The Coldcard Exploit: Was AI The Unexpected Hero?

📊 Full opportunity report: The Coldcard Exploit: Was AI The Unexpected Hero? on ThorstenMeyerAI.com — validation score, market gap, and execution plan.

TL;DR

A security flaw in Coldcard hardware wallets was exploited to drain over $116 million in Bitcoin. While some claim AI played a role, evidence is inconclusive. The incident highlights vulnerabilities in offline wallets and AI-assisted security analysis.

Over 1,800 Bitcoin, worth approximately $116 million, was drained from Coldcard hardware wallets in a series of automated attacks in late July 2023. The breach is linked to a previously unknown security flaw in the device’s firmware, which caused the seeds generated to become predictable. While some sources suggest artificial intelligence may have assisted in exploiting the flaw, there is no confirmed evidence tying AI directly to the attack.

The attack targeted Coldcard Mk3 hardware wallets manufactured by Coinkite, which are designed for offline, cold storage of Bitcoin. The breach was facilitated by a firmware update from March 2021 that quietly reduced the entropy of seed generation from 128 bits to roughly 40 bits, making the keys vulnerable to brute-force attacks. Over a four-day window from July 29 to August 1, hackers systematically drained hundreds of wallets, totaling 1,816 BTC.

Speculation quickly arose that AI, specifically the open-weighted model Kimi K3, might have played a role in discovering or exploiting the vulnerability. A viral post claimed that the model was ‘finding critical vulnerabilities,’ with timing aligning with the model’s release date on July 27. However, Coinkite’s official position remains that there is no concrete evidence linking AI to the breach. Independent researchers have demonstrated that the vulnerability could be exploited through standard computational means, without AI assistance, given the reduced entropy.

At a glance
reportWhen: developing; theft occurred between July…
The developmentA hardware wallet vulnerability led to the theft of over 1,800 BTC, with speculation about AI’s involvement, but no definitive proof has emerged.
AI DISPATCH · REALITY CHECK Coldcard exploit · 30 Jul–3 Aug 2026
A four-year-old bug, drained in minutes
Forty Bits

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 theory
$116M
1,816 BTC drained
5,200+
Addresses affected
128 → 40
Bits of seed entropy
4 yrs
Bug dormant since Mar 2021
01
What actually broke

A 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.

128
bits · as designed
Genuinely unpredictable. Guessing is not a strategy any adversary can attempt.
RNG fallback
~40
bits · after the flaw
A predictable, pattern-following process seeded by chip data. Searchable.
The keys were never stolen off the devices. They were regenerated from scratch on someone else’s computer — generate a candidate seed, derive its Bitcoin address, check it against the public blockchain, repeat. Seeds that added a dice roll or a passphrase were not vulnerable.
02
Four waves, mostly minutes apart

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.

30 Jul
41-minute window: 1,196 addresses drained; within it, a 25-min sweep of ~500 single-sig wallets took 594 BTC
~$70.2M
Fri–Sat
Third wave: 208 BTC swept from 1,912 addresses
208 BTC
Mon AM
Fourth wave detected, bringing the running total up
+ more
Total
1,816 BTC across 5,200+ addresses
~$116M
03
Was it Kimi K3? Keeping the strands apart

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.

The claim
Kimi K3 found the flaw
  • 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
What cuts against it
No investigator has named any actor
  • 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
04
The part that’s true regardless of who did it

Strip out the attribution entirely and the important finding survives.

The durable lesson
Coinkite ran an AI review of its own firmware weeks before the attack — and it did not catch the bug.
Defence isn’t a magic scanner
AI review performance depends on prompt, scope, and what it’s told to look for. It missed a live, catastrophic flaw.
The asymmetry favours attackers
The defender must find every dangerous weakness. The attacker needs to find one — at a cost that keeps falling.

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.

An AI may or may not have found the flaw. What’s certain: a defensive AI review missed it,
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 underscores the importance of robust security practices in hardware wallets, especially regarding firmware updates. It also highlights that while AI tools can assist in security analysis, they are not a magic solution; vulnerabilities can be discovered through traditional computational methods. The event raises questions about the reliance on offline storage and the potential for AI to lower barriers for exploiting hardware security flaws, emphasizing the need for continued vigilance and rigorous testing.

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Background on Coldcard and the Firmware Flaw

Coldcard is a widely used hardware wallet known for its emphasis on security and offline operation. In March 2021, a firmware update was released that inadvertently reduced the seed entropy from 128 bits to about 40 bits, significantly weakening the security of generated keys. This flaw remained unnoticed until the recent thefts, which involved automated, large-scale draining of wallets. The attack pattern suggests the use of precomputed keys and automated operations, rather than individual panic transactions.

Initial reports linked the timing of the attack to the release of Kimi K3, an open-weighted AI model, fueling speculation about AI's involvement. Experts, however, point out that exploiting the reduced entropy is a straightforward computational problem, solvable with specialized hardware, independent of AI capabilities.

"The vulnerability was rooted in a firmware change that quietly reduced the seed's entropy, making brute-force attacks feasible without sophisticated tools."

— Thorsten Meyer, security researcher

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Unconfirmed Links Between AI and the Attack

There is no verified evidence that artificial intelligence directly contributed to discovering or exploiting the firmware flaw. The timing of AI model releases and the attack is suggestive but coincidental. Experts note that the vulnerability could be exploited with standard hardware, without AI assistance. The role of AI remains speculative at this stage.

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Ongoing Investigations and Security Reinforcements

Researchers and security firms are examining the firmware and attack patterns to determine the exact method of exploitation. Coinkite is expected to review and improve firmware security further. The community is also calling for more rigorous testing of hardware wallet updates and increased transparency about vulnerabilities.

Additionally, discussions about AI's role in security analysis and vulnerability detection are likely to intensify, emphasizing the need for clear evidence before attributing exploits to AI models.

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Key Questions

Did AI directly cause the Coldcard wallet breach?

There is no confirmed evidence that AI caused or contributed to the breach. The attack exploited a firmware flaw that could be exploited through computational means alone.

How did the firmware flaw go unnoticed for so long?

The firmware change reducing seed entropy was implemented quietly and was not detected during routine security reviews, highlighting gaps in firmware testing processes.

Can hardware wallets be fully secure against such exploits?

No security system is infallible. Regular updates, thorough testing, and vigilant security practices are essential to mitigate risks, especially when firmware updates are involved.

What should users of Coldcard do now?

Users should monitor official security advisories, consider reinitializing affected wallets if possible, and stay updated on firmware improvements and security patches.

Source: ThorstenMeyerAI.com

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