Faking a JPEG
71–80 of 97 posts
Re: Faking a JPEG
#72This makes me wonder if there are more efficient image formats that one might want to feed botnets. JPEG is highly complex, but PNG uses a relatively simple DEFLATE stream as well as some basic filters. Perhaps one could make a zip-bomb like PNG that only consists of a few bytes?
That might be challenging because you can trivially determine the output file sized based on the dimensions in pixels and pixel format, so if the DEFLATE stream goes beyond that you can stop decoding and discard the image as malformed. Of course, some decoders may not do so and thus would be vulnerable.
PNG doesn't have size limitation on the image dimensions (4bytes each). So I bet you can break at least one scrap bot with that.
Re: Faking a JPEG
#73the worst offender I saw is meta. they have facebookexternalhit bot (they sometimes use default python request user agent) that (as they documented) explicitly ignores robots.txt it's (as they say) used to validate links if they contain malware. But if someone would like to serve malware the first thing they would do would be to serve innocent page to facebook AS and their user agent. they also re-check every URL eve…
That barely registers as a blip even if you're hosting your site on a single server.
Re: Faking a JPEG
#74I am bit confused about the context. What is exactly the point of exposing fake data to webcrawlers?
Re: Faking a JPEG
#75the worst offender I saw is meta. they have facebookexternalhit bot (they sometimes use default python request user agent) that (as they documented) explicitly ignores robots.txt it's (as they say) used to validate links if they contain malware. But if someone would like to serve malware the first thing they would do would be to serve innocent page to facebook AS and their user agent. they also re-check every URL eve…
Since when is 10r/s flooding? That barely registers as a blip even if you're hosting your site on a single server.
This resulted in upscale. When handling such bot cost more than rest of the users and bots, that's an issue. Especially for our customers with smaller traffic.
This request rate varied from site to site, but it ranged from half to 75% of whole traffic and was basically saturating many servers for days if not blocked.
Re: Faking a JPEG
#76Given that current LLMs do not consistently output total garbage, and can be used as judges in a fairly efficient way, I highly doubt this could even in theory have any impact on the capabilities of future models. Once (a) models are capable enough to distinguish between semi-plausible garbage and possibly relevant text and (b) companies are aware of the problem, I do not think data poisoning will be an issue at all.