For those curious, here’s the NYTimes article where they report on the CSAM in the publicly-released files: https://www.nytimes.com/2026/02/01/us/nude-photos-epstein-files.html (behind paywall.)

NYTimes says that they discovered the CSAM on Friday and notified the DOJ on Saturday, and the DOJ was diligent in removing the files NYTimes had flagged.

NYTimes does not say that the material is in Dataset 9 specifically, but we observed that the DOJ was removing files from Dataset 9 on Saturday and not other datasets, so the server behavior would be consistent with CSAM in Dataset 9.

The site epsteinfilez.com claims to have the full Dataset 9. Can’t find a way to download it directly from them, since the site is only set up for searching. Perhaps if we asked nicely?

DOJ Just Removed Epstein Flight Log + Contact book in the last 30 minutes

MIRRORS:

This should be the flight log: https://epsteinfilez.com/?doc=f2f8c7628ddc9cbc1cf6a7532b847ae45eec1165cb400fccea19213982956d3d.pdf&p=1

and

https://epsteinfilez.com/?doc=bccc4a7953c0834228a422f1c3fede4d361dc8240c191d2e2b4616259ccdb4e9.pdf&p=1

and this is the contact book: https://epsteinfilez.com/?doc=b395c578ed9394206eaae4f724f99b094d81a5fce45006b247150433b38016c6.pdf&p=1

I’m not sure if it is useful to anyone, but the partial 9 zip from the DOJ website does contain the eDiscovery index files. VOL00009.DAT and VOL00009.OPT which are conveniently at the very start of the zip file. They are text files and it’s easy to parse out what files they thought were included in the massive zip file… IDK if you have one from zero hour, but I have the first few GB from the one the CDN occasionally spits out saved if anyone wants them so see what files may be missing from the “index”

just advising you that there is confirmed csam in dataset9-more-complete.tar.zst and probably the other partial dataset9s

Is there any grunt work that needs to be done? I would like to help out but I’m not sure how to make sure my work isn’t redundant. I mean like looking through individual files etc. Is there an organized effort to comb through everything?

I’ve been working on a structured inventory of the datasets with a slightly different angle: rather than maximizing scrape coverage, I’m focusing on understanding what’s present vs. what appears to be structurally missing based on filename patterns, numeric continuity, file sizes, and anchor adjacency.

For Dataset 9 specifically, collapsing hundreds of thousands of files down into a small number of high-confidence “missing blocks” has been useful for auditing completeness once large merged sets (like yours) exist. The goal isn’t to assume missing content, but to identify ranges where the structure strongly suggests attachments or exhibits likely existed.

If anyone else here is doing similar inventory or diff work, I’d be interested in comparing methodology and sanity-checking assumptions. No requests for files (yet) Just notes on structure and verification

Bro is about to be deported by ICE

I am seeding sets 1-8, 10-12, and the larger set 9. Seedbox is outside the US and has a very fast connection.

I will keep an eye on this post for other sets. 👍

deleted by creator

Thx for posting, seed if you can ppl.

Funny how a rag-tag ad-hoc group can seed data so much better than the DOJ. Beautiful to see in action.

Heads up that the DOJ site is a tar pit, it’s going to return 50 files on the page regardless of the page number your on seems like somewhere between 2k-5k pages it just wraps around right now.

Testing page 2000... ✓ 50 new files (out of 50)
Testing page 5000... ○ 0 new files - all duplicates
Testing page 10000... ○ 0 new files - all duplicates
Testing page 20000... ○ 0 new files - all duplicates
Testing page 50000... ○ 0 new files - all duplicates
Testing page 100000... ○ 0 new files - all duplicates

I’m working on a different method of obtaining a complete dataset zip for dataset 9. For those who are unaware, for a time yesterday there was an official zip available from the DOJ. To my knowledge no one was able to fully grab it. But I believe the 49Gb zip is a partial of that before downloads got cut. It’s my thought that this original zip likely contained incriminating information and it’s why it got halted.

What I’ve observed is that Akamai still serves that zip sporadically in small chunks. It’s really strange and I’m not sure why it does, but I have verified with strings that there are pdf file names in the zip data. I’ve been able to use a script to pull small chunks from the CDN across the entire span of the file’s byte range.

Using the 49GB file as a starting point I’m working on piecing the file together, however progress is extremely extremely slow. If there is anyone willing to team up on this and combine the chunks please let me know.

How to grab the chunked data:

Script link: https://pastebin.com/sjMBCnzm

For the script will probably have to:

pip install rich

Grab DATASET 9, INCOMPLETE AT ~48GB:

 magnet:?xt=urn:btih:0a3d4b84a77bd982c9c2761f40944402b94f9c64&tr=udp%3A%2F%2Ftracker.opentrackr.org%3A1337%2Fannounce 

Then name the downloaded file 0-(the last byte the file spans).bin

So for example the 48 GB file it would be: 0-48995762175.bin

Next to the python script make a directory called: DataSet 9.zip.chunks

Move the renamed first byte range 48 GB file in to that directory.

