Module 17 Lesson 2: Securing LangChain "Chains" and "Agents"

LangChain is powerful because of Agents (AIs that can use tools). But an agent is only as safe as the constraints you put on it.

1. Tool Sandboxing (The Firewall for Tools)

If you give an agent a PythonREPLTool or a ShellTool, you must run that code in an isolated environment.

• The Attack: os.system('cat /etc/passwd').
• The Defense:
  1. Run your LangChain server in a Docker Container.
  2. Use a Read-only file system.
  3. Disable all network access for that container except for the specific API it needs.

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2. "Human-in-the-loop" for Sensitive Tools

LangChain allows you to add an Acknowledge step before a tool is executed.

• Best Practice: For any tool that can Write or Delete data (e.g., send_email, delete_user, transfer_funds), the agent should stop and ask for a human to click a button.
• Implementation: Use the human_in_the_loop=True flag in your agent configuration.

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3. Securing Agent Memory

Agents "remember" past conversations using BufferMemory or SummaryMemory.

• The Risk: If an attacker injects a command in Message #1, and the agent "remembers" that command in its summary, the attack persists even after you "clear" the current prompt.
• The Defense:
  1. Use ChatMessageHistory with a database that supports TTL (Time to Live).
  2. Periodically "Sanitize" the memory using a second LLM to remove any instruction-like text.

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4. Constraint-based Orchestration

Instead of a generic agent, use Structured Chains.

• Generic Agent: "Give me a goal and I will use any tool to reach it." (UNSAFE).
• Structured Chain: "Step 1: Use Tool A. Step 2: Pass result of A to Tool B." (SAFE).
• By hardcoding the "Path" the data takes, you prevent the AI from "Choosing" to use a tool in a way you didn't intend.

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Exercise: The Chain Hardener

1. Why is an "Agent" more dangerous than a simple "Sequential Chain"?
2. What is the most dangerous LangChain tool? (Hint: Does it involve eval()?).
3. How can you use "Metadata" on a tool to ensure it only runs for "Subscribed" users?
4. Research: What is "LangGraph" and how does it provide more control over agent state than basic LangChain?

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Summary

Securing LangChain is about Boundaries. You must define exactly what tools an agent can use, what data it can remember, and most importantly, when it needs to stop and ask for human permission.

Next Lesson: Knowledge base safety: LlamaIndex security and data connectors.