AI-Powered Autonomous Cyber Threat Investigation & Response

Inspiration

Cybersecurity teams receive thousands of security alerts every day, making it difficult to identify genuine threats quickly. We were inspired to build an AI-powered system that automates threat investigation, connects suspicious activities, and helps security teams respond faster to cyberattacks.

What it does

Our project, CyberSentinel AI, is an autonomous cyber threat investigation and response platform. It analyzes security logs, detects suspicious activities, correlates related events, investigates potential attacks using specialized AI agents, assesses threat severity, and recommends appropriate response actions with human approval.

How we built it

We designed a multi-agent AI architecture using Python, FastAPI, and LangGraph. Specialized agents handle log analysis, threat intelligence, event correlation, incident investigation, risk assessment, and response recommendations. We use machine learning for anomaly detection and React for an interactive security dashboard. Security events and investigation results are stored in a database.

Challenges we ran into

Designing communication and coordination between multiple AI agents. Identifying genuine threats while reducing false-positive alerts. Correlating security events from different sources. Generating reliable threat severity scores using evidence. Ensuring safe response actions through human approval.

Accomplishments that we're proud of

Designed a multi-agent AI-based cybersecurity investigation system. Combined threat detection, event correlation, and automated investigation into one platform. Developed an approach to reconstruct potential attack sequences. Focused on explainable threat analysis and human-supervised response. Created a solution addressing a real-world cybersecurity challenge.

What we learned

We learned how agentic AI can support cybersecurity operations, how to analyze and correlate security logs, and how to use machine learning for anomaly detection. We also gained experience in API development, multi-agent orchestration, threat intelligence, risk assessment, and secure system design.

What's next for AI-Powered Autonomous Cyber Threat Investigation & Response

Integrate real-time security monitoring using Wazuh. Connect cloud platforms such as AWS for activity-log analysis. Improve threat detection using advanced machine learning models. Expand MITRE ATT&CK-based attack mapping. Add more threat intelligence sources. Develop controlled automated response capabilities with human approval. Make the platform scalable for organizations, enterprises, and SOC teams.