Related: The future of digital self-governance: AI agents in crypto“AI model poisoning involves injecting malicious data into training samples, which then becomes embedded in the model parameters,” co-founder of blockchain security firm SlowMist “Monster Z” told Cointelegraph.“In contrast, the poisoning of agents and MCPs mainly stems from additional malicious information introduced during the model’s interaction phase.” “Personally, I believe [poisoning of agents] threat level and privilege scope are higher than that of standalone AI poisoning,” he said.
SlowMist identified the attack vectors from pre-released MCP projects it audited, which mitigated actual losses to end-users. However, the threat level of MCP security vulnerabilities is very real, according to Monster, who recalled an audit where the vulnerability may have led to private key leaks — a catastrophic ordeal for any crypto project or investor, as it could grant full asset control to uninvited actors.
Loud said it’s “not difficult” to implement such security checks to prevent malicious injections or data poisoning, just “tedious and time consuming” — a small price to pay to secure crypto funds.
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