Topic
AI Agent Security & Prompt Injection Defense
14 posts on ai agent security & prompt injection defense — part of ai agents & automation on the n4n AI blog.
Why agents with file access need stricter guardrails
AI agents file access guardrails are critical because prompt injection turns file contents into commands; sandboxing, scoping, and audit logs are key defenses.
Sandboxing untrusted tool output for AI agents
A practical guide to sandboxing untrusted tool output for AI agents: isolation patterns, validation code, and pitfalls when building agentic systems.
Least-privilege design for multi-tool AI agents
Practical guide to least-privilege design for multi-tool AI agents: scope credentials, isolate execution, validate inputs, and test against prompt injection.
Jailbreaking AI agents: common techniques and defenses
Practical guide to jailbreaking AI agents: exploit techniques like prompt injection and defensive architecture with tool scoping, validation, and routing.
How to secure API keys used by autonomous AI agents
Practical steps to secure API keys AI agents use: scoped tokens, gateway proxying, secret rotation, and isolation to block prompt-injection theft.
How to isolate agent memory from untrusted context
Step-by-step engineering guide to isolate agent memory from untrusted context in LLM agents, with runnable code for sanitization and tests.
How to build permission scopes for AI agent tool access
Practical guide to building permission scopes AI agent tools: model tools as scoped capabilities, enforce at dispatch, filter by session, test against injection.
How to audit AI agent actions for security review
A practical end-to-end guide to audit AI agent actions security: instrument tool calls, enforce policies, store immutable logs, and review traces.
How malicious web pages can hijack browsing agents
Analysis of how malicious web pages hijack browsing agents via prompt injection, with concrete code examples and a defensive architecture for engineers.
Data exfiltration risks in autonomous AI agents
Autonomous agents introduce novel data exfiltration paths via tool calls and prompt injection. We analyze the risks and practical defenses for engineers.
What is prompt injection and how it targets AI agents
Prompt injection AI agents is an attack where untrusted input hijacks an LLM's instructions. Learn how it works, real examples, and defenses.
The OWASP Top 10 for LLM applications, explained
A practitioner's guide to the OWASP Top 10 LLM applications: defining each risk, showing how to threat-model against them, and debunking common misconceptions.
How to test AI agents for prompt injection vulnerabilities
Practical steps to test AI agents prompt injection vulnerabilities with a reproducible harness, sample attacks, and cross-model validation. Learn to build and run it.
How to defend AI agents against indirect prompt injection
Practical steps to defend against indirect prompt injection in LLM agents: isolation, validation, least privilege, and adversarial testing with runnable code.
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