📢 Gate Square #MBG Posting Challenge# is Live— Post for MBG Rewards!
Want a share of 1,000 MBG? Get involved now—show your insights and real participation to become an MBG promoter!
💰 20 top posts will each win 50 MBG!
How to Participate:
1️⃣ Research the MBG project
Share your in-depth views on MBG’s fundamentals, community governance, development goals, and tokenomics, etc.
2️⃣ Join and share your real experience
Take part in MBG activities (CandyDrop, Launchpool, or spot trading), and post your screenshots, earnings, or step-by-step tutorials. Content can include profits, beginner-friendl
Google AI Agent Uncovers Critical SQLite Flaw Before Exploitation
HomeNews* Google used its AI-powered framework to spot a major security flaw in the open-source SQLite database before it was widely exploited.
Google described this security flaw as critical, noting that threat actors were aware of it and could have exploited it. “Through the combination of threat intelligence and Big Sleep, Google was able to actually predict that a vulnerability was imminently going to be used and we were able to cut it off beforehand,” said Kent Walker, President of Global Affairs at Google and Alphabet, in an official statement. He also said, “We believe this is the first time an AI agent has been used to directly foil efforts to exploit a vulnerability in the wild.”
Last year, Big Sleep also detected a separate SQLite vulnerability—a stack buffer underflow—that could have led to crashes or attackers running arbitrary code. In response to these incidents, Google released a white paper that recommends clear human controls and strict operational boundaries for AI agents.
Google says traditional software security controls are not enough, as they don’t provide the needed context for AI agents. At the same time, security based only on AI’s judgment does not provide strong guarantees because of weaknesses like prompt injection. To tackle this, Google uses a multi-layered, “defense-in-depth” approach that blends traditional safeguards and AI-driven defenses. These layers aim to reduce risks from attacks, even if the agent’s internal process is manipulated by threats or unexpected input.
Previous Articles: