Artificial intelligence (AI) has ceased to be an industry that can be analyzed in isolation. Its advancement is already modifying the security of financial systems, competing for energy, infrastructure, and capital, and is changing the way vulnerabilities are detected.
To put it clearly and directly: AI no longer needs to be the central theme of a story to end up being part of it.
Proof of this is the hacking of Coldcard hardware wallets, which resulted in the theft of over 2,000 BTC. This episode accelerated a review of the infrastructure surrounding the digital currency. A distinction that is important to highlight simply because the Bitcoin protocol was not compromised.
As reported by CriptoNoticias, Bitcoin Red Team, a coalition of security researchers, used AI to audit that ecosystem on a large scale. After analyzing 501 open-source projects, it reported nearly 7,958 vulnerabilities, with over 1,288 classified as high or critical severity.
This episode shows how far AI is starting to extend. A story that began with the security of a hardware wallet ended up involving models capable of reviewing thousands of projects for flaws. And that is just one of the points where both industries began to intersect.
Calle BTC, a developer and researcher from Bitcoin Red Team, described the current moment on August 13 as a "massive collision" between decades of open-source code developed by humans and the new AI models.
For years, wallets, Lightning Network implementations, and other tools accumulated errors that needed to be found through traditional audits. Now, part of that work can be automated and executed on a much larger scale.
The results were not exactly reassuring. "Everything is broken, Bitcoin is on fire," Calle BTC expressed.
Here it is necessary to make a brief clarification because this phrase needs precision. The researcher is not saying that the Bitcoin protocol has been compromised, but rather that the review is exposing deficiencies in the software built around it. In fact, he believes that discovering them is part of the necessary process to strengthen the ecosystem.
AI thus takes on a dual role. The same capability that can facilitate the search for a vulnerability can be used to find and fix it before it is exploited.
Bitcoin Red Team has already completed a basic scan of nearly all the free software related to the currency, according to Calle BTC. High and critical severity flaws were communicated to the project leaders, although the speed of response depends on the maintenance of each one.
The researcher believes that this work should continue. Instead of isolated audits, he proposes ongoing processes that combine different AI models, analysis techniques, and human review.
If error detection can be automated, defense will have to accelerate.
The intersection between both industries appears far from the code. Companies dedicated to Bitcoin mining are allocating part of their resources to the business of data centers and high-performance computing. MARA, Riot Platforms, and Bitdeer, among others, have advanced in this direction as demand related to artificial intelligence grows.
The movement introduces competition for energy, electrical capacity, land, and infrastructure, resources that are essential for mining. At the same time, it opens a new potential source of income for companies whose profitability is conditioned by the price of BTC and the cost of electricity.
Competition also extends to capital. The growth of companies linked to AI has turned the sector into one of the major investment destinations, forcing Bitcoin-related firms to compete for financing with an industry that requires extraordinary amounts of money to expand.
The relationship, therefore, changes depending on where you look. AI can help protect the infrastructure around Bitcoin while simultaneously competing with its industry for some of the necessary resources to grow.
For Calle BTC, what is happening in the Bitcoin ecosystem foreshadows a process that will reach other technology industries.
There are signs that this movement has already begun. Organizations such as the International Monetary Fund (IMF) and the Financial Stability Board (FSB) are analyzing how AI can increase the speed and scale at which vulnerabilities in traditional finance are found and exploited.
The architecture of a bank and that of Bitcoin are completely different. Their vulnerabilities are also different. What they share is an increasing dependence on software at a time when it can be analyzed at a speed and scale previously difficult to achieve.
That same pattern appears in other areas. In energy, the expansion of data centers modifies demand and forces competition for electrical capacity. In markets, AI companies attract capital that could be directed towards other sectors. And in cybersecurity, new tools can serve both to find a flaw and to correct it.
Coldcard started as a story about the security of a hardware wallet. Following its consequences led to AI models auditing thousands of vulnerabilities. By broadening the perspective a bit more, the same technology reappears in mining, energy, infrastructure, and markets.
There lies the fundamental change. AI no longer needs to be the subject of an industry to modify it. It can appear as a tool, competitor, risk, or source of income. AI has stopped seeking a niche. Now the niche belongs to everyone.
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