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Recently, malicious Bots have appeared in the Solana ecosystem, stealing users' Private Keys through the open source project pumpfun-pumpswap-sniper-copy-trading-bot and sending them to the attacker's server. The security team analyzed and found that the project contains malicious code hidden in the configuration files, advising users to remain vigilant about unknown projects and to operate in a secure environment.

In the field of Crypto Assets, many "air" projects receive high valuations due to a lack of actual products, a phenomenon that stems from the effects of game theory. Project founders attract investment through vague yet exciting statements, leading investors to blindly chase investments due to feelings of fear of missing out (FOMO) and information asymmetry, ultimately forming an investment model dominated by imagination and marketing. Although this situation is reasonable, it also stifles the development of real products and the healthy growth of the market.

Last week, there were a total of 15 financing events in the global blockchain industry, with a total amount exceeding $224 million. The main areas involved include Decentralized Finance, Web3 gaming, AI+Web3, and infrastructure, with notable financing cases including an Islamic DeFi project, a Swiss cloud platform, and a UK cloud mining platform.

On November 1st, tech entrepreneur Musk shared an interesting image on a social media platform, triggering a Fluctuation in the Crypto Assets market. The image featured a Shiba Inu wearing a shirt with the social platform's logo, and Musk added a GRIN emoji. This move seems to have had a positive impact on certain Crypto Assets. Market data shows that the price of DOGE coin has seen a significant rise, breaking through the $0.14 mark. As of the time of reporting, the trading price of DOGE coin was $0.14072, with a 24-hour increase of 15.16%. This phenomenon again highlights the potential influence of social media and celebrities on the Crypto Assets market. Investors and market observers are closely monitoring this development to assess its possible long-term impacts.

The article summarizes 7 common misconceptions in the development of AI Agent projects, including blind imitation, insufficient sales capability, following trends, premature Token issuance, neglecting the feasibility of MVP, lack of clear KPIs, and balancing user and investor expectations. It provides corresponding countermeasures and emphasizes that success requires attention to user needs and substantive value.