If you're giving an AI agent a wallet, put these guardrails outside the model
Summary
A practitioner shares best practices for securing AI agents with crypto wallets: keep private keys out of the model, enforce limits in signing-service code rather than prompts, use allowlists, simulation, logging, and a kill switch to defend against prompt injection and overspending.
Similar Articles
What guardrails do you add before launching an AI Agent app publicly?
A developer reflects on critical safety measures—such as spending caps, rate limits, and fallback models—that should be in place before launching an AI Agent app publicly to avoid hidden costs and unexpected behaviors.
Securing AI Agents against financial fraud
Discusses methods to protect AI agents from being used in financial fraud schemes.
How are you protecting action-taking AI agents from prompt injection?
A discussion on securing action-taking AI agents against prompt injection, arguing that backend controls, tool restrictions, transaction limits, and human approval matter more than prompt-level defenses. The author invites practitioners to share their real-world mitigation strategies.
Don't hand your AI agent your personal email. Give it a mailbox of its own.
Advises giving AI agents their own managed email inbox with policy guardrails rather than using personal email to avoid prompt injection risks, using Nylas CLI as a solution.
lessons from running AI agents that trade real money on-chain, unsupervised 24/7
Lessons from building autonomous AI agents that trade on-chain memecoins unsupervised, highlighting that execution reliability matters more than model cleverness, self-reflection beats larger context, and hard guardrails are essential.