Cryptocurrency hacks reached a record $1.1 billion in losses during the first half of 2026, according to Blockaid's report.
In the first half of 2026, cryptocurrency projects faced unprecedented losses of approximately $1.1 billion due to hacking incidents, according to a report from Blockaid. This marks the highest number of confirmed exploits for any six-month period, with 212 successful attacks recorded, making it the "most hacked half-year in history." Despite the increase in incidents, the total amount stolen was lower than in previous years, particularly when compared to last year's spike driven by a $1.5 billion hack of Bybit.
Blockaid noted that 55% of the stolen funds were linked to North Korean actors, with significant attacks on Drift and KelpDAO resulting in losses of $285 million and $292 million, respectively. Analysts expect continued activity from these hackers in the future.
Key strategies employed by hackers included social engineering tactics via LinkedIn and the compromise of multi-signature wallet signers, which were involved in two of the four largest incidents during this period.
While Blockaid's estimates indicate a total loss of $1.1 billion, other reports, such as Immunefi's June 2026 Ecosystem Update, estimated industry losses around $972 million across 207 incidents. Quill Audits reported similar figures, focusing on $935.3 million lost in 87 DeFi hacks. Immunefi also highlighted that losses from DeFi projects in 2026 were still 74% lower than the peak in 2022.
The blockchain most affected by these hacks was Ethereum, with losses of $332 million, followed closely by Solana at $326 million. Blockaid pointed out a trend of "large-scale code exploits" on Ethereum, while attacks on Solana primarily targeted the infrastructure of signers rather than smart contracts.
Looking ahead, Blockaid warned of potential risks associated with artificial intelligence exploits, citing the hack of Bankr, which involved $216,000, as a concerning trend. This incident highlighted vulnerabilities that could allow for future attacks on AI agents through techniques like prompt injections.
