Just started working with the Anthropic Agent SDK and I'm a bit worried about the default tool permissions. When I create a new agent, it seems like all my registered tools are just... available. 😅
For a simple weather agent, I tested adding a file read tool and it could access anything. Shouldn't we be explicitly granting permissions per tool? Here's what my setup looks like:
```python
@tool
def read_file(path: str):
with open(path, 'r') as f:
return f.read()
agent = AnthropicAgent(tools=[read_file, get_weather])
```
Is there a built-in way to scope this that I'm missing? Coming from web dev, this feels like having no authentication on an API endpoint by default. What are others doing to lock this down?
Yeah, that's exactly why I'm trying to build my own permission layer wrapper! It's wild that they just expose everything.
I'm doing a hacky thing where I wrap each tool function with a check. Something like `if "file_read" in allowed_tools: call_real_tool()`. But it feels like I'm rebuilding what should be built in.
Do you think the SDK team assumes we're only using "safe" tools in development? Because I'm trying to use this for a Pi project with actual file access...
Yeah, that's the default behavior. It's a dev-first design choice, probably because they assume you're only hooking up tools you trust for that specific agent.
Your web dev comparison is spot on. No built-in scoping that I've seen. In production, you need to handle it at the tool definition layer. I do something similar to what you're thinking:
- Wrap the actual file operation in a function that validates the path against an allowlist.
- Or better, create a dedicated `safe_read_file` tool that only has access to a specific directory. Don't give it the raw `open`.
For your example, I'd change the tool to something like:
```python
ALLOWED_PATHS = ["./weather_data/"]
@tool
def read_weather_file(filename: str):
full_path = os.path.join(ALLOWED_PATHS[0], filename)
# Normalize path and check it's still within allowed directory
if not os.path.commonpath([os.path.normpath(full_path), ALLOWED_PATHS[0]]) == ALLOWED_PATHS[0]:
return "Error: Path not allowed."
with open(full_path, 'r') as f:
return f.read()
```
You're not missing anything, the SDK just puts the security burden on you.
Log everything, alert on anomalies.
Oh man, welcome to the exact same panic I had six months ago! You're totally right, it feels wrong coming from any other background. That web dev comparison hits home - it's like deploying a Flask app with `app.config['SECRET_KEY'] = 'dev'` and calling it a day.
What you're missing is that the SDK really is built for speed in prototyping, not for safety out of the box. There's no built-in scoping mechanism, you have to bake it into your tool definitions themselves.
What I ended up doing for my home server agents was creating a permission decorator. I wrap my actual tool functions with a check against a simple JSON config that maps agent names to allowed tool names. It's not elegant, but it works. So my `read_file` becomes `agent_safe_read_file(path, agent_id)` and it checks the config first.
Makes startup a bit slower, but at least I can sleep at night knowing my grocery list agent can't suddenly decide to read my SSH keys. Have you looked at how you'd structure that allowlist?
lab.firstname.net
Yep, that's the exact approach! The path normalization check is crucial. I've been burned by relative path tricks before, so I actually wrote a little helper function for my homelab agents. It's a bit more paranoid, checking for symlink escapes too.
```python
def is_path_safe(user_path, allowed_base):
# realpath resolves symlinks, which avoids chained symlink attacks
real_user = os.path.realpath(os.path.normpath(user_path))
real_base = os.path.realpath(os.path.normpath(allowed_base))
return real_user.startswith(real_base + os.sep)
```
What's wild is that you're right, this *is* the production solution - we're all just reinventing basic ACLs in our own scripts. Makes me wish the SDK had a permission decorator we could just drop in. 😅
Do you think a common library for this would gain traction, or is everyone's use case too specific?
Automate the boring parts.
That Flask dev key comparison is perfect, it's exactly the same kind of pitfall. Your decorator approach is the right way to go. I'm doing something similar but driven from a central runbook config, so the permission mapping is external to the code.
One thing I'd add to your setup - you mentioned the config check makes startup slower. That's a red flag for me operationally. If you're loading and parsing a JSON file on every tool call, you're adding latency and I/O. I'd move that to an in-memory cache on agent initialization. Load the permission map once when the agent spins up, then your decorator just checks the cached dict.
Actually, that's a good pattern for any runtime config an agent needs. Makes me think we should all be building these agents like little services, with a proper config phase before they go live.
What does your agent log look like?