for dedicated/virtual server hosting
dnshistory.org contains historical domain -> mappings.
We have not managed to extract much from this source, they don't have as much data on the range of interest.
But they do have some unique data at least, perhaps we should try them a bit more often, e.g. they were the only source we've seen so far that made the association: headlines2day.com -> 212.209.74.126 which places it in the more plausible globalbaseballnews.com IP range.
TODO can it do IP to domain? Or just domain to IP? Asked on their Discord: discord.com/channels/698151879166918727/968586102493552731/1124254204257632377. Their banner suggests that yes:
With our new look website you can now find other domains hosted on the same IP address, your website neighbours and more even quicker than before.
Owner replied, you can't:
At the moment you can only do this for current not historical records
This is a shame, reverse IP here could be quite valuable.
In principle, we could obtain this data from search engines, but Google doesn't track that entire website well, e.g. no hits for site:dnshistory.org "62.22.60.48" presumably due to heavy IP throttling.
Homepage dnshistory.org/ gives date starting in 2009:
Here at DNS History we have been crawling DNS records since 2009, our database currently contains over 1 billion domains and over 12 billion DNS records.
and it is true that they do have some hits from that useful era.
This could refer to several more specific courses, see the tagged articles for a list.
So far, no new domains have been found with Common Crawl, nor have any existing known domains been found to be present in Common Crawl. Our working theory is that Common Crawl never reached the domains How did Alexa find the domains?
Let's try and do something with Common Crawl.
Unfortunately there's no IP data apparently: github.com/commoncrawl/cc-index-table/issues/30, so let's focus on the URLs.
Hello world:
select * from "ccindex"."ccindex" limit 100;
Data scanned: 11.75 MB
Sample first output line:
#                            2
url_surtkey                  org,whwheelers)/robots.txt
url                          https://whwheelers.org/robots.txt
url_host_name                whwheelers.org
url_host_tld                 org
url_host_2nd_last_part       whwheelers
url_host_3rd_last_part
url_host_4th_last_part
url_host_5th_last_part
url_host_registry_suffix     org
url_host_registered_domain   whwheelers.org
url_host_private_suffix      org
url_host_private_domain      whwheelers.org
url_host_name_reversed
url_protocol                 https
url_port
url_path                     /robots.txt
url_query
fetch_time                   2021-06-22 16:36:50.000
fetch_status                 301
fetch_redirect               https://www.whwheelers.org/robots.txt
content_digest               3I42H3S6NNFQ2MSVX7XZKYAYSCX5QBYJ
content_mime_type            text/html
content_mime_detected        text/html
content_charset
content_languages
content_truncated
warc_filename                crawl-data/CC-MAIN-2021-25/segments/1623488519183.85/robotstxt/CC-MAIN-20210622155328-20210622185328-00312.warc.gz
warc_record_offset           1854030
warc_record_length           639
warc_segment                 1623488519183.85
crawl                        CC-MAIN-2021-25
subset                       robotstxt
So url_host_3rd_last_part might be a winner for CGI comms fingerprinting!
Naive one for one index:
select * from "ccindex"."ccindex" where url_host_registered_domain = 'conquermstoday.com' limit 100;
have no results... data scanned: 5.73 GB
Let's see if they have any of the domain hits. Let's also restrict by date to try and reduce the data scanned:
select * from "ccindex"."ccindex" where
  fetch_time < TIMESTAMP '2014-01-01 00:00:00' AND
  url_host_registered_domain IN (
   'activegaminginfo.com',
   'altworldnews.com',
   ...
   'topbillingsite.com',
   'worldwildlifeadventure.com'
 )
Humm, data scanned: 60.59 GB and no hits... weird.
Sanity check:
select * from "ccindex"."ccindex" WHERE
  crawl = 'CC-MAIN-2013-20' AND
  subset = 'warc' AND
  url_host_registered_domain IN (
   'google.com',
   'amazon.com'
 )
has a bunch of hits of course. Data scanned: 212.88 MB, WHERE crawl and subset are a must! Should have read the article first.
Let's widen a bit more:
select * from "ccindex"."ccindex" WHERE
  crawl IN (
    'CC-MAIN-2013-20',
    'CC-MAIN-2013-48',
    'CC-MAIN-2014-10'
  ) AND
  subset = 'warc' AND
  url_host_registered_domain IN (
    'activegaminginfo.com',
    'altworldnews.com',
    ...
    'worldnewsandent.com',
    'worldwildlifeadventure.com'
 )
Still nothing found... they don't seem to have any of the URLs of interest?
Notes/book: www-thphys.physics.ox.ac.uk/people/SteveSimon/QCM2022/QuantumMatter.pdf Marked as being for Oxford MMathPhys, so it appears that this is a 4th year course normally. TODO but where is it listed under the course list of MMapthPhys? mmathphys.physics.ox.ac.uk/course-schedule

Pinned article: Introduction to the OurBigBook Project

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