📊 Full opportunity report: Exploring AI’s Potential In Coldcard Hack Discovery on ThorstenMeyerAI.com — validation score, market gap, and execution plan.
TL;DR
A firmware vulnerability in Coldcard hardware wallets caused the theft of over 1,800 BTC. While some speculate AI models may have played a role, evidence remains inconclusive. The incident highlights ongoing security challenges in cold storage solutions.
On July 30, 2023, a significant security breach resulted in the theft of over 1,800 BTC from Coldcard hardware wallets, despite their offline design. The incident has sparked debate over whether artificial intelligence models, specifically the open-weighted Kimi K3, played a role in discovering the underlying vulnerability, though no conclusive evidence has been presented.
The breach was traced to a firmware flaw introduced in March 2021, which reduced the randomness of seed generation from 128 bits to approximately 40 bits, making brute-force attacks feasible. Security analysis by Block’s engineering team confirmed that Coldcard wallets affected by this bug generated predictable seeds, enabling attackers to regenerate private keys on their own computers without physically tampering with the devices.
Between July 29 and August 1, over 1,800 BTC, worth roughly $116 million, was drained from more than 5,200 addresses in a series of automated operations. The pattern of rapid, large-scale withdrawals suggests an attack using precomputed keys rather than victims voluntarily moving funds. The breach involved a 41-minute window during which approximately 1,083 BTC was stolen.
Speculation arose that the open-weighted AI model Kimi K3, released on July 27, might have been used to identify the vulnerability. However, experts emphasize that the timing could be coincidental, and that the attack was primarily arithmetic, exploiting the predictable seed entropy rather than any AI-driven discovery process. Coinkite, the maker of Coldcard, stated that they have no evidence linking AI to the breach and that their own security review prior to the attack did not detect the flaw.
Offline hardware wallets were emptied without an attacker touching a single device. The keys weren’t stolen — they were regenerated, because a firmware flaw had quietly shrunk the space of possible keys to something a machine could search.
▲ AI attribution unproven · Kimi K3 claim is a community theoryA hardware wallet’s security rests entirely on one moment: the randomness used to generate its recovery seed. A 2021 firmware change quietly broke that randomness on affected Coldcard Mk3 devices.
The signature — hundreds of unrelated wallets emptied against a prepared list — points to an automated operation working from precomputed keys, per Galaxy Research on-chain analysis.
A viral post framed this as “the AI reckoning” and named Moonshot’s new open-weight model. The timing is suggestive. The evidence is not conclusive.
- K3 weights dropped 27 Jul; first draining ~29–30 Jul — two days apart
- Public firmware is exactly what an AI code agent can read
- Widely shared, emotionally resonant, and entirely uncorroborated
- UK–US AISI eval: K3’s exploit ability reaches only ~40% of frontier US models
- Independent researchers reproduced it after the flaw was public — not cold
- A 40-bit search needs no LLM; specialised hardware brute-forces it
Strip out the attribution entirely and the important finding survives.
The real shift isn’t that AI broke cryptography — the mathematics held; the software around it did not. It’s that frontier models are collapsing the window between when a vulnerability is created, discovered, and exploited. A flaw sat dormant for four years. That dormancy is becoming the exception.
and the window from dormant bug to drained wallet just got much shorter for everyone shipping code.
Implications for Cold Storage Security and AI’s Limitations
This incident underscores the persistent vulnerabilities in hardware wallet security, especially when firmware updates inadvertently weaken cryptographic randomness. It also highlights that, despite the hype around AI’s capabilities, many security flaws can be exploited through straightforward computational methods, and AI is not yet a reliable tool for identifying all such vulnerabilities. The case illustrates the importance of rigorous, independent security audits and the limits of current AI models in specialized security tasks.
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Recent Firmware Flaw and Its Impact on Coldcard Wallets
In March 2021, a firmware update for Coldcard Mk3 devices introduced a critical bug that reduced seed entropy from 128 bits to about 40 bits. This change was not initially detected and remained unnoticed until the recent theft. The vulnerability was publicly acknowledged by security researchers, who confirmed that the reduced entropy enabled brute-force attacks, leading to the recent large-scale theft. Prior to this, Coldcard was regarded as one of the most secure hardware wallets, emphasizing the significance of firmware integrity and independent security reviews in crypto hardware.
"The Coldcard incident reveals that even hardware designed for cold storage can be compromised through firmware flaws, and that AI's role in discovering such vulnerabilities remains uncertain."
— Thorsten Meyer, security researcher
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Unconfirmed Links Between AI and the Coldcard Breach
While some speculate that the open-weighted Kimi K3 AI model may have contributed to discovering the firmware flaw, there is no concrete evidence to support this. Experts note that the vulnerability was arithmetic in nature, and AI's role remains speculative. The timing coincidence does not establish causality, and investigations continue to determine how the flaw was discovered.
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Ongoing Investigations and Strengthening Firmware Security
Authorities and security researchers are conducting further analysis to confirm how the firmware flaw was exploited. Coldcard's manufacturer plans to implement more rigorous firmware review processes and release updated hardware with improved security features. The industry is also likely to see increased emphasis on independent audits and transparency to prevent similar incidents in the future.
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Key Questions
Could AI models like Kimi K3 have automatically found the Coldcard firmware flaw?
Current evidence suggests that the vulnerability was arithmetic and could be brute-forced without AI assistance. While AI may have lowered discovery costs, there is no definitive proof that Kimi K3 or similar models directly identified the flaw.
What does this incident reveal about hardware wallet security?
It highlights that firmware flaws can significantly weaken hardware security, especially if updates introduce bugs. Independent security reviews are essential to detect such vulnerabilities before they are exploited.
Is AI likely to become a reliable tool for discovering security flaws in hardware devices?
AI's capabilities are improving, but current models are limited in security-specific tasks. They can assist in code analysis but are not yet capable of reliably discovering complex vulnerabilities independently.
What measures will Coldcard take after this breach?
The manufacturer plans to enhance firmware review processes, improve hardware security features, and increase transparency to restore user confidence and prevent future exploits.
Source: ThorstenMeyerAI.com
