New research alert 🚨 from my group, “Blockchain Address Poisoning” (Tsuchiya et al.), to appear at
@usenixsecurity 2025 (https://arxiv.org/abs/2501.16681)! As a follow-up, we also developed a real-time detection system: https://cryptotrade.cylab.cmu.edu/poisoning/ and
https://x.com/toxin_tagger
Background: Crypto wallet addresses are usually impossible to memorize. As a result, users often select addresses from their recent transaction history, which facilitates phishing-like attacks: blockchain address poisoning.
The attacker generates “lookalike” addresses that resemble the victim’s recipient’s address, engages with the victim to “poison” the transaction history, and fools the victim into sending their assets to the attacker by mistake.
We developed a detection system and performed measurements on two years of ETH and BSC. We identified 13x the number of attack attempts reported previously—in all, 270M on-chain attacks targeting 17M victims. 6,633 incidents have caused at least 83.8M USD in losses.
We discovered a few large attack entities using clustering techniques. Larger groups are vastly profitable and win against smaller attack groups. We uncovered some attack strategies, such as populations they target, success conditions, and cross-chain attacks.
We simulated the lookalike address generation process across various software- and hardware-based implementations. One large attacker group appears to use GPUs for this attack! The paper also discusses some defenses.
TLDR: Address poisoning is a thing.
Paper: https://arxiv.org/abs/2501.16681
Real-time website: https://cryptotrade.cylab.cmu.edu/poisoning/
Real-time twitter bot:
https://x.com/toxin_tagger
(No Mastodon bot yet, soon I hope).