Key Highlights
- Advanced AI can autonomously exploit smart contracts, creating real financial risks and challenging current blockchain security practices.
- AI-driven exploits are becoming faster, cheaper, and more effective, shrinking the time developers have to fix vulnerabilities.
- The focus on utility over tokens is critical, as AI highlights risks in speculative crypto projects with limited real-world value.
Artificial intelligence (AI) is starting to pose real financial risks, as AI agents can now exploit vulnerabilities in blockchain smart contracts. Researchers at Anthropic, working with MATS and Anthropic Fellows, recently put advanced AI models to the test against these smart contract weaknesses.
As per the study, researchers tested Claude Opus 4.5, Claude Sonnet 4.5, and GPT-5 using the Smart Contracts Exploitation benchmark called as SCONE-bench, consisting of 405 real contracts exploited between 2020 and 2025. Results show not only that AI-driven exploitation is possible but also that it might represent a significant economic risk.
The research focused on trying to quantify the cyber capability of AI in a controlled, simulated environment. When tested on contracts post-dating the knowledge cutoff in March 2025, the exploits developed by the agents tallied $4.6 million in simulated funds.
In addition to the historic contracts, Sonnet 4.5 and GPT-5 scanned 2,849 newly deployed contracts with no previously known vulnerabilities. They found two new zero-day exploits that reaped simulated revenue of $3,694 at a cost of $3,476 for GPT-5. This shows that smart-contract exploitation driven by AI is feasible and cost-efficient.
AI performance and economic implications
SCONE-bench measures the dollar value of exploits, unlike conventional cyber benchmarks. Researchers simulated attacks on platforms like Ethereum, Binance Smart Chain, and Base, estimating losses using historical token prices.
Of these, 10 AI models successfully exploited 207 contracts from the 405 benchmark problems, which corresponded to potential losses of $550.1 million. Researchers then used the same 10 models on 34 problems that we exploited after March 1. Together, Opus 4.5, Sonnet 4.5, and GPT-5 exploited 19 of these contracts, with the Opus 4.5 alone yielding $4.5 million.
These findings have collectively set a basic benchmark for how much economic impact AI agents might have in real-world applications. One test discovered a flaw in a token contract where a public function could be repeatedly used. The AI exploited this to inflate token balances, generating a simulated profit of about $2,500. Another vulnerability allowed the AI to withdraw fees it shouldn’t have, creating a potential gain of around $1,000 in the simulation.
The operational cost of scanning all 2,849 contracts with GPT-5 averaged about $1.22 per scan, while the average revenue per exploit was $1,847, yielding a small net profit of $109. Newer models’ increased efficiency decreased token consumption by more than 70%, resulting in faster and less expensive exploits in the future.
Rapid evolution of AI capabilities
Researchers found that the money AI could make from exploiting smart contracts doubled roughly every 1.3 months last year. Smarter thinking, better tools, and longer-term planning are behind this growth. As a result, developers have less time to fix vulnerabilities before AI can take advantage
Open-source platforms are the first to be checked by AI, but private software will likely face the same pressure as AI gets smarter. These tools can also help by finding and fixing security issues before they’re exploited.
Broader blockchain implications
The study shows real-world blockchain effects. Ethereum developers explained that old standards like HTTP 402, along with Ethereum Improvement Proposal 3009, could let AI handle stablecoin payments automatically. Kevin Leffew and Lincoln Murr said these autonomous agents could end up using Ethereum more than any human users.
Meanwhile, earlier this year, Binance Co-Founder Changpeng Zhao warned that many AI crypto projects focus on token launches rather than practical utility, a trend reflected in a 61% market decline for AI-related cryptocurrencies since December 2023.
In a March 17 post on X, CZ stated, “Launch a coin only if you have scale. Focus on utility, not tokens.”
Anthropic’s research shows that AI can independently exploit smart contracts and cause measurable financial losses. Developers and investors need to address vulnerabilities and focus on practical applications rather than speculative tokens.
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