Canadian Technology Magazine has been tracking a shift that should make every business owner, investor, and everyday internet user pay attention: AI is making it dramatically easier to discover software vulnerabilities that remained hidden for years. A recent hardware wallet theft, in which tens of millions of dollars in Bitcoin were drained in under an hour, is a brutal illustration of what that can look like in practice.
This is not only a crypto story. It is a warning about the entire digital world: banking systems, email accounts, cloud services, mobile apps, browser extensions, payment platforms, and the software supply chains underneath them all. The issue is not that every AI system is malicious. The issue is that AI can now search for weaknesses at a scale, speed, and persistence humans simply cannot match.
For Canadian Technology Magazine, the central question is simple: what happens when attackers and defenders both have access to tools that can comb through enormous amounts of code, uncover subtle flaws, and turn those flaws into real-world attacks?
Canadian Technology Magazine and the Bitcoin Wallet Wake-Up Call
The theft involved Coldcard, a Bitcoin-only hardware wallet produced by Coinkite, a company well known for emphasizing security. Hardware wallets are meant to be one of the safest ways to hold crypto because private keys are kept offline rather than exposed on an internet-connected computer.
That is why this incident is so unsettling. The people affected were not necessarily careless newcomers clicking obvious scams. Many were security-conscious crypto users who had taken the usual precautions. They used dedicated hardware, protected their keys, and assumed the wallet’s core cryptography was doing what it was supposed to do.
The reported weakness was not a broken Bitcoin network or a failure of the blockchain itself. It was an issue in key generation. A private key should be selected from such an unimaginably large range of possible values that guessing one is effectively impossible. In this case, a long-standing bug allegedly generated keys from a much smaller and weaker pool.
Once an attacker understood that weakness, the process became much more dangerous:
- Generate every possible private key from the reduced keyspace.
- Derive the public address associated with each possible key.
- Check which public addresses contain Bitcoin.
- Sort the addresses by balance.
- Automate withdrawals, beginning with the largest holdings.
Roughly 1,200 wallets were reportedly drained in about 41 minutes, with early estimates placing the loss around US$70 million and broader estimates exceeding US$100 million. The attacker did not need to crack a giant random number by brute force. They allegedly exploited a flawed implementation that shrank the problem into something computationally manageable.
That distinction matters enormously. Canadian Technology Magazine readers should understand that strong security can be undermined by one small engineering mistake in a critical layer of the stack.
A Five-Year Bug Meets a New AI Era
The alleged vulnerability had existed for more than five years. That means countless people, developers, researchers, and security professionals had opportunities to spot it. Nobody did, at least not in time to stop the damage.
Then, within a period when more capable AI models and open-source alternatives were becoming widely discussed, the flaw was found and used. There is no public proof establishing that AI was used in this particular theft. Still, the timing captures the broader concern: code that humans considered adequately reviewed may now be vulnerable to automated analysis at a completely different level.
Picture millions of tireless software agents crawling repositories, dependencies, documentation, old releases, public code archives, and configuration files. Some belong to responsible vendors and security researchers trying to find flaws before criminals do. Others may not have good intentions.
That is the uncomfortable reality highlighted by Canadian Technology Magazine: the same capabilities that can harden systems can also help identify the weakest link in those systems.
Open-source software has historically had an important security advantage. More people can inspect the code, identify problems, and propose fixes. That logic still matters. But there is now a flip side. If code has been public, it may be searchable by increasingly capable automated systems. A flaw that survived human review can become visible much faster once the right model is pointed at it.
This does not mean open source is inherently unsafe, nor does it mean closed code is secure by default. Closed systems still depend on vendors, libraries, integrations, cloud infrastructure, payment processors, and third-party tools. Security is never just one company’s code. It is the entire chain of technology that supports the product.
Canadian Technology Magazine: Why This Is Bigger Than Bitcoin
Crypto is especially exposed because stolen funds can move quickly, transactions can be irreversible, and there may be no central authority capable of freezing an account or reversing a transfer. If an attacker gets a valid private key, the network sees a legitimate transaction, even if the key was obtained through a vulnerability.
But the underlying pattern applies far beyond digital wallets. Banks, insurers, healthcare providers, retailers, governments, and small businesses all rely on vast layers of software. A large financial institution may have its own security team, but its operations can still depend on older databases, vendor applications, APIs, cloud providers, browser-based portals, and open-source packages.
