Notice how I didn’t just use the service name?

<Disco>

<Netfucks>

<MailGoog>

Whatever nickname you use for your services. There is no requirement you also use the service name in the tagging template.

The idea that a breach of a service would have someone looking at your individual password is also pretty silly. There would be variations and pattern matching Lagos run against lists of hundreds of thousands to millions of passwords… but the decryption of a complete password to plain text is so reductions at this point, we are talking about the 0.01% case of a then even more silly “let’s look at this guys password in particular” 0.0001% case on top of it…

It’s not a real problem because if your service is at the point it is leaking not just salted and hashed passwords, but plain text passwords: you are in a big problem up no matter what for most users. Almost everyone reuses passwords. The real risk is the simple reuse. Get just a slightly different variation and you are miles more secure in the case of a breach that results in full decryption.

The majority still reuse Password1234! Everywhere. This gives you a easier way to be miles better.

Better still of course is some sort of managed password vault, assuming you trust their implementation. However, this costs zero in the training, or tech literacy upskilling that even the moderate change to a password vault requires. It’s simply an extension of what people already intuitively know. Thus, barrier to entry is easier while giving you several orders more protection.

Merica means freedom to do dumb things. Lemme fly!

https://dev-to-uploads.s3.amazonaws.com/i/it0fk0jbqphcgecnpbq7.jpg

Hmmm. No.

You don’t partially decrypt passwords. You either get the full thing or you get gobble.

So if they get 1, they still don’t know you use <DiscordTag> or <Disco> or <DiscordSeevice> etc. I wouldn’t just straight up say “Netflix” in my service tagging.

You can take this a step further to segregate passwords as well.

Reusing passwords across devices is bad. If one gets compromised you don’t want a password being out into a brute force table to be used with all your other accounts elsewhere.

This method of tagging using HTML markup styles in your passwords lets you keep the same core passphrase but alter the tagging, specific to the service.

You can do this easily while also giving you artificial password complexity.

Example:

Core passpgrase is “yogurt”

Password for gmail becomes markup with a <mailPassGoog>yogurt</mailPassGoog>

I only need to remember yogurt.

Every device just gets a truncated service tag appended to the beginning and end using HTML style tags.

Suddenly you have a 26+ character password that you don’t forget and doesn’t compromise you across other services because each is different.

Lol. No.

9mm? 1 round? Nah.

I like how I said, the problem is progress is moving so far you don’t even realize what you don’t know about the subject as a layman… and then this comment appears saying things are not possible.

Lol.

How timely.

I the speed at which things are changing and redefining what is possible in this space is moving faster than any other are of research. It’s insane to the point that if you are not actively reading white papers every day, you miss major advances.

The layman had this idea of what “AI” means, but we have truly no good way to make the word align to its meaning and capabilities with how fast we change what it means underneath.

Seeing Beyond the Brain: Conditional Diffusion Model with Sparse Masked Modeling for Vision Decoding: https://aiimpacts.org/2022-expert-survey-on-progress-in-ai/

High-resolution image reconstruction with latent diffusion models from human brain activity: https://www.biorxiv.org/content/10.1101/2022.11.18.517004v3

Semantic reconstruction of continuous language from non-invasive brain recordings: https://www.biorxiv.org/content/10.1101/2022.09.29.509744v1

Seeing Beyond the Brain: Conditional Diffusion Model with Sparse Masked Modeling for Vision Decoding: https://aiimpacts.org/2022-expert-survey-on-progress-in-ai/

High-resolution image reconstruction with latent diffusion models from human brain activity: https://www.biorxiv.org/content/10.1101/2022.11.18.517004v3

Semantic reconstruction of continuous language from non-invasive brain recordings: https://www.biorxiv.org/content/10.1101/2022.09.29.509744v1

A large language model took a 3 second snippet of a voice and extrapolated from that the whole spoken English lexicon from that voice in a way that was indistinguishable from the real person to banking voice verification algorithms.

We are so far beyond what you think of when we say the word AI, because we replaced the underlying thing that it is without most people realizing it. The speed of large language models progress at current is mind boggling.

These models when shown FMRI data for a patient, can figure out what image the patient is looking at, and then render it. Patient looks at a picture of a giraffe in a jungle, and the model renders it having never before seen a giraffe… from brain scan data, in real time.

Not good enough? The same FMRI data was examined in real time by a large language model while a patient was watching a short movie and asked to think about what they saw in words. The sentence the person thought, was rendered as English sentences by the model, in real time, looking at fMRI data.

That’s a step from reading dreams and that too will happen inside 20 months.

We, are very much there.

There is a limit of pain and suffering humans can tolerate before they hit a breaking point. Every person, no matter how strong, will kill a human being if pushed far enough down that road.

I have witnessed both of the only two possible outcomes.

Themselves, or someone else.