AI agents are increasingly responsible for handling crypto, executing smart contracts, and managing blockchain data. Recent research highlights their vulnerability to subtle yet powerful attacks. A new paper identifies one new major threat: Memory injection - an attack that embeds malicious instructions into an AI's memory. These instructions persist across sessions, platforms, and even users. ➡️ How it works AI agents in blockchain systems utilize LLMs to: - Understand user instructions - Interact with smart contracts - Execute transactions - Maintain persistent memory These systems heavily depend on context, including current prompts, external data, past decisions, and stored memory. ➡️ Why memory injection is dangerous Memory injection poses a unique threat, distinct from prompt injection, because it: - Activates later across multiple sessions - Mimics legitimate context - Bypasses typical security checks - Can propagate across platforms and users ➡️ Defense strategies Short-term solutions include: - Whitelisting transaction targets - Multi-layer verification for high-risk actions Long-term: - Develop context-aware models that understand their environment, role, and risks, similar to financial professionals. These findings highlight real security risks in AI agent design. A must-read if your systems rely on persistent AI, especially in fintech. Explore the full paper: https://lnkd.in/eHgtiCdq Stress-test AI systems at HackAPrompt 2.0: https://lnkd.in/e-Y_6WR6