<rbrunner7> @silicon.dystopia:matrix.org: youtube.com/playlist?list=PLsSYUeVwrHBnAUre2G_LYDsdo-tD0ov-y

<rbrunner7> Although those are not really attempts to crack the "math". How would you even do that?

<silicon.dystopia:matrix.org> @rbrunner7: i mean who knows

<silicon.dystopia:matrix.org> on paper it might be solid, but the implementation might give cracks to sophisticated attacks

<silicon.dystopia:matrix.org> maybe there are still some signals that are possible to extract

<silicon.dystopia:matrix.org> ig i should be speaking in the past tense- i ofc dont mean any unfixed 'vulnerabilities'. im strictly interested in the past/fixed ones

There is a tool in src/blockchain_utilities that attempts to determine which outputs are spent by examining small rings. Ideally, spent status should not be knowable, but historically, the combination of very small rings (1 and 3 members IIRC) allowed chain reactions. While theoretically possible nowadays still, the larger rings used mean the probability of still doing so with modern

outputs is vanishingly small.

It's not a flaw in the math though, so might not be what you're after.

Another one closer to a flaw in the math is the ability to spend an output up to 8 times. AFAIK it was not actually exploited before we patched it.

Then there's presumably a lot of private work into probabity theory to break rings, but the people doing that are typically siding with the fash and not us, so that work isn't public.

There's an interesting use of change outputs if you're sending regularly to some party. If that party often sees, in a tx sent to them, a recurrence of an output created a change to another output they received earlier, they know there's a fair chance the tx comes from the same party. The same applies if the earlier output is a recent possible-ancestor of the output sent in the newer

tx, but probability goes down (rather fast I think) with ancestry depth.

All this attack surface is going to go with fcmp. AFAIK the other two layers of monero (stealth addressing and amount commitments) offer no purchase.

About implementation side issues, there are a lot of small fingerprinting things that can help group txes probabilistically too, such as "this tx was likely created by version x of monero-wallet-cli", etc. Nothing to do with math though.

<rucknium> @silicon.dystopia:matrix.org: Can you be more specific? Depending on what you mean, there have been a lot of attempts or zero. Do you mean the privacy (and deterministic or probabilistic), counterfeiting and theft protection, network stability, etc.? > <@silicon.dystopia:matrix.org> hi

<milas900:matrix.org> Hello I have a question .. can ai agents exploit the private key on monero on your device ?

<-----0:zano.org> @milas900:matrix.org: yes

<milas900:matrix.org> @-----0:zano.org: Can you elaborate more

<-----0:zano.org> @milas900:matrix.org: no. just don't do it

<-----0:zano.org> haha. joking. yes i will elaborate

<-----0:zano.org> most people recommend running your agents on a standalone set up, to avoid this and other issues

<plowsof:matrix.org> #monero.social:monero.social hardly an MRL topic is it . 'is my hot wallet safe' type of question

<-----0:zano.org> good point

<-----0:zano.org> @milas900:matrix.org: ask in the social lounge

<silicon.dystopia:matrix.org> @rucknium: hiii

<silicon.dystopia:matrix.org> (I'll respond to the earlier messages by moneromoo later when I have a chance to sit down :3)

<silicon.dystopia:matrix.org> honestly I'm deiven by curiosity; dont have any goal in mind[... more lines follow, see mrelay.p2pool.observer/e/gKHmyvwKb0pRYjJl ]

<silicon.dystopia:matrix.org> probabilistic is also good tho

<rucknium> Biggest cryptography one is getmonero.org/2017/05/17/disclosure…in-cryptonote-based-currencies.html

<rucknium> Here is an example of what happens if you don't implement Monero's cryptography correctly: github.com/kayabaNerve/zephyr-verify-bulletproofs

<rucknium> Check out moneroresearch.info too

<rucknium> For probabilistic, see github.com/Rucknium/OSPEAD and github.com/ACK-J/Monero-Dataset-Pip…rtificially_Intelligent_Attacks.pdf