Summary
- Anthropic’s Claude Fable 5 model offers stronger reasoning and coding abilities while attempting to block dangerous uses. A more powerful Mythos 5 variant is restricted to vetted security users.
- Security experts warn that advanced AI will not invent fundamentally new crypto hacks, but will dramatically speed up finding misconfigurations and constructing ways of exploiting weaknesses such as social engineering, exposed keys and flawed signing flows.
- This year’s largest DeFi losses, totaling more than $840 million, have mostly stemmed from human error and operational failures rather than smart-contract bugs.
The newest AI model from Anthropic, which gives users access to stronger, faster reasoning and coding capabilities, lands in a crypto market beset by security problems and could well exacerbate them.
The company released Claude Fable 5 on Tuesday, the first public model in the Mythos class and, Anthropic says, its most powerful yet. So powerful, in fact, the company released two versions: one for widespread use and the other for more restricted distribution.
The public version sports stronger reasoning and coding ability while blocking the most dangerous uses. A less-hamstrung counterpart, Claude Mythos 5, is available only to vetted users in cybersecurity and critical infrastructure.
Experts say Mythos can find and chain zero-day vulnerabilities, or previously unknown software flaws, and help turn a bug into a working attack. Anthropic says the software tries to intercept possible attack vectors by detecting high-risk requests. Once identified, they are routed to a weaker model, Claude Opus 4.8.
The company says this specific fallback triggers in fewer than 5% of sessions. It also said in a blog post that specialized cybersecurity teams and more than 1,000 hours of external bug-bounty work found no universal way of breaking the system.
Still, Anthropic recognizes that the system is unlikely to be foolproof and says it expects determined, well-funded attackers to keep trying because the capability is valuable.
“The uplift from Mythos-level capabilities is valuable to many adversaries—for instance, those who could financially gain from cyberattacks—and we therefore expect them to be motivated to try to circumvent our safety measures,” the firm said in the post.
“… not a reliable control against a determined adversary.”
Identifying a weakness in a target, however, is not the biggest innovation AI brings to a hacker’s toolbox. The key facility is superhuman speed, and the limitations introduced into the AI models may not be strong enough to overcome that.
“Current AI guardrails raise friction,” said Charles Guillemet, the chief technology officer at hardware-wallet maker Ledger, in an email to CoinDesk. “They are not a reliable control against a determined adversary.”
The shift is less about AI inventing new kinds of hacks and more about how long it takes to create them, he said. A reasoning model can “diff every commit, grep every config, and enumerate every misconfiguration at machine speed,” referring to steps in the process of software development.
Crypto is unusually exposed because software failure can become a financial loss almost immediately.
Social engineering
DeFi protocols have lost more than $840 million to hacks in the first five months of the year, DefiLlama data shows. April alone accounted for more than $600 million, the worst month on record for the decentralized finance industry.
It’s just likely to come sooner rather than later.
Artificial IntelligenceHackDeFi
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