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Email obfuscation rendered almost ineffective against ChatGPT

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Re: Email obfuscation rendered almost ineffective against ChatGPT

#171

Post by gnicholas »

marginalia_nu wrote: post #146

If you aren't getting spam-email on your obfuscated email string, it seems more likely email scraping with the intent of sending spam is very risky given the fairly widespread proliferation of spamtraps/honeypots along with actual legislation in some regions. You can quickly ruin your IP and domain reputation and end up on various grey/blacklists doing this stuff. Like I post my (unobfuscated) email address absolutel…

> Like I post my (unobfuscated) email address absolutely everywhere and rarely get unsolicited email as a result, because almost nobody in this space is ignorant enough to send unsolicited commercial emails to unknown email addresses found online.

Really? I’ve started getting founderspam from YC companies lately, and when I read this blog post I realized where they likely got my email address.

Re: Email obfuscation rendered almost ineffective against ChatGPT

#172

Post by nervuri »

marginalia_nu wrote: post #146

If you aren't getting spam-email on your obfuscated email string, it seems more likely email scraping with the intent of sending spam is very risky given the fairly widespread proliferation of spamtraps/honeypots along with actual legislation in some regions. You can quickly ruin your IP and domain reputation and end up on various grey/blacklists doing this stuff. Like I post my (unobfuscated) email address absolutel…

> It also seems like this type of obfusction probably never was particularlly effective.

It actually is effective - at least it was a few years ago. See these tests:

https://www.johnplummer.com/javascript/email-obfuscation-wor...

https://web.archive.org/web/20160304042853/http://techblog.t...

Re: Email obfuscation rendered almost ineffective against ChatGPT

#173

Post by GTP »

Tostino wrote: post #8
axlee wrote: post #5

No large-scale email scraper has the budget necessary to run the content it scrapes through a LLM. So as far as real-world goes, nothing changes: the .2 cents it would cost to run ChatGPT on a page to extract potentially obfuscated emails would cost magnitudes more than it could ever bring in revenues. Regarding the examples provided, there is nothing there that a simple regex couldn't achieve, so I don't really see…

You do realize how possible it is to fine tune a task like this (along with a hundred others in a similar vein) on a tiny model you can scale on your own hardware? I've run hundreds of millions (150m so far in a couple of weeks of non-continuous running as I tweaked things) of tokens through my 2x 3090 with a 13b llama2 model I fine tuned on tasks like: summary, knowledge graph generation, writing using the knowledge…

Why finetune a LLM if you can defeat most obfuscation tecniques with a few regex?

Re: Email obfuscation rendered almost ineffective against ChatGPT

#174

Post by ac2u »

GTP wrote: post #173
Tostino wrote: post #8

Earlier quoted context omitted.

You do realize how possible it is to fine tune a task like this (along with a hundred others in a similar vein) on a tiny model you can scale on your own hardware? I've run hundreds of millions (150m so far in a couple of weeks of non-continuous running as I tweaked things) of tokens through my 2x 3090 with a 13b llama2 model I fine tuned on tasks like: summary, knowledge graph generation, writing using the knowledge…

Why finetune a LLM if you can defeat most obfuscation tecniques with a few regex?

Because there's a chance your LLM might be able to still get what you need if the obfuscation technique is changed or altered.

Anyway, nothing to say you can't use both, or have a fallback system.

Re: Email obfuscation rendered almost ineffective against ChatGPT

#175

Post by indrora »

PeterisP wrote: post #85
menzoic wrote: post #21

Earlier quoted context omitted.

This is assuming you’re using a really big LLM behind a paid service. There are plenty of smaller open source models. Not sure at what point it’s not “large” but when fine tuned they are capable of matching the largest LLM in performance on narrow tasks. Some of these open source models can even be run on your local machine. It’d be very inexpensive to run thousands of pages through it. https://llm-leaderboard.stream…

The "smaller" open source models with adequate capabilities are still rather large and thus compute-intensive. Running thousands of pages through it on a random CPU won't happen in minutes but rather in days, and extracting emails from only thousands of pages is not very valuable.

Thousands of pages is pretty good and what I’m coming to expect on the low side for cheap (single consumer GPU or NPU) throughput with the 5…8GB models now. Heck, with some of the optimizations that Llama.cpp has made, with SafeTensors and GGUF, you can reduce the actual memory usage down.

