Notably, the password is hardcoded and its hash is stored in the JavaScript itself. The result is then submitted back via a POST request to /cgi-bin/goal.cgi.
TODO: how is the SHA calculated? Appears to be manual.
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.
AlphaGo Zero by Ciro Santilli 40 Updated 2025-07-16
Figure 1.
AlphaGo Zero cheat sheet by David Foster (2017)
Source.
SQL contiguous ranges by Ciro Santilli 40 Updated 2025-07-16
stackoverflow.com/questions/17046204/how-to-find-the-boundaries-of-groups-of-contiguous-sequential-numbers/17046749#17046749 just works, even in SQLite which supports all quoting types known to man including [] for compatibility with insane RDBMSs!
Here's a slightly saner version:
rm -f tmp.sqlite
sqlite3 tmp.sqlite "create table mytable (id integer primary key autoincrement, number integer, status integer)"
sqlite3 tmp.sqlite <<EOF
insert into mytable(number, status) values
  (100,0),
  (101,0),
  (102,0),
  (103,0),
  (104,1),
  (105,1),
  (106,0),
  (107,0),
  (1014,0),
  (1015,0),
  (1016,1),
  (1017,0)
EOF
sqlite3 tmp.sqlite <<EOF
SELECT
  MIN(id) AS "id",
  MIN(number) AS "from",
  MAX(number) AS "to"
FROM (
  SELECT ROW_NUMBER() OVER (ORDER BY number) - number AS grp, id, number
  FROM mytable
  WHERE status = 0
)
GROUP BY grp
ORDER BY MIN(number)
EOF
output:
1|100|103
7|106|107
9|1014|1015
12|1017|1017
To get only groups of length greater than 1:
sqlite3 tmp.sqlite <<EOF
SELECT "id", "from", "to", "to" - "from" + 1 as "len" FROM (
  SELECT
    MIN("id") AS "id",
    MIN(number) AS "from",
    MAX(number) AS "to"
  FROM (
    SELECT ROW_NUMBER() OVER (ORDER BY "number") - "number" AS "grp", "id", "number"
    FROM "mytable"
    WHERE "status" = 0
  )
  GROUP BY "grp"
  ORDER BY MIN("number")
) WHERE "len" > 1
EOF
Output:
1|100|103|4
7|106|107|2
9|1014|1015|2
SQL window RANGE by Ciro Santilli 40 Updated 2025-07-16
rm -f tmp.sqlite
sqlite3 tmp.sqlite "create table t (id integer, val integer)"
sqlite3 tmp.sqlite <<EOF
insert into t values
  (0, 0),
  (1, 5),
  (2, 10),
  (3, 14),
  (4, 15),
  (5, 16),
  (6, 20),
  (7, 25),
  (8, 29),
  (9, 30),
  (10, 30),
  (11, 31),
  (12, 35),
  (13, 40)
EOF
Show how many neighbours each column has with val between val - 2 and val + 2 inclusive:
sqlite3 tmp.sqlite <<EOF
SELECT id, val, COUNT(*) OVER (
  ORDER BY val RANGE BETWEEN 2 PRECEDING AND 2 FOLLOWING
) FROM t;
EOF
Output:
0|0|1
1|5|1
2|10|1
3|14|3
4|15|3
5|16|3
6|20|1
7|25|1
8|29|4
9|30|4
10|30|4
11|31|4
12|35|1
13|40|1
val - 1 and val + 1 inclusive instead:
sqlite3 tmp.sqlite <<EOF
SELECT id, val, COUNT(*) OVER (
  ORDER BY val RANGE BETWEEN 1 PRECEDING AND 1 FOLLOWING
) FROM t;
EOF
Output:
0|0|1
1|5|1
2|10|1
3|14|2
4|15|3
5|16|2
6|20|1
7|25|1
8|29|3
9|30|4
10|30|4
11|31|3
12|35|1
13|40|1
There seems to be no analogue to HAVING for window functions, so we can just settle for a subquery for once, e.g.:
sqlite3 tmp.sqlite <<EOF
SELECT * FROM (
  SELECT id, val, COUNT(*) OVER (
    ORDER BY val RANGE BETWEEN 1 PRECEDING AND 1 FOLLOWING
  ) as c FROM t
) WHERE c > 2
EOF
which outputs:
4|15|3
8|29|3
9|30|4
10|30|4
11|31|3
ROW_NUMBER by Ciro Santilli 40 Updated 2025-07-16
sqlite3 ':memory:'  'WITH t (i) AS (VALUES (-1), (-1), (-2)) SELECT *, row_number() over () FROM t'
Possible output:
-1|1
-1|2
-2|3
Gives them unique IDs.
