📊 Full opportunity report: The Coldcard Hack: Did AI Play A Part In Its Discovery? on ThorstenMeyerAI.com — validation score, market gap, and execution plan.
TL;DR
The Coldcard hardware wallet experienced a significant breach involving the theft of over 1,800 BTC. While some claim AI, specifically the Kimi K3 model, was involved in discovering the vulnerability, evidence remains inconclusive. The incident highlights limitations of AI in security testing and ongoing concerns about hardware wallet safety.
In late July 2023, over 1,800 BTC—approximately $116 million—were drained from Coldcard hardware wallets, despite their offline, secure design. While initial speculation linked the breach to AI models, no definitive evidence confirms this connection, and investigations remain ongoing. This incident raises questions about the security of hardware wallets and the role of AI in vulnerability discovery.
The breach involved the theft of funds from more than 5,200 addresses, with a pattern indicating automated, precomputed operations rather than victims’ panic transfers. The attack exploited a flaw in Coldcard Mk3 devices, which had a firmware update in March 2021 that reduced the randomness of seed generation from 128 bits to approximately 40 bits of entropy. This significant reduction made it feasible for attackers with specialized hardware to brute-force private keys, enabling the theft of funds without directly compromising the devices.
Within hours of the attack, a pseudonymous account suggested that an AI model, Kimi K3, might have identified the vulnerability, citing the timing of the model’s release and the start of the theft. However, experts point out that the model’s capabilities in security-specific tasks are limited, and the breach’s arithmetic nature means AI was likely not necessary for the attack. Independent researchers confirmed that the vulnerability could be exploited through brute-force methods, which do not require AI assistance.
Coinkite, the maker of Coldcard, stated that they cannot confirm AI involvement, noting that their own AI review of the firmware prior to the attack did not detect the flaw. This underscores the current limitations of AI in security audits and suggests that the breach was primarily a hardware and firmware issue rather than an AI-driven discovery.
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 Hardware Wallet Security and AI's Role
This incident highlights that even highly secure, offline hardware wallets can be vulnerable if firmware flaws are not detected. It also demonstrates that current AI models, such as Kimi K3, have limited ability to identify security-critical vulnerabilities autonomously. The story underscores the importance of rigorous manual security testing and the ongoing challenges in integrating AI into hardware security assessments.
As an affiliate, we earn on qualifying purchases.
Background on Coldcard and the 2021 Firmware Flaw
Coldcard, developed by Canadian firm Coinkite, is a widely used hardware wallet designed for secure offline Bitcoin storage. In March 2021, a firmware update was released that inadvertently reduced the seed generation entropy from 128 bits to roughly 40 bits, significantly weakening the security of new wallets created after that update. This flaw remained undetected until the July 2023 breach, which exploited the reduced randomness to facilitate large-scale thefts. The attack's pattern suggests an automated process, possibly using precomputed keys, rather than a targeted attack on individual users.
"We have no evidence to confirm that AI was involved in discovering or exploiting the vulnerability."
— Coinkite spokesperson
As an affiliate, we earn on qualifying purchases.
Unconfirmed Role of AI in the Coldcard Breach
While some claims suggest AI models like Kimi K3 may have been used to identify the vulnerability, there is no concrete evidence to support this. Experts note that the attack was arithmetic and brute-force in nature, which does not inherently require AI assistance. The actual method used to discover the firmware flaw remains unconfirmed, and investigations are ongoing.
hardware wallet firmware update kit
As an affiliate, we earn on qualifying purchases.
As an affiliate, we earn on qualifying purchases.
Ongoing Investigations and Security Improvements
Authorities and Coinkite are continuing to investigate the breach to determine how the firmware flaw was exploited. The company has committed to reviewing and patching the firmware to prevent future vulnerabilities. Industry experts emphasize the need for enhanced security audits and caution against overestimating AI's current capabilities in security vulnerability detection.
As an affiliate, we earn on qualifying purchases.
Key Questions
Did AI directly cause the Coldcard breach?
There is no confirmed evidence that AI caused or discovered the vulnerability. While some speculate AI models like Kimi K3 may have played a role, experts agree the attack was arithmetic and brute-force based, not AI-driven.
What was the technical flaw that enabled the theft?
The firmware update in March 2021 reduced the seed generation entropy from 128 bits to approximately 40 bits, making the private keys vulnerable to brute-force attacks.
Has Coinkite confirmed AI involvement?
No. Coinkite explicitly stated they have no evidence to confirm AI involvement and that their own AI review did not detect the flaw prior to the attack.
What are the implications for hardware wallet security?
This incident underscores the importance of rigorous firmware testing and the limitations of current AI tools in security audits. It highlights the need for manual review and multiple layers of security in hardware devices.
Source: ThorstenMeyerAI.com
