
Enterprises are deploying AI agents that autonomously access Jira, edit tickets, change priorities, and modify sensitive project data — while security teams have zero visibility. A single misconfigured agent edited a CONFIDENTIAL payroll credential ticket across 6 fields in under 7 minutes. AgentGuard caught it, blocked every action, and generated an audit report in real time. AgentGuard is a runtime governance platform that sits between AI agents and enterprise systems. It monitors every Jira action in real time, classifies risk, detects AI-originated behavior, and produces audit trails a compliance officer can actually sign. Four Governance Layers: Real-Time Action Monitoring - every Jira action (CREATE, EDIT, ASSIGN, DELETE) is captured via REST API with full changelog context. Actor, timestamp, field, old value, new value all logged. Multi-Signal AI Detection - identifies whether actions came from humans, AI agents (Claude, GPT), or Atlassian Intelligence using five signals: content patterns, Atlassian template structure, API origin behavior, velocity detection (inhuman speed), and structural similarity across tickets. Rule-Based Policy Engine - DELETE on compliance tickets = BLOCKED. Edits to CONFIDENTIAL content = BLOCKED. CRITICAL priority escalations = FLAGGED. Every decision is transparent and explainable — not a black box. Prompt Inspection via Lobster Trap - Veea's deep prompt inspection layer analyzes AI-generated ticket content for injection patterns, credential exposure, and data exfiltration signals. Declared versus detected intent is shown side by side. Every action shown in AgentGuard comes from a live Jira project. Claude Haiku autonomously created tickets tagged [AI-GENERATED]. Atlassian Intelligence rewrote a CONFIDENTIAL payroll ticket. AgentGuard detected both — real data, real governance, real audit trail.
19 May 2026