Slow Fog and Bitget release AI Agent security report, the security boundaries behind "lobster-style" automated trading

As the application of AI Agents in cryptocurrency trading rapidly heats up, automated trading is transitioning from "tool-assisted" to "autonomous execution." However, at the same time, a series of security risks are also emerging. Recently, the security agency SlowMist and the exchange Bitget jointly released an AI Agent security report, systematically outlining the potential threats and protective systems for Agent automated trading in the current Web3 scenario.

The report combines real cases and security research to analyze the typical security issues faced by AI Agents today, including risks of behavioral manipulation caused by Prompt Injection, supply chain vulnerabilities in plugins and Skill ecosystems, abuse of API Keys and account permissions, as well as potential threats from automated execution leading to operational errors and permission escalation.

The report recommends that users effectively control permissions when using AI Agents for trading, by isolating through sub-accounts, setting API IP whitelists, and establishing continuous trading monitoring and anomaly alert mechanisms. Additionally, it suggests introducing manual confirmation or independent signature mechanisms for high-risk operations to prevent model misjudgments from directly affecting asset security. To facilitate users in implementing security measures, the report includes a trading security self-checklist at the end, helping users quickly identify security risks.

From an industry development perspective, AI Agents are continuously driving the intelligence of Web3 trading, but the construction of security systems still needs to be upgraded in parallel. Establishing a balance between efficiency and controllability will become an important topic of long-term concern for the industry.