Agentic AI is transforming security operations by enabling autonomous agents to efficiently tackle incidents, enhancing decision-making, and automating routine tasks. Its integration into security frameworks allows for real-time threat detection and response, although it comes with risks such as lack of transparency and potential misinterpretation of data. Affected: security operations, cybersecurity, AI systems
Keypoints :
- Agentic AI enables autonomous decision-making in security operations.
- Integrates generative AI for enhanced data interpretation and response.
- Reduces time and errors in incident response through automation.
- Multi-AI-agent systems can efficiently tackle complex challenges collaboratively.
- Potential risks include black-box decision-making and misinterpretation of data.
- Generative AI can enhance both threat detection and incident response capabilities.
MITRE Techniques :
- T1203 – Exploit Public-Facing Application: Agentic AI can identify vulnerabilities in applications through real-time anomaly detection.
- T1071.001 – Application Layer Protocol: AI agents can automate communication between various security tools to streamline responses.
- T1070.006 – Indicator Removal on Host: Agentic AI can autonomously remove malicious artifacts on compromised systems.
- T1499 – Endpoint Denial of Service: The ability of agentic AI to isolate affected devices prevents threats from spreading.
Indicator of Compromise :
- [Domain] malicious.com
- [Domain] example.com
- [IP Address] 192.168.1.1
- [Email Address] attacker@example.com
- [SHA-256] 9c56cc51bc8008a3c8e99ffa176d5598425e4b5c3d06376998d5a14e73bdc9ef
Full Story: https://www.reliaquest.com/blog/agentic-ai-vs-generative-ai-era-of-multi-ai-agent-systems/