Ledger executives argue that artificial intelligence is amplifying existing wallet security weaknesses rather than proving hardware wallets are fundamentally broken. The $116 million Coldcard theft, which drained roughly 1,816 Bitcoin (BTC) from over 5,200 addresses starting July 30, exposed a firmware flaw that weakened seed generation, but the real lesson, according to Ledger leadership, is about how AI changes the threat landscape for all digital asset custody.

What Went Wrong With Coldcard's Seed Generation?

Coldcard maker Coinkite disclosed that a firmware problem introduced in 2021 caused the device's seed generation process to rely on a software pseudorandom number generator instead of the intended hardware-based path. This flaw reduced the effective entropy, or randomness, that protects private keys. On older Mk2 and Mk3 devices, entropy dropped to approximately 40 bits; on newer affected models, it fell to roughly 72 bits. For context, strong cryptographic security typically requires entropy levels far higher than these figures.

TRM Labs, a blockchain intelligence firm, tracked four separate theft waves that collectively drained the Bitcoin from affected wallets. The losses totaled close to $116 million at the time of discovery. The incident sparked concern across the hardware wallet industry, with competitors like Ledger and Trezor moving quickly to reassure users that their own devices use certified hardware-based random number generators without software fallbacks.

How Is AI Changing Wallet Security Risks?

Ian Rogers, Ledger's chief human agency officer, outlined three ways artificial intelligence is reshaping the threat environment for crypto custody and beyond. Rather than framing the Coldcard incident as proof that hardware wallets are unsafe, Rogers emphasized that AI tools are making it cheaper and faster for attackers to discover existing vulnerabilities in any system.

• Vulnerability Discovery: AI gives attackers stronger tools to search for and identify weaknesses in wallet firmware, cryptographic implementations, and other security mechanisms without requiring deep manual expertise.
• Software Development Speed: Autonomous AI agents can accelerate the pace at which attackers develop exploits and refine attack strategies, compressing timelines that once took weeks into days or hours.
• Credential and Secret Access: AI agents deployed in enterprise environments may gain access to sensitive systems including email, credentials, payment data, and internal communications, expanding the attack surface beyond crypto wallets to institutional infrastructure.

"Wherever your assets are stored, you should be interested in the level of security that's protecting them," said Ian Rogers, Ledger's chief human agency officer.

Ian Rogers, Chief Human Agency Officer at Ledger

Rogers compared the challenge of controlling AI agent permissions to a parent deciding when a teenager should receive car keys. The decision, he argued, should depend on context and the specific task at hand. Ledger is developing tools designed to separate an agent's ability to operate a wallet from its control over private keys, creating a layer of protection even if an AI system is compromised.

Is This the First Time Ledger Has Flagged Randomness Issues?

The Coldcard incident is not the first time weak randomness has threatened crypto wallet security. Ledger's Donjon security team previously identified a similar flaw in Trust Wallet's browser extension in November 2022. That vulnerability reduced seed entropy to just 32 bits, a level so low that attackers could feasibly brute-force private keys. Ledger reported the issue to Trust Wallet, and the company patched it.

These recurring discoveries suggest that randomness generation remains a critical but sometimes overlooked component of wallet security. Even small deviations from proper cryptographic practices can create exploitable weaknesses, especially as AI tools make it easier for attackers to test and verify their findings at scale.

How to Evaluate Your Wallet's Security Standards

• Hardware-Based Randomness: Verify that your wallet uses a certified hardware true random number generator rather than relying on software-based pseudorandom generation, which can be predictable under certain conditions.
• Secure Element Certification: Check whether the device's security components are certified by independent standards bodies, indicating third-party validation of the cryptographic implementation.
• Firmware Update History: Review the wallet manufacturer's track record for releasing security patches and firmware updates, and ensure you can easily apply updates to your device.
• Transparency on Vulnerabilities: Look for manufacturers that publicly disclose security issues they discover and explain how they were resolved, rather than staying silent about flaws.

The broader implication of Rogers' warning extends beyond individual wallet users. As AI tools become more accessible and powerful, organizations holding digital assets, whether in self-custody or institutional custody arrangements, need to reassess their security posture. The Coldcard case demonstrates that even well-intentioned hardware wallet makers can introduce subtle flaws that remain hidden until attackers have the tools and motivation to find them.

For crypto holders, the incident underscores the importance of understanding not just which wallet they use, but how that wallet generates and protects the cryptographic secrets that control their assets. The Coldcard theft was not caused by a fundamental flaw in the concept of hardware wallets or self-custody; it was caused by a specific implementation error. However, AI's role in making such errors easier to exploit suggests that security standards and verification processes will need to evolve alongside the threat landscape.