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AGENTIC SEARCH

Threat Scenario — Possible Lunar Spider Activity

Agent Verdict: Suspicious
Confidence: High

Summary: Suspicious activity on ADMIN-WKS-129 by mont.donald — rundll32.exe, encoded PowerShell, and AD recon suggest an attempt at persistence and internal reconnaissance.

Event Timeline

• 11:18 AM: Suspicious rundll32 Execution
• 11:19 AM: Create / Modify Schtasks
• 11:21 AM: Encoded PowerShell Command
• 11:22 AM: AdFind Commands

AGENTIC DETECTION ENGINEERING

Activity

1. Intel Report Intake: Gather daily threat intel.
2. Detection Gap Analysis: Identify detections to fill gaps.
3. Create Detections: Build from available feeds.
4. Deploy Detections: Roll out new detections.
5. Validate Detections: Run attack simulations.
   • Human Approval Gate: APPROVED

Anvilogic Platform

Onboard Agents

Parse, normalize, and map data from any source — no data engineering project per feed.

Search Agents

One query across Splunk, Snowflake, Sentinel, S3, and more — without moving the data.

Detect Agents

From threat intel to validated, deployed detection logic on every connected platform.

Investigate Agents

Automated triage, enrichment, and severity scoring before an analyst opens the case.

Blueprints

Tie your agents together into step-by-step workflows — security automated end to end.

Why Trust Anvilogic

Practitioner-built. Proven in production.

• Roland Costea, CISO, Enterprise Cloud Services, SAP: "We were early adopters of the unified workflow Anvilogic and Databricks provide."
• T-Mobile Security Leadership: "Anvilogic is central to our SOC strategy."
• Guang Wang, Sr. Director, Security Operations & Engineering, Alteryx: "Anvilogic is the perfect solution because it doesn’t depend on any specific underlying data lake or SIEM."

Performance Metrics

• Onboard Agents: 10× Faster data onboarding
• Search Agents: ↓$1M+ Reduction in SIEM costs
• Detect Agents: ↓85% Reduction in MTTD
• Investigate Agents: <2 min Time to triage per alert

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