Make a new file next to the script called cookies.txt

Install the cookie editor browser extension (https://cookie-editor.com/)

With the browser extension open go to: https://www.justice.gov/age-verify?destination=%2Fepstein%2Ffiles%2FDataSet+9.zip

The download should start in your browser, cancel it.

Export the cookies in Netscape Format. They will copy to your clipboard.

Paste those in your cookies.txt, save and close it.

You can run the script like so:

python3 script.py \
  'https://www.justice.gov/epstein/files/DataSet%209.zip' \
  -o 'DataSet 9.zip' \
  --cookies cookies.txt --retries 3 \
  --backoff 5.0 \
  --referer 'https://www.justice.gov/age-verify?destination=%2Fepstein%2Ffiles%2FDataSet+9.zip' \
  -t auto -c auto

Script Options:

• -t - The number of concurrent threads to use which results in trying that many byte ranges at the same time. Setting this to auto will auto calculate based on your CPU but will cap at 8 to be safe and avoid getting banned by Akamai.
• -c - The chunk size to request from the server in MB. This is not always respected by the server and you may get a smaller or larger chunk, but the script should handle that. Setting this to auto scales with the file size, though feel free to try different sizes.
• --backoff - The backoff factor between failures, helps prevent Akimai throttling your requests.
• --retries - The number of times to retry a byte range for that iteration before moving on to the next byte range. If it moves on it will come back to it again on the next loop.
• --cookies - The path to the file containing your Netscape formatted cookies.
• -o - The final file name. The chunks directory is derived from this so make sure it matches the name of the chunk directory that you primed with the torrent chunk.
• --referer - Just leave this for Akimai, set the referer http header.

There are more options if you tun the script with the --help option.

If you start to receive HTML and or HTTP/200 responses then you need to refresh your cookie.

If you start to receive HTTP/400 responses then you need to refresh your cookie in a different browser, Akamai is very fussy.

A VPN and multiple browser might be useful to change your cookie and location combo.

Edit

I tested the script on Dataset 8 and it was able to stitch a valid zip together so assuming we’re getting valid data with Dataset 9 it should work.

I’m in the process of downloading both dataset 9 torrents (45.63 GB + 86.74 GB). I will then compare the filenames in both versions (the 45.63GB version has 201,358 files alone), note any duplicates, and merge all unique files into one folder. I’ll upload that as a torrent once it’s done so we can get closer to a complete dataset 9 as one file.

• Edit 31Jan2026 816pm EST - Making progress. I finished downloading both dataset 9s (45.6 GB and the 86.74 GB). The 45.6GB set is 200,000 files and the 86GB set is 500,000 files. I have a .csv of the filenames and sizes of all files in the 45.6GB version. I’m creating the same .csv for the 86GB version now.

• Edit 31Jan2026 845pm EST -

  • dataset 9 (45.63 GB) = 201357 files
  • dataset 9 (86.74 GB) = 531257 files

  I did an exact filename combined with an exact file size comparison between the two dataset9 versions. I also did an exact filename combined with a fuzzy file size comparison (tolerance of +/- 1KB) between the two dataset9 versions. There were:

  • 201330 exact matches
  • 201330 fuzzy matches (+/- 1KB)

  Meaning there are 201330 duplicate files between the two dataset9 versions.

  These matches were written to a duplicates file. Then, from each dataset9 version, all files/sizes matching the file and size listed in the duplicates file will be moved to a subfolder. Then I’ll merge both parent folders into one enormous folder containing all unique files and a folder of duplicates. Finally, compress it, make a torrent, and upload it.

• Edit 31Jan2026 945pm EST -

  Still moving duplicates into subfolders.

• Edit 31Jan2026 1027pm EST -

  Going off of xodoh74984’s comment (https://lemmy.world/post/42440468/21884588), I’m increasing the rigor of my determination of whether the files that share a filename and size between both version of dataset9 are in fact duplicates. This will be identical to rsync --checksum to verify bit-for-bit that the files are the same by calculating their MD5 hash. This will take a while but is the best way.

• Edit 01Feb2026 1227am EST -

  Checksum comparison complete. 73 files found that have the same file name and size but different content. Total number of duplicate files = 201257. Merging both dataset versions now, while keeping one subfolder of the duplicates, so nothing is deleted.

• Edit 01Feb2026 1258am EST -

  Creating the .tar.zst file now. 531285 total files, which includes all unique files between dataset9 (45.6GB) and dataset9 (86.7GB), as well as a subfolder containing the files that were found in both dataset9 versions.

• Edit 01Feb2026 215am EST -

  I was using wayyyy to high a compression value for no reason (ztsd --ultra --22). Restarted the .tar.zst file creation (with ztsd -12) and it’s going 100x faster now. Should be finished within the hour

• Edit 01Feb2026 311am EST -

  .tar.zst file creation is taking very long. I’m going to let it run overnight - will check back in a few hours. I’m tired boss.

• EDIT 01Feb2026 831am EST -

COMPLETE!

And then I doxxed myself in the torrent. One moment please while I fix that…

Final magnet link is HERE. GO GO GOOOOOO

I’m seeding @ 55 MB/s. I’m also trying to get into the new r/EpsteinPublicDatasets subreddit to share the torrent there.