Streamlining the Security Analyst Experience

Key Takeaways

• An Agentic SOC utilizes AI Agents and Skills to automate workflows like detection engineering, alert triage, and threat hunting.
• Elastic Security integrates AI via Agent Builder, which is LLM-agnostic and supports conversational triage and Attack Discovery.
• Automated workflows can perform immediate response actions, such as isolating vulnerable hosts and creating centralized cases.
• Organizations must carefully evaluate the risk profile and permissions of AI-driven security workflows before deployment.

Detection Availability

• YARA Rules: No
• Sigma Rules: No
• Snort/Suricata Rules: No
• KQL Queries: No
• Splunk SPL Queries: No
• EQL Queries: No
• Other Detection Logic: No

No specific detection rules are provided, though the article mentions Elastic's library of over 1,700 pre-built SIEM rules.

Detection Engineering Assessment

EDR Visibility: None — The article discusses SOC methodology and product features rather than specific threat behaviors. Network Visibility: None — No network-based threats or indicators are discussed. Detection Difficulty: Moderate — Not applicable as this is a conceptual article about AI in the SOC.

Hunting Hypotheses

Hypothesis	Telemetry	ATT&CK Stage	FP Risk
Adversaries may execute uncommon or anomalous processes on compromised hosts during an active intrusion.	Process creation events (e.g., Event ID 4688, Sysmon Event ID 1)	Execution	High

False Positive Assessment

• Low

Recommendations

Immediate Mitigation

• N/A

Infrastructure Hardening

• N/A

User Protection

• N/A

Security Awareness

• Evaluate the risk profile, data access, and permissions of AI-driven security workflows before enabling them in production environments.