One weak component can be enough.
Canadian Technology Magazine sees this as a supply-chain problem as much as an AI problem. You may trust your bank, accounting platform, customer relationship system, or payment provider. But how many external services does that platform rely on? How many code libraries sit under the interface? How many older systems are still connected behind the scenes?
AI-assisted code review could expose flaws in places that no one has looked closely at for decades. Databases and protocols that have been treated as stable may contain bugs that were simply too difficult for humans to find efficiently.
AI Is Getting Better at Breaking Mathematical Assumptions
There is another layer to this story: cryptography itself. Security does not rely only on clean software implementation. It also relies on mathematical assumptions, meaning the belief that certain problems are extremely difficult to solve with available computing power.
AI models are becoming better at mathematics, pattern discovery, and combining known concepts in unusual ways. They are not creating alien mathematics out of nowhere. They are remixing existing knowledge and identifying connections that human researchers may have missed.
One reported example involved HAWC, a post-quantum digital signature candidate considered in a process connected to future encryption standards. After extensive expert review, an AI system reportedly found a new attack approach that substantially reduced the scheme’s effective security strength. The candidate was not a widely deployed system, which is good news. Finding the issue before broad adoption is exactly what strong security review is for.
But it reinforces the concern raised by Canadian Technology Magazine: if AI can find previously unknown ways to weaken a future cryptographic candidate in dozens of hours, what could it discover in the encryption systems already deployed across the economy?
Quantum Computing Could Compress the Timeline
Post-quantum cryptography is based on a straightforward concern. A sufficiently capable fault-tolerant quantum computer could potentially break some of the public-key cryptographic systems used today. Organizations are therefore planning long migrations to quantum-resistant methods.
Some public plans use 2035 as a target for completing that migration. Yet respected researchers in quantum computing and error correction have suggested that machines capable of threatening deployed cryptography could arrive closer to 2029.
That difference is not a minor scheduling dispute. It could be the difference between an orderly transition and a security scramble.
AI may speed up progress in quantum computing as well. Machine learning systems are already being explored for quantum error correction, one of the major obstacles to making quantum hardware reliable enough for useful large-scale computation. That creates a difficult situation: the tools helping society improve its defences may also accelerate the technologies that pressure existing defences.
Canadian Technology Magazine believes the most important point is not to predict an exact date. No one can responsibly promise whether the critical moment is 2029, 2035, or later. The point is that migration plans built around slow technological progress may no longer be adequate if AI sharply accelerates discovery.
Harvest Now, Decrypt Later
Governments and sophisticated organizations have long had an incentive to collect encrypted information, even when they cannot read it immediately. The idea is simple: store the data now, then decrypt it later if new tools make that possible.
This is sometimes called a harvest-now, decrypt-later strategy. It matters because encryption does not only protect today’s transactions. It protects personal communications, intellectual property, financial data, business plans, government information, and access credentials that may retain value years from now.
The hardware wallet event offers a smaller version of this same logic. An attacker may discover a vulnerability but delay action. They can map possible targets, prepare automation, identify valuable accounts, and strike only when the operation is ready. When the attack begins, it can unfold with shocking speed.
For Canadian Technology Magazine, this is why preparation cannot begin after a public breach. Organizations need to identify sensitive data, reduce unnecessary exposure, review old systems, and build a plan before a weakness turns into an incident.
AI-Assisted Audits Are Finding Problems Humans Missed
There is some genuinely good news. AI is not only an attacker’s tool. Bitcoin security teams and red-team researchers have reportedly used AI-assisted auditing across hundreds of open-source Bitcoin repositories, producing thousands of findings. Dozens were categorized as critical and hundreds as high severity.
That is alarming, but it is also exactly what should happen next. Vulnerabilities that were invisible are becoming visible. The responsible path is to find them, validate them, patch them, and communicate clearly with affected users.
The concern is the uneven distribution of defensive capability. Large technology companies and major financial institutions can afford elite security teams, extensive audits, advanced tools, and direct access to leading AI systems. Smaller banks, startups, regional organizations, and open-source projects may not have the same resources.
Canadian Technology Magazine expects that imbalance to become a major cybersecurity issue. The institutions with the strongest defences may become safer faster, while smaller organizations may struggle to keep pace.
