I'm curious if Is AutoGen the future of enterprise AI agents? in the context of a Security Operations Center (SOC). Can we have agents that constantly monitor logs and "talk" to each other to correlate events? I’m worried about "false positive" loops where agents keep escalating non-issues because they are over-analyzing the chat history. Has anyone stress-tested this framework for real-time security monitoring?
3 answers
Using AutoGen for Cyber Security requires a very different prompting strategy. In early 2024, we built a prototype for automated incident response. We had a "Monitor" agent, a "Forensics" agent, and a "Manager" agent. To prevent the "false positive" loop you mentioned, we implemented a "Grounding Tool." Before the Forensics agent could escalate, it had to query a real-time threat feed API to see if the IP or hash was truly malicious. This prevented the agents from just "hallucinating" a threat based on a weird-looking log entry. It's powerful, but it needs real-world data anchors to stay reliable.
Pamela, how did you handle the latency? In a SOC, seconds matter. Doesn't the back-and-forth between agents take too long to respond to an active breach?
We found that using a local model for the initial filtering and then escalating the "interesting" logs to an AutoGen crew with GPT-4 saved us a ton of money.
Diane's hybrid approach is the only way to make this cost-effective. You can't feed every single log to a multi-agent chat. You have to be strategic about what gets "discussed" by the crew.
Kenneth, for "active" breaches, you still need traditional automated rules (SOAR). Where AutoGen shines is in "Post-Incident Analysis" or "Hunting." It can spend 10 minutes digging through 10,000 logs to find the "low and slow" lateral movement that a traditional rule might miss. It’s an analyst's assistant, not a replacement for a firewall. We treat the crew as a Tier 2 analyst that works 24/7. It doesn't need to respond in milliseconds; it just needs to find the needles in the haystack that the humans are too tired to look for.