📊 Full opportunity report: Did Artificial Intelligence Reveal The Coldcard Hack? Examining The Evidence on ThorstenMeyerAI.com — validation score, market gap, and execution plan.
TL;DR
The Coldcard hardware wallet was drained of over 1,800 BTC in a series of automated attacks. Claims link AI, specifically the Kimi K3 model, to the exploit, but evidence remains unconfirmed. The event highlights concerns about AI’s role in security vulnerabilities.
The Coldcard hardware wallet was drained of more than 1,800 BTC in a series of automated transactions that bypassed its offline security measures. While the device’s firmware was found to have a critical vulnerability, the evidence linking artificial intelligence, specifically the Kimi K3 model, to the exploit remains unconfirmed. This incident raises questions about the role of AI in security breaches involving hardware wallets.
On July 30, 2023, approximately 1,816 BTC, valued at around $116 million, was stolen from Coldcard wallets in multiple waves over a 41-minute window. The pattern of the theft suggests an automated process using precomputed keys, rather than victims manually moving funds.
The root cause appears to be a firmware flaw introduced in March 2021, which reduced the device’s seed entropy from 128 bits to about 40 bits. This significantly lowered the security barrier, enabling an attacker with sufficient hardware to brute-force the keys by scanning blockchain addresses.
Claims emerged linking the attack to the AI model Kimi K3, with some suggesting it identified vulnerabilities in the firmware shortly after its public release on July 27. However, no concrete evidence has been presented to confirm that AI directly discovered or exploited the flaw. Coinkite, the maker of Coldcard, stated that it cannot confirm how the vulnerability was discovered, only that an attacker could have used AI to read the firmware.
Independent researchers reproduced the vulnerability using AI models after the flaw was already publicly known, indicating that AI’s role may have been to lower the cost of analyzing the firmware rather than discovering the flaw unprompted.
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 of AI Involvement in Coldcard Breach
This incident underscores the potential for AI to assist in security breaches, especially by reducing the cost and complexity of analyzing firmware and code. The fact that Coinkite's own AI review prior to the attack failed to detect the flaw highlights current limitations in automated security assessments. The event raises concerns about the future role of AI in both defending and attacking hardware security, emphasizing the need for more robust safeguards.
Sexyppl Wallet Replacement Screws + Screwdriver+ Metal Clip, For Metal Wallet Repair Screw Kit，Elastic Cash Strap Replacement for Wallet (Standard Set - Black) (5)
- Premium Material: Made of high-quality materials for durability
- Multiple Options: Includes screwdrivers, screws, belts, and clips
- Easy Replacement: Simplifies repairing and replacing wallet parts
As an affiliate, we earn on qualifying purchases.
As an affiliate, we earn on qualifying purchases.
Background on Coldcard Firmware and Recent Vulnerability
Coldcard is a widely used hardware wallet designed for secure, offline storage of Bitcoin private keys. In March 2021, a firmware update introduced a flaw that reduced seed entropy, making the device vulnerable to brute-force attacks. The vulnerability was publicly documented, and researchers demonstrated that AI models could assist in analyzing such flaws, although they did not discover the bug independently.
The July 2023 theft involved automated, large-scale draining of wallets, with patterns indicating precomputed key attacks rather than user error. The timing of claims linking AI models to the attack coincides with the public release of Kimi K3, but no direct connection has been established.
"We cannot confirm how the vulnerability was discovered, only that it was exploited."
— Coinkite spokesperson
cold storage cryptocurrency wallets
As an affiliate, we earn on qualifying purchases.
As an affiliate, we earn on qualifying purchases.
Unconfirmed Role of AI in the Coldcard Attack
There is no conclusive evidence that artificial intelligence, including the Kimi K3 model, directly discovered or exploited the firmware vulnerability. While claims suggest a possible link based on timing and capabilities, investigations have yet to confirm AI involvement. It remains unclear whether the attacker used AI tools or simply took advantage of known vulnerabilities.
hardware wallet firmware upgrade kit
As an affiliate, we earn on qualifying purchases.
As an affiliate, we earn on qualifying purchases.
Future Investigations and Security Measures
Authorities and security researchers will continue analyzing the attack to determine the precise method used. Coinkite is expected to review and improve firmware security protocols, possibly integrating more advanced AI-driven testing. The incident may also prompt broader industry discussions on AI's role in security and vulnerability detection, emphasizing the need for stronger safeguards against automated exploitation.
As an affiliate, we earn on qualifying purchases.
Key Questions
Did AI actually discover the firmware flaw?
There is no confirmed evidence that AI discovered the flaw independently. The vulnerability was publicly known before the attack, and AI analysis likely lowered the cost of exploiting it rather than discovering it unprompted.
Could AI have helped in the attack?
It is possible that AI tools assisted the attacker in analyzing the firmware or scanning blockchain addresses efficiently, but this has not been proven. The attack itself was arithmetic and could have been executed without AI assistance.
What does this mean for hardware wallet security?
This incident highlights the importance of rigorous firmware security and the limitations of current automated review processes. It suggests that even devices considered secure can be vulnerable if firmware flaws are overlooked.
Will this change how AI is used in security testing?
Likely yes. The event underscores both the potential and current limitations of AI in security assessments, prompting developers to enhance testing protocols and incorporate more advanced AI tools.
Source: ThorstenMeyerAI.com
