📊 Full opportunity report: The Coldcard Breach And AI: Did Artificial Intelligence Find The Vulnerability? on ThorstenMeyerAI.com — validation score, market gap, and execution plan.
TL;DR
The Coldcard hardware wallet was compromised due to a firmware vulnerability that reduced seed entropy, allowing automated theft of over $70 million. Claims that AI, specifically Kimi K3, discovered the flaw are unproven. The incident highlights ongoing security challenges and AI’s role in vulnerability analysis.
Canadian hardware wallet maker Coinkite confirmed that a firmware update in March 2021 compromised the security of its Coldcard Mk3 devices, leading to a large-scale theft of Bitcoin. The breach involved the devices generating predictable seeds due to a reduced entropy source, enabling automated attacks that drained over 1,816 BTC—roughly $116 million.
On 30 July, blockchain analysis from Galaxy Research revealed that attackers exploited the firmware flaw within a 41-minute window, draining a significant number of wallets. The vulnerability stemmed from a firmware update that quietly reduced seed randomness from 128 bits to approximately 40 bits, making brute-force attacks feasible with specialized hardware.
Claims emerged suggesting that an AI model, Kimi K3, might have played a role in discovering the flaw. A pseudonymous post claimed the model was ‘finding critical vulnerabilities,’ citing the timing between Kimi K3’s release and the attack. However, experts and Coinkite have not confirmed any direct AI involvement, emphasizing that the attack was arithmetic and could have been executed without AI assistance.
Independent researchers reproduced the vulnerability using AI models after the flaw was publicly known, indicating that AI lowered the cost of analysis but did not necessarily find the flaw independently. Coinkite’s own AI review prior to the attack failed to detect the bug, raising questions about AI’s effectiveness in security audits.
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 Speculation
This incident underscores the persistent security risks in hardware wallets, especially when firmware updates unintentionally weaken cryptographic properties. The unconfirmed claims about AI discovering the vulnerability highlight the current limitations of AI in security contexts, emphasizing that complex arithmetic problems like this can be solved with specialized hardware alone.
Moreover, the event raises concerns about overestimating AI's capabilities in cybersecurity, as the breach was ultimately a hardware and firmware issue rather than an AI-driven attack. The fact that AI review failed to catch the bug beforehand suggests that current AI tools are not yet reliable for comprehensive security audits.
As an affiliate, we earn on qualifying purchases.
Background of Coldcard Security and Recent Firmware Updates
The Coldcard Mk3, produced by Canadian firm Coinkite, is marketed as one of the most secure Bitcoin hardware wallets, designed to keep private keys offline. In March 2021, a firmware update was released that introduced a vulnerability by reducing the seed's entropy from 128 bits to about 40 bits, making the generated keys predictable under certain conditions.
Prior to this incident, Coldcard devices were considered highly secure, with their design emphasizing offline key storage. The breach, involving the theft of over 1,800 BTC, marked a significant failure linked directly to the firmware flaw. The attack pattern suggested automated, precomputed key attacks rather than targeted phishing or social engineering.
"We cannot confirm any AI involvement in the discovery or exploitation of this vulnerability. Our review did not detect the flaw beforehand."
— Coinkite spokesperson
Bitcoin hardware wallet with seed generation
As an affiliate, we earn on qualifying purchases.
As an affiliate, we earn on qualifying purchases.
Unconfirmed Role of AI in the Coldcard Breach
There is no verified evidence linking AI models like Kimi K3 directly to the discovery of the firmware flaw. While claims suggest AI may have played a role, experts caution that the vulnerability was arithmetic and could have been exploited without AI assistance. The timing between AI model release and attack remains coincidental, and no concrete proof exists to confirm AI involvement at this stage.
hardware wallet firmware update kit
As an affiliate, we earn on qualifying purchases.
As an affiliate, we earn on qualifying purchases.
Next Steps for Security Verification and AI Role Clarification
Further investigations are expected to clarify whether AI tools contributed to discovering the flaw. Coinkite and independent security researchers will likely conduct additional audits of firmware security and AI's utility in vulnerability detection. The incident may also prompt updates to hardware wallet security protocols and AI-based review processes.
As an affiliate, we earn on qualifying purchases.
Key Questions
Did AI directly cause the Coldcard breach?
No confirmed evidence links AI directly to the discovery or exploitation of the firmware flaw. Claims remain speculative at this stage.
Could AI have helped identify the vulnerability?
While AI models can analyze code and identify weaknesses, the specific flaw was arithmetic and could be brute-forced with hardware alone. AI likely lowered the analysis cost but did not necessarily find the bug independently.
What was the main technical cause of the breach?
A firmware update in March 2021 reduced the seed's entropy from 128 bits to about 40 bits, making the keys predictable and allowing automated theft of Bitcoin.
Will this incident impact Coldcard's reputation?
The breach highlights the importance of rigorous firmware testing. While it may affect trust temporarily, transparency and improved security measures can restore confidence.
Source: ThorstenMeyerAI.com
