"How I Almost Lost Half of My Bitcoins (and Kimi K3 Saved the Day)": Ledger User

• Screen failures on a Ledger Nano S prevented signing transactions and verifying addresses.
• By deploying Kimi K3 and Fable, the user managed to develop recovery software.

A user recently shared their experience trying to safeguard their bitcoins after a vulnerability was detected in Coldcard hardware wallets, exposing the severe technical challenges that can arise during self-custody.

The account shared on X by the user <<@stack2thefuture>> comes in a context where the failure in the random number generator (RNG) of Coldcard's firmware allowed the theft of approximately 2,055 bitcoins in four waves of attacks, according to estimates from Galaxy Research published in early August 2026 by CriptoNoticias.

Facing the imminent risk of being part of the most exposed group, the affected user withdrew their funds in time and decided to resort to their old Ledger Nano S to transfer them to a new multi-signature scheme. <<I started to worry about my old Ledger Nano S, which I knew I had set up without using a password>>, they commented.

However, the hardware's screen was severely deteriorated: <>.

After exhausting almost all access attempts due to a discrepancy in their physical backup --- where their family had noted an 8 instead of a 0 in the PIN --- the user managed to unlock the device.

The visual failure of the device worsened and prevented them from verifying the receiving address. When they gave up and opted to recover the funds using their seed phrase in the Sparrow software, the system indicated that the checksum was invalid, even though they later confirmed that all the words noted belonged to the official BIP39 standard list.

In an attempt to sign the transaction blindly without visual verification, the Ledger threw error 0x6b00, associated with outdated software. Following the technical support instructions to update the firmware, the device's screen failed completely, rendering the equipment unusable, even preventing the entry of the PIN.

This is where the desperation begins.

Saves Their Bitcoins by Creating Offline Recovery Scripts with AI

After exhausting manual attempts to decipher their seed phrase, this person used the Kimi K3 model to program a brute-force solution based on Python. In other words, they would attempt numerous tries until finding the correct seed.

<<Before writing any code, I asked Kimi to interview me about all this>>, they wrote. From there, the software emerged, from the extended public keys (xpub) obtained from Ledger Live and the visual structure in which the words were noted. The resulting script operated autonomously using only the standard library of the language and without requiring an internet connection.

<<To my surprise, my node wasn't even needed. Even more surprisingly, internet wasn't needed either. [...] Therefore, everything could be done completely *offline*>>, they recounted in their post.

Before processing the actual information, the user audited the code using a second artificial intelligence model called Fable. This review detected and corrected a technical flaw in the validation of the xpub that could have interrupted the search.

After fixing the error, the program ran in an offline environment and found the correct seed within minutes by identifying that a single word had been incorrectly recorded, reading <> instead of <>.

Despite the discovery, when importing the corrected phrase into the Sparrow software, the main funds were not initially reflected. This setback occurred because the wallet derived into two different accounts. The default import directed to the SegWit path, while the main capital was located in the Native SegWit path (m/84'/0'/0′).

With the assistance of artificial intelligence, the user configured the correct derivation path, allowing them to access the funds and transfer them to a new multi-signature scheme.

As a conclusion to the incident, the affected user emphasized the need to keep a record of the xpub and test the recovery phrase before depositing funds. To mitigate human errors when recording seeds, they recommended adopting open-source organizational standards like those of the Keybackup project, stressing that all recovery through third-party software should be executed privately to avoid compromising the original words.

The application of this tool highlights a transformation in the security mechanisms of the ecosystem. Kimi K3 is the same artificial intelligence model to which the Bitcoin Red Team allocated 74% of their recent budget, successfully detecting 1,280 high or critical severity vulnerabilities in open-source projects during its early days of work.

This adoption demonstrates that advanced computing models are becoming a fundamental resource for auditing Bitcoin's infrastructure at an institutional level as well as mitigating critical failures in individual custody.