[AI Security] Exploring Behavioral AI for Runtime Threat Detection

[u/No-Creme-5778]

Hi everyone,

I’ve been experimenting with an open-source project called BPFense AI focused on behavioral runtime detection and anomaly analysis.

Main areas I’m exploring:

• local AI inference
• telemetry-driven behavioral analysis
• TensorFlow + IsolationForest pipelines
• ensemble threat scoring
• deterministic replay validation

I’m mainly looking for technical feedback and research direction suggestions from people working in:

• AI security
• runtime detection
• malware behavior analysis
• adversarial ML
• eBPF/security telemetry

Project:
https://github.com/Anilk880/BPFense_ai_core

Would appreciate thoughts on:

• detection methodology
• dataset/replay strategies
• behavioral modeling approaches
• real-world runtime security use cases

Thanks.