Billionaire investor warns Bitcoin will be hacked and go to zero

In this news:

Key takeaways

  • Chamath Palihapitiya warned that Bitcoin could eventually be hacked and collapse to zero.
  • Advances in quantum computing and AI present long-term security challenges for cryptocurrencies.
  • Analysts and experts disagree on the timeline for when quantum computers might threaten Bitcoin.

Billionaire investor Chamath Palihapitiya has warned that Bitcoin (BTC) will eventually be hacked and collapse to zero, citing advances in artificial intelligence (AI) and weaknesses in its security model.

Palihapitiya argued that Bitcoin faces a ceiling on its value and could lose market confidence following a successful attack while speaking on the October 21 episode of Peter Diamandis’ Moonshots podcast. He also questioned whether its decentralized community could implement quantum-resistant security before the technology becomes a practical threat. These comments come after Palihapitiya previously described Bitcoin as a digital alternative to gold and predicted it could reach $200,000.

However, he now argues that its transparent ledger limits financial privacy, potentially reducing its appeal to central banks and other institutions.

“It’s incumbent on these efforts to migrate to quantum-secure, quantum-resistant cryptographic mechanisms, which, as you can see, in the Bitcoin community is basically impossible, because it’s a bunch of people who can’t even agree. I think crypto is a bit lost in the woods. I think eventually it gets hacked. And then it goes to zero,” he said.

The investor also revealed that he no longer holds Bitcoin directly, having exchanged his exposure for equity in Digital Currency Group.

Fears of Bitcoin getting hacked

Fears of Bitcoin being hacked have accelerated after Google Quantum AI’s March 31, 2026, research found that improved quantum algorithms could break the elliptic-curve cryptography used by cryptocurrencies with fewer than 500,000 physical qubits under specified assumptions, roughly 20 times fewer than previously estimated. Researchers urged crypto networks to adopt post-quantum security. Current quantum computers cannot yet break Bitcoin at scale, but advances in algorithms, error correction and hardware could accelerate the threat.

Experts take on Bitcoin being hacked

At the same time, experts disagree on when quantum computers could threaten Bitcoin. Bernstein analysts said in April that crypto networks had three to five years to prepare for post-quantum upgrades, while Benchmark analyst Mark Palmer expects practical attacks to remain decades away. Bitwise cited Charles Edwards’ warning that Bitcoin’s encryption could be threatened by 2029, while Ethereum co-founder Vitalik Buterin has discussed the possibility before 2030. Blockstream CEO Adam Back considers the threat more distant.

Meanwhile, a May 2026 Glassnode analysis estimated that 6.04 million BTC, or 30.2% of the supply, sits in addresses with publicly exposed keys, potentially making them vulnerable to future quantum attacks. A June report by Coinbase’s Independent Advisory Board on Quantum Computing and Blockchain put the figure at roughly 7 million BTC, reflecting differences in methodology.

These holdings cannot be stolen today, and a successful attack would require a sufficiently powerful quantum computer. However, compromising large amounts of Bitcoin, particularly dormant coins linked to creator Satoshi Nakamoto, could trigger market uncertainty and selling pressure.

Impact of AI

Meanwhile, AI presents a separate security risk as highlighted in July 2026, when Anthropic said its Claude Mythos Preview model had identified improved attacks against certain cryptographic algorithms, including a post-quantum signature scheme, though no production systems were affected. On October 16, Anthropic reported that Claude had traced the origins of longstanding elliptic-curve cryptography parameters, stressing that this revealed no cryptographic weakness.

While these findings do not show AI can break Bitcoin’s encryption, advanced models could help identify cryptographic implementation flaws.

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