A cheap Mac mini with apple’s neural cores is good enough that it roleplays smut with a human at human speed. We’re going to see a rapid increase in throughput to price. We’ve already got small LLMs that run on mobile phones.

Re: Email obfuscation rendered almost ineffective against ChatGPT

#176

Post by ac2u »

batch12 wrote: post #167
axlee wrote: post #5

No large-scale email scraper has the budget necessary to run the content it scrapes through a LLM. So as far as real-world goes, nothing changes: the .2 cents it would cost to run ChatGPT on a page to extract potentially obfuscated emails would cost magnitudes more than it could ever bring in revenues. Regarding the examples provided, there is nothing there that a simple regex couldn't achieve, so I don't really see…

There are likely only so many patterns that can exist and still be usable as a shareable and human reversible email address. Maybe one could have the llm identify these edge cases and write regex/code to parse future instances to convert back to a usable format.

Let's say the poster works at IBM and they want to provide a means for humans to contact them and frustrate scrapers so they say:

'My email address is my username@"the company no one ever got fired for buying from".com'

Write me a regex for that.

GPT on the other hand:

https://imgur.com/a/Hw0kcee

Re: Email obfuscation rendered almost ineffective against ChatGPT

#177

Post by john2x »

kajic wrote: post #151
bdcravens wrote: post #150

Of course. The idea that human parseable strings would forever be computer-proof is silly. I'm always amazed at the number of people who think myemailname+filterkeyword@gmail.com is spam proof.

Some people set filterkeyword to name-of-business, to know who sold them out if they start receiving spam on that address.

I use the + technique, but I've been doubtful of its effectiveness. It's easy enough to remove the text after the +.

Re: Email obfuscation rendered almost ineffective against ChatGPT

#178

Post by dazhbog »

waveBidder wrote: post #163
dazhbog wrote: post #32

I used chatGPT to decode proprietary binary files of some industrial machinery. It was amazing how it can decipher shit and find patterns. It first looked for ascii characters, then byte sequences acting as delimiters, then it started looking at which bytes could be the length or what 4-bytes could be floating point numbers of coordinates and which endianness was more logic for coordinates, etc. etc. crazy stuff.

how are you sure it wasn't bullshitting? were you feeding it a known binary?

Some of the input data was known yes, because this software has a gui and it outputs a binary file based on user data (PCB Bill of materials)+internal machine settings. So i knew there were some coordinates and ascii data in there and GPT helped find the delimiters, etc. Some things i was also able to figure out with Ghidra and lots of trial and error.

Re: Email obfuscation rendered almost ineffective against ChatGPT

#179

Post by dazhbog »

tamimio wrote: post #158
dazhbog wrote: post #32

I used chatGPT to decode proprietary binary files of some industrial machinery. It was amazing how it can decipher shit and find patterns. It first looked for ascii characters, then byte sequences acting as delimiters, then it started looking at which bytes could be the length or what 4-bytes could be floating point numbers of coordinates and which endianness was more logic for coordinates, etc. etc. crazy stuff.

Check Ciphey, I have used several times before and overall it’s great. https://github.com/Ciphey/Ciphey

Oh looks cool, I will check it out! Thanks!

Re: Email obfuscation rendered almost ineffective against ChatGPT

#180

Post by marwis »

Detrytus wrote: post #120
Karellen wrote: post #55

Earlier quoted context omitted.

I think the point is that particular type of obfuscation is an example, and a regex will only catch that one. If the obfuscation is substantially different, you'll need another regex which you'll have to write yourself. Whereas the LLM doesn't need to be told about the specific type of obfuscation in use, and can act in a more general way - including against some new types that haven't been used before.

Still, you can get a collection of like 10-20 regexes for most common types of obfuscation, and that will solve the problem like 90% of the time. And it is much cheaper, computationally, than running LLM on the whole content.

I always felt email obfuscation is just a cargo cult and the reduction in spam is only from improvements in anti-spam tech.

I never obfuscated my address and pretty much haven't seen spam since first days of Gmail. And very little even before then thanks to SpamAssassin.

Also raw email addresses can be easily harvested from git repos, mailing list archives and possibly other sources. A lot of technical people who chose to obfuscate likely posted to one such system at some point.

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