Practical Steps to Reduce Your Exposure
There is no magical setting that makes anyone invulnerable. Still, basic security habits matter more when vulnerabilities can be discovered and weaponized faster. The goal is not panic. The goal is to reduce the damage one compromised app, account, device, or password can cause.
Install updates quickly
Software updates are often security patches. Delaying them creates a longer window in which a known flaw can be exploited. Keep operating systems, browsers, mobile apps, routers, firmware, and security tools current.
Use a password manager and unique passwords
Every important account should have a unique, long password. Reused passwords turn one breach into multiple breaches. A password manager can generate and store strong credentials without forcing you to memorize dozens of random strings.
Protect email as a high-value account
Email is often the recovery channel for banking, shopping, cloud storage, social accounts, and work systems. If someone controls your email, they may be able to reset passwords across the rest of your digital life.
Use strong two-factor authentication, preferably through an authenticator app or a hardware security key rather than SMS where possible. Canadian Technology Magazine considers email protection one of the highest-return security improvements available to most people.
Review connected apps and old permissions
Many people have connected bank accounts, email accounts, cloud drives, calendars, or social profiles to services they no longer use. Those forgotten connections can become attack paths.
- Remove apps and services you do not recognize or no longer need.
- Review browser extensions and uninstall unnecessary ones.
- Turn off Bluetooth, AirDrop, remote desktop, and similar services when they are not needed.
- Check which devices are signed into important accounts.
- Use virtual credit cards for online purchases when your financial provider offers them.
Compartmentalize risky activity
If you experiment with unfamiliar software, AI agents, code, browser tools, or untested services, avoid doing it on the device that holds your most sensitive information. A separate machine or account can limit the blast radius if something goes wrong.
Think through a simple question: if this device were compromised today, what else could the attacker reach? Banking credentials, private documents, cloud backups, saved browser passwords, cryptocurrency wallets, work accounts, and personal email should not all be exposed from one careless click.
Restart phones and devices regularly
Some threats can persist in memory while a device remains powered on. Regular restarts are not a complete defence, but they are a sensible habit, especially for phones that many people leave running continuously for weeks or months.
Canadian Technology Magazine: Do Not Confuse Convenience With Security
There is a real tension here. People often prefer smaller services, independent apps, decentralized tools, and niche platforms. That preference can be healthy. Competition and openness matter.
At the same time, large providers may currently have an advantage in this new AI security environment because they can spend billions on security research, monitoring, incident response, and advanced tooling. A major browser, operating system, or financial institution may have more resources to detect and patch emerging threats than a tiny vendor with a limited team.
That does not mean every large company is safe or every small company is unsafe. It means security should become a serious factor in decisions about where to store money, which apps to trust, what extensions to install, and which services deserve access to sensitive data.
The uncomfortable bet is that attacks will increase as AI-assisted vulnerability discovery becomes more common. Maybe that prediction will be wrong, and that would be excellent. But waiting for certainty is not a security strategy.
Canadian Technology Magazine recommends treating this moment as an opportunity to clean up your digital life. Update the software. Remove old permissions. Lock down email. Use unique passwords. Separate experimental activity from critical accounts. Assume that somewhere in the software stack, there may be a weakness nobody has found yet.
Because increasingly, somebody or something may be looking for it right now.
Canadian Technology Magazine FAQ
Did AI cause the Bitcoin hardware wallet theft?
There is no public proof that AI was used in the reported wallet attack. However, the incident occurred amid growing concern that advanced AI tools can identify vulnerabilities in software much faster than traditional manual review.
Why are hardware wallets still vulnerable?
Hardware wallets can protect private keys from many online threats, but they still depend on secure firmware, correct key generation, trustworthy supply chains, and careful user practices. A flaw in any critical component can undermine the protections users expect.
What is the most important cybersecurity step to take first?
Start by securing your primary email account with a unique password and strong app-based or hardware-based two-factor authentication. Then use a password manager, update devices promptly, and review old app connections and browser extensions.
Should people stop using crypto because of AI security threats?
The key lesson is not that every crypto asset is doomed. It is that users should understand the risks of wallet software, key management, encryption changes, and irreversible transactions. Security practices and vendor scrutiny matter more than ever.
Why does post-quantum encryption matter now?
Organizations need time to replace older cryptographic systems. If quantum computing and AI progress faster than expected, systems that delay planning could face a difficult and expensive transition under pressure.
