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Prompt injection is a class of vulnerabilities in which crafted input manipulates a large language model into ignoring its original instructions and following the attacker's instead. Unlike a bug in traditional code, it exploits the model's inability to reliably separate trusted instructions from untrusted data — which makes it especially dangerous for AI agents that read external content, call tools, or act on code, funds, and infrastructure in fintech and Web3 systems.
On this page you'll find articles on how prompt injection works, direct and indirect attack vectors, real-world incidents against LLM-integrated products, why it can't be patched like SQL injection, and the defense-in-depth strategies for building AI agents and LLM applications that stay safe in production.
What prompt injection is, why it can't be patched like SQL injection, how real attacks hit Slack AI, Copilot, and coding agents, and the defense-in-depth strategy that actually works.
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