Skip to main content

Crawl telegra.ph for nude pictures and videos

Project description

nude crawler

Nude crawler crawls all pages on telegra.ph for today and N past days for specific words, checks number of nude, non-nude images, videos (not analysed) and reports pages which looks interesting (e.g. has more then 10 nude images, or has one video)

Ineffective intriguing warning

No matter how old you are, no matter how tolerant you are, no matter what your sexual orientation is, no matter what your favorite perversion is, no matter how big your sexual horizons are, with NudeCrawler you will find a lot of things that you will NOT like.

I wrote this warning because I have seen some shit. LITERALLY.

Please use it only for legal and ethical purposes. And it's 18+ surely.

Install

pip3 install nudecrawler

alternatively, install right from git repo:

pip3 install git+https://github.com/yaroslaff/nudecrawler

Launch Nude Crawler!

(I intentionally changed links, do not want to violate github policy)

$ nudecrawler sasha-grey
INTERESTING https://telegra.ph/sasha-grey-XXXXXXXX
  Nude: 0 non-nude: 0
  Total video: 1

INTERESTING https://telegra.ph/sasha-grey-XXXXX
  Nude: 9 non-nude: 6

INTERESTING https://telegra.ph/sasha-grey-XXXXX
  Nude: 9 non-nude: 6

INTERESTING https://telegra.ph/sasha-grey-XXXXX
  Nude: 6 non-nude: 3

Getting only interesting results

Nudecrawler uses evalidate to filter results with python expression (--expr). With -h help will list all avaliable variables, like: total_images nude_images nonnude_images new_nude_images new_nonnude_images new_total_images total_video. Default value: (total_images>5 and new_nude_images>0) or total_video>0.

Working with different nudity detectors

NudeCrawler can work with different nudity detectors and very easy to extend. Option -a/--all will disable detection totally, and it will report all pages.

Bult-in filter :nude based on nude.py, (python port of nude.js) is mostly good and used by default (and does not needs to install many dependecties as with keras/tensorflow detectors, which better to use as Docker images), but it's slower

There are two options to connect user filters, --detect-image SCRIPT and --detect-url SCRIPT, first one will call script and pass it filename of downloaded image to analyse, and second one will call script and pass it URL of image to analyse. Script should return with either 0 return code (image is SFW) or 1 (image is NSFW). Mnemonic: return code is number of interesting images.

if you will use /bin/true as script, it will detect all images as nude, and /bin/false will detect all images as non-nude.

Scripts are usually installed to /usr/local/bin and if it's in $PATH, you do not need to specify full path to script, nudecrawler will find it in $PATH.

detector: nsfw_api (recommended)

To use nsfw_api:

Start:

sudo docker run --rm --name nsfw-api -d -p 3000:3000 ghcr.io/arnidan/nsfw-api:latest

Use option --detect nsfwapi

This detector understands DETECTOR_VERBOSE, and special threshold for each of NSFW classes (porn, sexy, hentai), also, DETECTOR_THRESHOLD sets default threshold for all classes.

DETECTOR_VERBOSE=1 DETECTOR_THRESHOLD_HENTAI=0.9 bin/detect-image-nsfw-api.py /tmp/sketch-girl.jpg ; echo $?
Safe /tmp/sketch-girl.jpg: {'hentai': 0.57, 'drawing': 0.4, 'porn': 0.02, 'neutral': 0.01, 'sexy': 0.0}
0

detector: adult-image-detector

To use adult-image-detector:

sudo docker run --rm -d -p 9191:9191 --name aid --memory=1G opendating/adult-image-detector

And use option --detect aid

adult-image-detector works good and fast for me, but has memory leaking so needs more and more RAM. It's good for short-time run

detector: NudeNet

Installing NudeNet (little trick needed)

Using NudeNet does not requires docker, but you need to install pip3 install -U flask nudenet (consider using virtualenv, because nudenet has many dependencies). Also, NudeNet requires model in file ~/.NudeNet/classifier_model.onnx, if file is missing, NudeNet (unsuccessfully) tries to download file from https://github.com/notAI-tech/NudeNet/releases/download/v0/classifier_model.onnx but there is problem, github may display warning page instead of real .onnx file, so this page is downloaded (which is certainly wrong).

Right way workaround is simple - after you will install NudeNet download model manually (no wget!) and place it to ~/.NudeNet/

Or you can download from my temporary site: wget https://nudecrawler.netlify.app/classifier_model.onnx (But I cannot promise it will be there forever) and put it to ~/.NudeNet .

