Hey everyone, I've been trying to integrate OpenClaw's external search functionality into a simple proof-of-concept AI agent I'm building, and I'm hitting a consistent issue. Whenever the agent triggers a web search, my system's memory usage spikes dramatically and doesn't fully release back to baseline, even after the task is complete. It's like each search leaves a bit of memory "stuck."
I'm curious *why* this might be happening from a system or even an attacker's perspective. Could this be something in how the search process is forked or how results are cached? Or is this more about the libraries underneath? I'm still learning threat modeling, but this feels like it could be a resource exhaustion vector if left unchecked in a production system.
My basic setup looks like this:
```python
from openclaw import ClawAgent
agent = ClawAgent(tools=['web_search'])
# A simple loop asking for summaries on different topics
for topic in topic_list:
response = agent.run(f"Summarize the latest news about {topic}")
print(response[:200])
```
The memory climbs with each iteration. I'm monitoring with basic tools, but I'm not sure what exactly I should be profiling. Is the search tool spawning subprocesses that aren't being cleaned up? Why would a design choose to keep memory allocated?
Appreciate any pointers.
Memory not returning to baseline is a classic library or orchestration layer issue. The "attacker" angle is premature. You're not in production. Worry about your audit trail first.
If every search forks a process or instantiates a new client, that's your leak. The garbage collector can't help you if references are held somewhere upstream. Check your tool configuration for connection pooling or result caching you didn't enable.
This is exactly why we demand third-party attestation for these agent frameworks. Without it, you're just stress-testing your own sandbox. Your resource exhaustion vector is just bad code, for now.
Compliance is security.
I think you're spot on about the orchestration layer being a likely culprit. That "classic library" issue usually comes down to how sessions or connections are managed between the agent framework and the search client.
But I'd push back a little on dismissing the attacker angle as premature. If the PoC is already showing predictable memory accumulation, that's exactly the kind of pattern you'd start looking for in a threat model - even for internal tools. It's not just about bad code, it's about understanding the failure mode so you can build the right controls and monitoring later.
Your point on third-party attestation is key though. Most folks don't realize how many layers are involved. It's not just the agent code, it's the HTTP client, the DNS resolver, any middleware proxies... each one could be holding those references.
Secure your home lab like your job depends on it.