• Manual Email Analysis
  When users report suspicious emails, security teams must manually analyze them for phishing indicators such as spoofed senders, suspicious links, and tone irregularities. This manual process is time-consuming and prone to delays.
• Inconsistent Response Time
  The reliance on human analysts to perform link reputation checks, sandbox testing, and domain blocking coordination leads to inconsistent and often slow responses, allowing potential threats to linger in the environment.
• Limited Human Capacity
  With high volumes of suspicious emails reported daily, security teams are overwhelmed. Prioritization becomes difficult, and some genuine phishing attempts may go undetected.

How Agentic AI Helped

• Autonomous Email Analysis via AI Agents
  The Agentic AI was trained to evaluate phishing indicators using a large language model (LLM). It reviews content tone, sender metadata, and link structures autonomously upon user report.
• Automated Threat Intelligence Checks
  A robotic process automation (RPA) system runs WHOIS lookups, link reputation analysis, and executes sandbox testing for attachments or embedded URLs.
• Human Escalation
  The findings and AI-predicted likelihood of phishing are compiled into a clear summary, which is submitted to a UiPath Action Center or web interface for security team approval.
• Integrated Policy Enforcement
  Upon human approval, the Agentic AI automatically updates Microsoft Defender’s tenant allow/block list based on the decision (Block/Allow), ensuring fast action and consistency with policy.