Using NudeNet with NudeCrawler

NudeNet filtering is implemented as client-server. Start server (PATH_TO/detect-server-nudenet.py) on other terminal (or screen/tmux) and add option --detect nudenet to NudeCrawler.

Writing your own detector

If you want to write your own detector, explore current detector scripts as example, but here is main rules:

  • Image URL or PATH passed as argv[1]
  • Return 0 if image is safe and boring, return 1 if image is interesting
  • Return 0 if there are any technical problems (timeout or 404)
  • Additional configuration could be specified via environment, NudeCrawler will pass environment to your script
  • NudeCrawler also sets env variables NUDECRAWLER_PAGE_URL and NUDECRAWLER_IMAGE_URL

Prefiltering

To speed-up processing, nudecrawler uses pre-filtering, HTTP HEAD request is performed for any image, and further processing is performed only if images passes basic check:

  • Image URL must return status 200
  • If server responds with Content-Length in response headers (telegra.ph uses Content-Length), it must be more then --minsize (minsize specified in Kb, and default value is 10Kb). This saves us from downloading/filtering icons.

Long-time run

Stop/Resume

When working with worklists an --stats file, current status is periodically saved to this file. If you need to resume it, just use command nudecrawler --resume PATH/TO/stats.json

Memory leaking in containers

You may check container memory usage with sudo docker stats or sudo docker stats --no-stream. Often containers consume more and more memory with time, leading to out-of-memory in the end. To prevent this problem use combination of --stop and --refresh like --stop 1000 --refresh bin/refresh-nsfw-api.sh this will call refresh script every 1000 images. Refresh script should stop current container and start it again. See source of refresh-nsfw-api.sh for example, it's very simple.

Benchmarking/test

Tested on same page, different technologies (default thresholds) gives different results. Page A: belle delphine from 16th Jan (64 lite sexy images, mostly underwear, nude breast on few) Page B: sasha grey from 18 Apr (16 images, 12 clearly nsfw, 4 are clearly safe )

filtering technology A time A nudes B time B nudes
:nude (bilt-in) 127s 63 34s 14 (false positives/negatives)
detect-image-nsfw_api (docker) 90s 49 23s 12
detect-image-aid (docker) 124s 10 28s 6 (false negatives)
detect-image-nudenet (scripts) 90s 57 24s 12

Working with wordlists

In simplest case (not so big wordlist), just use -w, like:

# verbose, no-filtering (report all pages), use wordlist
nudecrawler -v -a -w wordlist.txt

If you have very large wordlist, better to pre-check it with faster tool like bulk-http-check, it's much faster, doing simple check (we need only filter-out 200 vs 404 pages) millions of page per hour on smallest VPS server.

Convert wordlist to urllist

# only generate URLs 
nudecrawler -v -w wordlist.txt --urls > urls.txt

Verify it with bulk-http-check and get output file with this format:

https://telegra.ph/abazhurah-02-26 OK 404
https://telegra.ph/ab-03-01 OK 200
https://telegra.ph/aaronov-02-22 OK 404
https://telegra.ph/abazhurami-02-25 OK 404

Filter it, to leave only existing pages, and strip date from it:

grep "OK 200" .local/urls-status.log | cut -f 1 -d" "| sed 's/-[0-9]\+-[0-9]\+$//g' | sort | uniq > .local/urs.txt

List (urls.txt) will look like:

https://telegra.ph/
https://telegra.ph/a
https://telegra.ph/ab
https://telegra.ph/aba
https://telegra.ph/Abakan
....

This list (~300Kb, 11k urls) created from 1.5M words russian wordlist. There are only words which had at least one page with this title for last 10 days. So it has words 'Анжелика' or 'Анфиса' (beautiful woman names), but has no words 'Абажурами' or 'Абажуродержателем' (Because there are no pages with these titles on telegra.ph).

Now you can use this file as wordlist (nudecrawler will detect it's already base URL, and will only append date to URL).

Example usage:

Check one page (using built-in :nude filter):

nudecrawler -v --url1 https://telegra.ph/your-page-address 
nudecrawler -w urls.txt --nude 5 -d 30 -f 5 --stats .local/mystats.json  --log .local/nudecrawler.log 

process urls from urls.txt, report page if 5+ nude images (or 1 any video, default), nudity must be over 0.5 threshold, check from todays date to 30 days ago, append all found pages to .local/nudecrawler.log, save periodical statistics to .local/mystats.json

If crawler will see page Sasha-Grey-01-23-100, but Sasha-Grey-01-23-101 is 404 Not Found, it will try -102 and so on. It will stop only if 5 (-f) pages in a row will fail.

nudecrawler -v --detect-image bin/detect-image-nsfw-api.py -f 5 --total 10 --nude 3 -w urls.txt --stats .local/stats.json --log .local/urls.log --stop 1000 --refresh bin/refresh-nsfw-api.sh

Work verbosely (-v), use NSFW_API for resolving (and call refresh-nsfw-api.sh script to restart docker container every 1000 images).

