📊 Full opportunity report: Can AI Explain The Coldcard Hack? An Investigation on ThorstenMeyerAI.com — validation score, market gap, and execution plan.
TL;DR
The Coldcard hardware wallet was drained of over 1,800 BTC due to a firmware vulnerability that reduced seed entropy. While AI models are suspected by some, evidence indicates the attack was arithmetic, not AI-driven. The incident highlights limitations of AI in security testing.
Confirmed evidence shows that the Coldcard hardware wallets were drained of approximately 1,816 BTC—worth around $116 million—due to a firmware vulnerability that reduced seed randomness. The breach occurred in late July 2023, weeks after a suspected AI-related claim surfaced, but no direct link between AI and the attack has been established.
The vulnerability originated from a firmware update in March 2021, which quietly degraded the randomness of seed generation on affected Coldcard Mk3 devices. This reduction from approximately 128 bits of entropy to about 40 bits made the seeds predictable enough for an attacker to generate candidate keys en masse. Over a 41-minute window, attackers drained over 1,083 BTC from hundreds of addresses, with a significant portion taken in a single 25-minute sweep. The theft was carried out through automated, precomputed key attacks, not by hacking individual devices or stealing private keys directly.
Some claims suggested that an AI model, Kimi K3, identified vulnerabilities and facilitated the attack, given its weights were released shortly before the breach. However, security experts and independent researchers have pointed out that the attack was arithmetic in nature, and AI’s role—if any—remains speculative. Coinkite, the device manufacturer, acknowledged that they cannot confirm AI involvement, emphasizing that the attack exploited a known flaw that could be brute-forced without AI assistance.
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 Firmware Flaw and AI Claims
This incident underscores the importance of rigorous firmware security review, especially for hardware wallets that store billions in Bitcoin. The fact that a known flaw was exploited through straightforward brute-force methods highlights the limits of AI-based security assessments. The claims of AI involvement, while sensational, are not supported by concrete evidence and distract from the core issue: the vulnerability was arithmetic and could be exploited without advanced AI tools. The event raises questions about the effectiveness of current security review processes and the real role of AI in cybersecurity threats.
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Background on Coldcard and the Firmware Flaw
Coldcard, developed by Canadian firm Coinkite, is a widely used hardware wallet designed for secure offline storage of Bitcoin. In March 2021, a firmware update was released that inadvertently reduced the seed generation’s entropy, making the seeds more predictable. This flaw went unnoticed for over two years until the July 2023 attack, which utilized the predictable seed space to systematically drain funds. The incident is notable because the wallets’ private keys were never directly stolen; instead, the attacker regenerated keys from the weak seed space, bypassing physical security measures.
The attack pattern—mass draining of unrelated wallets within minutes—indicates an automated, computationally driven process, not a targeted breach. The timing and scale prompted speculation about AI involvement, especially after a viral claim linked the event to a recently released AI model, Kimi K3, but no evidence supports this connection.
"We cannot confirm AI was used in discovering or exploiting this vulnerability. The flaw was a known issue that could be brute-forced with sufficient computational resources."
— Coinkite spokesperson
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Unconfirmed Role of AI in the Coldcard Breach
While some claims suggest AI models like Kimi K3 identified vulnerabilities and facilitated the attack, there is no concrete evidence linking the model to the breach. Experts point out that the attack was arithmetic, and AI's involvement remains speculative. The true discovery method of the flaw is still unknown, and attribution to AI is not confirmed.
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Next Steps in Coldcard Security and Investigation
Coinkite has indicated it will review its firmware security processes and may release patches or updates to prevent similar vulnerabilities. Industry experts recommend thorough firmware audits and improved entropy testing for hardware wallets. Investigations into the breach are ongoing, and the community awaits more detailed forensic analysis to confirm how the flaw was discovered and exploited. Further scrutiny of AI's role in security vulnerabilities is expected, but current evidence does not support AI as the primary driver behind this attack.
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Key Questions
Was AI directly responsible for the Coldcard hack?
There is no confirmed evidence that AI was responsible. The attack exploited a known firmware flaw that reduced seed entropy, which could be brute-forced without AI assistance.
How did the attacker drain so many wallets so quickly?
The attacker used precomputed keys generated through brute-force methods, taking advantage of the reduced entropy in the seed generation process, enabling rapid, automated draining of funds.
Did the firmware update intentionally introduce the vulnerability?
No, the firmware update in March 2021 was an unintentional bug that degraded seed randomness. It was not designed to create a vulnerability.
Can this vulnerability be fixed now?
Yes, Coinkite has the opportunity to release firmware updates that restore proper entropy and improve security protocols to prevent future exploits.
What does this incident say about AI's role in cybersecurity?
This incident highlights that while AI can assist in security analysis, many vulnerabilities, especially arithmetic ones, can be exploited without AI. AI's role remains supportive rather than primary in such scenarios.
Source: ThorstenMeyerAI.com
