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A tell from the Manhattan Project was that scientists who had been publishing about nuclear fission suddenly stopped publishing. As Justin points out here, the lack of cryptographic results in OpenAI's mathematical breakthrough could itself be a tell. Evidence against it would be if they published a few improvements that aren't massive breakthroughs.
Today I call upon the blockchain industry to calmly begin planning for "bunker mode". My personal recommendation is to set in motion a controlled mass migration of assets to fresh addresses, i.e. addresses whose pubkeys remain hidden behind a hash.
Holders, starting with large and sophisticated ones, should consider moving the bulk of their funds to addresses that have never signed a transaction. And when they do sign one, they should also move remaining funds to a new address (possibly generated from the same seed phrase).
Don't rush. While I believe there is cause for action a rushed migration would do more harm than good. Don't panic either. Moving assets to protected addresses is a simple, preventative step which does not require new cryptography or new wallets.
IMO it is now reasonable to brace for the possibility that ECDSA breaks before qday, in the worst case in months not years. By "break" I mean fast private key recovery (e.g. in one week) on available hardware (e.g. a large GPU cluster).
Recent days have been humbling for human mathematical intuition. Long-held, unquestioned hypotheses have fallen. This includes the n log(n) bound for integer multiplication and the 3SUM conjecture. In hindsight, May's unexpected disproof of the Erdős unit distance conjecture was our warning shot.
Yesterday's OpenAI drop made it clear that mathematical superintelligence is upon us. They say there are weeks where decades happen. We are about to live through weeks where centuries of mathematical progress happen. Could our magic 64-byte ECDSA signatures be too good to be true? Was it just security through obscurity all this time?
Elliptic curves feel especially vulnerable to superintelligence. Curves carry rich structure, with room for fancy tricks like Schoof, Frobenius, pairings. (By contrast, hashes are designed to minimise algebraic structure.)
Separately, as Ewin Tang can attest, an efficient quantum algorithm sometimes foreshadows an efficient classical one. We should be open to the possibility of a classical counterpart to Shor that breaks elliptic curves and RSA at once.
Also noteworthy is the striking under-representation of cryptographic breakthroughs among the 722 mathematical results OpenAI published. I've witnessed first-hand the US government censoring academic quantum cryptanalysis results. Backroom interventionism is my base case.
I urge large, sophisticated actors to lead by example. Project11's "risq list" (bitcoin-risq-list.projecteleven[.]com) is a great tracker of exposed BTC pubkeys. Binance, Bitbank, Robinhood, Bitfinex, and Tether have an opportunity to harden their cold storage. Next month I'll address institutions in London in a live Q&A (forum.ethereuminstitutional[.]org/london-2026).
Again, please do not rush. Wallets holding under 50 BTC enjoy partial cover from "Satoshi's shield", i.e. his 20K exposed addresses that hold 50 BTC each. Load-bearing signers like oracles and L2 security councils should consider rotating ECDSA pubkeys with every signed message and/or multi-signing with a hash-based schemes like SPHINCS.
Exiting bunker mode safely will require post-AI cryptography. My inclination is to go all-in on hash-based cryptography and avoid structured mathematical assumptions entirely, whether from curves, lattices, or isogenies. A single battle-tested hash (e.g. from the SHA or BLAKE families) yields plausible post-AI security.
The Ethereum roadmap on strawmap[.]org fully embraces hash-based cryptography with end-to-end formal verification as a response to the quantum threat. Those timelines must now be revisited and accelerated in light of mathematical superintelligence. I'll be pushing for maximum defensive acceleration.
PlasmaBitcoin retweeted
🚨 SPECIAL INVESTIGATION 🚨
Is residual DNA a hidden adjuvant in vaccines?
We’ve heard plenty about residual DNA in mRNA Covid vaccines. But there’s a much bigger story.
Many vaccines and monoclonal antibodies are made using recombinant DNA technology — including Gardasil, flu, Hep B and RSV products.
So what happens to the residual DNA left behind by manufacturing? And what if removing that impurity compromises the product’s performance?
That may prove to be the vaccine industry’s dirty little secret.
LINK 👇
@SecKennedy @KUPERWASSERLAB @Kevin_McKernan @newstart_2024 @RetsefL @FLSurgeonGen @AaronSiriSG @SenRonJohnson
PlasmaBitcoin retweeted
Microsoft claims it would take ten years to sell you Powerpoint without selling you Excel and Word.
Vaccine-Maker Claims Splitting MMR Shot Could Take Up To 10 Years zerohedge.com/medical/splitt…
PlasmaBitcoin retweeted
It is a massive problem that:
1. Voting is no longer a viable means of change (because the capture and corruption are so extensive):
2. Elites, experts, and gatekeepers in this country are batsh*t insane (and probably cognitively damaged from vaccines, SSRIs, statins, & GLP-1s).
PlasmaBitcoin retweeted
Most scientific studies are fundamentally driven by the incentive to ensure the study is maximally irrelevant, and then to sell it as maximally relevant to the audience.
One time in grad school a mentor was discussing some run-ins with the animal ethics board, who wanted toys included in the rat cages because it’s good for the mental health of the animals.