Options

$ nudecrawler -h
usage: nudecrawler [-h] [-d DAYS] [--url1 URL] [-f FAILS] [--day MONTH DAY] [--expr EXPR] [--total N] [--max-errors N] [--min-content-length N] [-a] [--detect-image SCRIPT]
                   [--detect-url SCRIPT] [--detect METHOD] [--extensions [EXTENSIONS ...]] [--minsize MINSIZE] [--cache PATH] [-v] [--unbuffered] [--urls] [--log LOG] [-w WORDLIST]
                   [--stats STATS_FILE] [--resume STATS_FILE] [--stop NUM_IMAGES] [--refresh SCRIPT [ARG ...]]
                   [words ...]

Nudecrawler: Telegra.ph Spider 0.3.0
https://github.com/yaroslaff/nudecrawler

positional arguments:
  words

optional arguments:
  -h, --help            show this help message and exit
  -d DAYS, --days DAYS
  --url1 URL            process only one url
  -f FAILS, --fails FAILS
                        stop searching next pages with same words after N failures
  --day MONTH DAY       Current date (default is today) example: --day 12 31
  --expr EXPR, -e EXPR  Interesting if EXPR is True. def: '(total_images>5 and new_nude_images>0) or total_video>0'
                        Fields: total_images nude_images nonnude_images new_nude_images new_nonnude_images new_total_images total_video
  --total N             Boring if less then N total images (5)
  --max-errors N        Max allowed errors on page ()
  --min-content-length N
                        Interesting if N+ total images (5)

Image filtering options:
  -a, --all             do not detect, print all found pages
  --detect-image SCRIPT
                        explicitly use this script to detect nudity on image file
  --detect-url SCRIPT   explicitly use this script to detect nudity on image URL
  --detect METHOD       One of true, false, nudepy, aid, nsfwapi, nudenet
  --extensions [EXTENSIONS ...]
                        interesting extensions (with dot, like .jpg)
  --minsize MINSIZE     min size of image in Kb (10)
  --cache PATH          path to cache file (will create if missing)

Output options:
  -v, --verbose         verbose
  --unbuffered, -b      Use unbuffered stdout
  --urls                Do not detect, just generate and print URLs
  --log LOG             print all precious treasures to this logfile

list-related options:
  -w WORDLIST, --wordlist WORDLIST
                        wordlist (urllist) file
  --stats STATS_FILE    periodical statistics file
  --resume STATS_FILE   resume from STATS_FILE (other args are not needed)
  --stop NUM_IMAGES     stop (or --refresh) after N images processed (or little after)
  --refresh SCRIPT [ARG ...]
                        run this refresh script every --stop NUM_IMAGES images

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

nudecrawler-0.3.0.tar.gz (24.9 kB view details)

Uploaded Source

Built Distribution

nudecrawler-0.3.0-py3-none-any.whl (23.3 kB view details)

Uploaded Python 3

File details

Details for the file nudecrawler-0.3.0.tar.gz.

File metadata

  • Download URL: nudecrawler-0.3.0.tar.gz
  • Upload date:
  • Size: 24.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.2

File hashes

Hashes for nudecrawler-0.3.0.tar.gz
Algorithm Hash digest
SHA256 e547fb27473856fdaa5a90290fd075eaac0e1b672714867d64f70e2ab8546b64
MD5 67e79281c4dd8cb74cc77ee6e82ca7ca
BLAKE2b-256 176737901b92ff4f88016629ae39f8ce3576a8f8a9d7e9839e423f92328ae9f2

See more details on using hashes here.

File details

Details for the file nudecrawler-0.3.0-py3-none-any.whl.

File metadata

  • Download URL: nudecrawler-0.3.0-py3-none-any.whl
  • Upload date:
  • Size: 23.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.2

File hashes

Hashes for nudecrawler-0.3.0-py3-none-any.whl
Algorithm Hash digest
SHA256 30e49523acccbd6aaa6e29a68f2e3292944263e7638915853fcfaed598362566
MD5 481aa28542514b2816caee54d572343d
BLAKE2b-256 936c0bf178bc222b6b4f78660d8ba79b808b99ce8bbc6f2fcc8c47e3ccec970f

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page