With a partition by:
sqlite3 ':memory:'  'WITH t (i) AS (VALUES (-1), (-1), (-2)) SELECT *, row_number() over ( partition by i ) FROM t'
possible output:
-2|1
-1|1
-1|2
Fish by Ciro Santilli 40 Updated 2025-07-16
This paraphyletic subgroup is easy to form the "acquatic only" (fishes) vs "things that come out of water" (tetrapods). Though mudfishes make that distinction harder.
Which kind of makes sense, why would you want for limbs unless you are going to stay out of water!
torchvision ResNet by Ciro Santilli 40 Updated 2026-08-21
That example uses a ResNet pre-trained on the COCO dataset to do some inference, tested on Ubuntu 22.10:
cd python/pytorch
wget -O resnet_demo_in.jpg https://upload.wikimedia.org/wikipedia/commons/thumb/6/60/Rooster_portrait2.jpg/330px-Rooster_portrait2.jpg
./resnet_demo.py resnet_demo_in.jpg resnet_demo_out.jpg
This first downloads the model, which is currently 167 MB.
We know it is COCO because of the docs: pytorch.org/vision/0.13/models/generated/torchvision.models.detection.fasterrcnn_resnet50_fpn_v2.html which explains that
FasterRCNN_ResNet50_FPN_V2_Weights.DEFAULT
is an alias for:
FasterRCNN_ResNet50_FPN_V2_Weights.COCO_V1
The runtime is relatively slow on P51, about 4.7s.
After it finishes, the program prints the recognized classes:
['bird', 'banana']
so we get the expected bird, but also the more intriguing banana.
By looking at the output image with bounding boxes, we understand where the banana came from!
Figure 1.
python/pytorch/resnet_demo_in.jpg
. Source.
Figure 2.
python/pytorch/resnet_demo_out.jpg
. The beak was of course a banana, not a beak!

Pinned article: Introduction to the OurBigBook Project

Welcome to the OurBigBook Project! Our goal is to create the perfect publishing platform for STEM subjects, and get university-level students to write the best free STEM tutorials ever.
Everyone is welcome to create an account and play with the site: ourbigbook.com/go/register. We belive that students themselves can write amazing tutorials, but teachers are welcome too. You can write about anything you want, it doesn't have to be STEM or even educational. Silly test content is very welcome and you won't be penalized in any way. Just keep it legal!
We have two killer features:
  1. topics: topics group articles by different users with the same title, e.g. here is the topic for the "Fundamental Theorem of Calculus" ourbigbook.com/go/topic/fundamental-theorem-of-calculus
    Articles of different users are sorted by upvote within each article page. This feature is a bit like:
    • a Wikipedia where each user can have their own version of each article
    • a Q&A website like Stack Overflow, where multiple people can give their views on a given topic, and the best ones are sorted by upvote. Except you don't need to wait for someone to ask first, and any topic goes, no matter how narrow or broad
    This feature makes it possible for readers to find better explanations of any topic created by other writers. And it allows writers to create an explanation in a place that readers might actually find it.
    Figure 1.
    Screenshot of the "Derivative" topic page
    . View it live at: ourbigbook.com/go/topic/derivative
  2. local editing: you can store all your personal knowledge base content locally in a plaintext markup format that can be edited locally and published either:
    This way you can be sure that even if OurBigBook.com were to go down one day (which we have no plans to do as it is quite cheap to host!), your content will still be perfectly readable as a static site.
    Figure 2.
    You can publish local OurBigBook lightweight markup files to either https://OurBigBook.com or as a static website
    .
    Figure 3.
    Visual Studio Code extension installation
    .
    Figure 4.
    Visual Studio Code extension tree navigation
    .
    Figure 5.
    Web editor
    . You can also edit articles on the Web editor without installing anything locally.
    Video 3.
    Edit locally and publish demo
    . Source. This shows editing OurBigBook Markup and publishing it using the Visual Studio Code extension.
    Video 4.
    OurBigBook Visual Studio Code extension editing and navigation demo
    . Source.
  3. https://raw.githubusercontent.com/ourbigbook/ourbigbook-media/master/feature/x/hilbert-space-arrow.png
  4. Infinitely deep tables of contents:
    Figure 6.
    Dynamic article tree with infinitely deep table of contents
    .
    Descendant pages can also show up as toplevel e.g.: ourbigbook.com/cirosantilli/chordate-subclade
All our software is open source and hosted at: github.com/ourbigbook/ourbigbook
Further documentation can be found at: docs.ourbigbook.com
Feel free to reach our to us for any help or suggestions: docs.ourbigbook.com/#contact