The mentor was fighting to get the toys excluded.
“Everyone in science knows that you can abolish the dietary effect of anything you study by including a hamster wheel.”
“Why?” I asked.
“Because most of the dietary effects are tied to obesity and no diet can make a rodent obese if you allow them to exercise.”
“But isn’t that more realistic? Free-living humans can exercise all they want.”
The mentor got momentarily excited.
“We’re not about ‘relevance.” WE’RE ABOUT CONTROL!”
In other words, you win the science game by arguing your experiment was well controlled and the most important thing is getting a result that is statistically significantly different.
That’s a manageable game.
Imposing relevance at the risk of getting no results is not.
Now ask, why are so many exercise science studies done in untrained college-aged men?
Because EVEYRYTHING looks good in someone who has never trained. Your results are guaranteed.
Do they bear relevance to someone in their tenth year of serious lifting?
LOL.
No.
Or, at least, they might but your study gives no information about whether they do.
Similarly with nutritional supplements you take people who haven’t been supplementing.
You justify this by saying you don’t want extra variation.
But what you’re really doing is taking people marginally deficient in all kinds of things and giving them a huge dose that fixes it fast.
Something with no relevance to someone who eats a good diet or takes a multi-vitamin.
Does 20 grams of creatine in a single night maintain cognitive function during sleeplessness the same way in someone taking five grams for the last ten years as it does in someone who has never taken it?
I seriously doubt it.
Now here’s the problem:
Who is actually reading exercise science studies? 20 year old men who have never seen the inside of the gym?
Who is reading nutrition science papers? People who eat pop tarts for breakfast?
Who is reading creatine papers? People who have never even heard of creatine?
No. It’s people for whom the studies are meaningless who actually want to know what they say.
PlasmaBitcoin retweeted
Replying to @COLDCARDwallet @jackmallers
This is some wild hairsplitting and misdirection.
You absolutely did fall back to weak entropy, and the yasmarang implementation you put in libngu was even weaker than the one in MicroPython (because yours used hardcoded constants): github.com/switck/libngu/blo…
You were warned about this particular issue by me and at least one other person 4 years before me.
PlasmaBitcoin retweeted
A lot of people tell me to read Christopher Palmer's (@ChrisPalmerMD) Brain Energy. I've tried a few times over the years and would keep putting it down, annoyed.
The premise is directionally correct: mental health is downstream of cellular energy availability. But Palmer's answer to it is always the same:
Biogenesis and mitophagy.
More mitochondria, cleaner mitochondria — that's the mechanism he credits for keto, fasting, exercise, electroconvulsive therapy (ECT), thyroid, and even SSRIs. A mechanism that explains diet, movement, and induced seizures equally well isn't explaining much.
Worse, biogenesis isn't automatically evidence of improved metabolism. It can be compensatory. If each mitochondrion produces less ATP, the cell may build more of them to hold total output steady. More mitochondria can mean the cell is struggling, not healing.
So it skips the real question: not how many mitochondria you have, but whether they can simply do their job and burn glucose.
Palmer has the evidence and walks right past it:
Brain insulin resistance preceding psychosis by fifteen years.
Induced hyperglycemia degrading memory and mood.
Alzheimer's as brain glucose hypometabolism.
Alcoholic brains starved when sober.
His own case for keto gives it away: ketones are a rescue fuel for cells that can't use glucose. He champions the workaround and never asks why the primary pathway failed.
The analysis stays frustratingly surface-level throughout. Palmer works almost entirely at the level of the organelle—ATP-to-ADP ratios, ROS, calcium handling, fusion and fission—and never gets down to the enzymes.
Pyruvate dehydrogenase, the irreversible committed gate into oxidative metabolism, appears nowhere in the book. B vitamins show up three or four times each, all in passing. Thyroid gets a few pages at the end of the hormone chapter, framed as an augmentation strategy for refractory depression rather than something to check first.
Keto gets over twenty mentions, none of them in Chapters 5 through 14—the entire theoretical core. It shows up only once he starts prescribing. The epilepsy evidence is strong. But his own mechanism for it is the same one he credits to fasting, exercise, and ECT. If that's the active ingredient, ketosis is one route among several, and he never asks what else gets there. It's the closest he comes to nutritional biochemistry, and he stops at the one diet that made his career.
The serotonin chapter is where I lose patience entirely.
Palmer introduces low serotonin as one of the best-known single-cause theories (come on…), raises five sharp questions it can't answer—and never turns any of them on the drugs. Chapter 11 opens by conceding the ground outright: he isn't challenging the trials, isn't challenging the imbalance observations, isn't challenging the people who say the drugs saved them. Instead he replaces a dead rationale with a live one: SSRIs work, he concludes, by driving mitochondrial biogenesis, which conveniently also explains the two-to-six-week delay he raised earlier in the book.
The biogenesis claim rests on a single 2019 rodent study. And it runs precisely opposite to the evidence that SSRIs inhibit electron transport chain complexes and reduce ATP production—evidence he never mentions. Which is the strange part, because he built the category himself.
He devotes pages to psychiatric drugs that impair mitochondrial function, names antipsychotics and valproate, and warns that suppressing mitochondria may block recovery and can itself cause symptoms. SSRIs are simply exempt. In fact, "SSRI" appears three times in a nearly 90,000-word book.
Moncrieff, Kirsch, and Healy appear zero times.
Akathisia and sexual dysfunction appear zero times; "blunting" appears once, describing facial expression in schizophrenia.
"Placebo" appears only as trial design, never as efficacy. He never once reports a drug–placebo difference.
He gets within one paragraph of the activation literature—claiming that antidepressants raise brain energy and can trigger anxiety, mania, or psychosis in metabolically compromised people—and stops.
That’s also exactly backwards: akathisia doesn't look like a surplus of brain energy; it looks like a brain that can't afford the cost of holding itself still.
I understand this is a book written for a lay audience, and things have to be kept simple. I appreciate what it attempts, directionally. But I can't help being frustrated by how many opportunities are missed, and how much time goes to throat-clearing (a car-and-traffic analogy that could have been a paragraph runs across four chapters).
I hope more researchers and clinicians take up the brain energy model. It's correct—Palmer just fails to explain why. This book feels like one tentative step in a 100-meter sprint.
PlasmaBitcoin retweeted
@SimonDixonTwitt and @anasalhajji should do a podcast together on “the real reason for the war in Iran: managed transition.”
PlasmaBitcoin retweeted
From my interview with @_DannyKnowles on WBD last November. The possibility of flawed entropy has been on our radar from the beginning with @SeedSigner, which is why we've never attempted to use an RNG to generate keys for users. Best practices matter. Defaults matter.
31 years ago, Bitcoin legend Hal Finney posted the first challenge to break 40-bit encryption.
Adam Back and three others cracked it a month later.
Encryption is built upon the shoulders of giants performing decades of research and development.
PlasmaBitcoin retweeted
This is one of the more interesting reveals of the ColdCard saga. Pretty much every Bitcoin maximalist in Korea were not affected because they all used dice rolls.
How can this be? The culture of the Korean Bitcoin community is very much about doing things the right way. To give you an idea, I've visited many times, seen the same people many times and I still don't know most of their names because they almost all use pseudonyms, which is considered a best practice in that community.
I think there's something to learn here because the US Bitcoin Maximalist community was a little too trusting and not enough cypherpunk. Be like the Koreans, do things the right way, all the way.
PlasmaBitcoin retweeted
I haven't told the full story yet, but I came to the same conclusion back in May 2025 when I started doing an audit of `coldcard/firmware`.
I wanted to figure out conclusively where the CC RNG was getting sourced from, and found that it backed up to some shady library called libngu (github.com/switck/libngu) that had literally 6 stars on github and was maintained solely by a pseudoanon tranny.
I knew from past experience that linking to libsecp256k1 from Python was pretty easy, which seemed to be the stated purpose of the library use, and so I was confused about why it was there.
I sent a report to the CC team that I had doubts about whether the true RNG was actually in use, and pointed out that the hardcoded yasmarang constants in libngu were sloppy. I advised they rip the whole thing out and link against libsecp256k1 directly.
I was told that if something was wrong "we'd already know about it by now" and that everything was properly configured for the real boards.
I didn't follow up rigorously, which was a horrible mistake on my part.
Replying to @zherbert @FoundationHQ
Someone in telegram group literally pointed about coldcard random function back in 2021. Of course it gets ignore.
PlasmaBitcoin retweeted
Replying to @TheBlueMatt @lopp
Not intending to Monday morning quarterback, but I wanted to sharing my approach to defensive coding around RNGs:
1. Identify each source of entropy used by the RNG and instrument them. Measure how much min-entropy each source provides across different environments. /1
PlasmaBitcoin retweeted
Independently audited @SparrowWallet v2.5.4 using Kimi K3. Looking good as well. No malicious code, no worrying issues found. this was a complete audit. Good security practices observed.
PlasmaBitcoin retweeted
How to self-custody bitcoin:
Step 1. Generate a private seed phrase with sufficient entropy
we cannot verify the entropy of a particular seed.
we CAN verify the entropy of a seed generation method.
don't trust, verify.
PlasmaBitcoin retweeted
Following the recent Coldcard events, we performed an additional review of Passport's entropy architecture – for current and previous Passport models – and want to share more about our existing testing and continued code hardening.
Passport contains multiple independent hardware randomness sources. Before releasing each Passport model, we empirically tested each source, as well as the final combined entropy output, and performed statistical analysis on the results.
Since January, we’ve also been regularly running frontier AI models against our code alongside human review of every change. This includes GPT trusted cyber access.
Going forward, we intend to publish a report alongside each new software release identifying which frontier models were used plus any key findings.
We are also:
(1) Adding further health monitoring to detect hardware component failures and ensure that an improbable hardware failure never results in a low-entropy seed.
(2) Releasing our internal entropy-testing app on Passport Prime so anyone can generate millions or billions of samples, save them to a USB drive, and perform independent statistical analysis.
Our additional review found no evidence of an entropy vulnerability in Passport Prime, Passport Core, or Passport Founders Edition devices.
No action is needed for Passport-generated seeds. Thank you.



























