AgentArmor v1.4.2

AgentArmor v1.4.0 — Multi-agentic only

AgentArmor is now a multi-agent AI red-teaming platform. The offline analysis mode has
been removed: every scan runs capability-aware attack-graph planning, an LLM judge, and
confidence scoring. This release also fixes real correctness bugs in the multi-agentic engine.

Changed

• Offline analysis mode removed — the GUI offline↔cloud picker is gone; the CLI and API
  run multi-agent (cloud) analysis on every scan.
• Analysis API key now required — scans without a provider key are rejected with a clear
  error. Set AGENTARMOR_ANALYSIS_API_KEY, or configure it in Settings / AgentArmor.toml.
• The local L1–L4/meta detection engine still runs as the under-the-hood scorer; local
  model-file scanning (--model) is unaffected.

Fixed (multi-agentic engine)

• Module targets now receive the real attack — red-team attacks against agent/MCP/RAG
  targets send the generated attack (harness prompt, RAG query, MCP tool-parameter injection)
  instead of running a static probe and relabelling the display text.
• Budget metering — the LLM judge and web attack planner now record token/cost usage
  against the budget governor instead of bypassing it.

Added (multi-agentic engine)

• Per-path campaign coverage — a finding now retires only its attack path and the campaign
  continues across the remaining paths, instead of stopping at the first finding.

---

Windows (recommended)

Download AgentArmor_1.4.0_x64-setup.exe or AgentArmor_1.4.0_x64_en-US.msi from the assets below.

1. Run the installer
2. Open AgentArmor — no Python install required
3. Add your analysis provider API key in Settings
4. Choose a scan profile → run scan → review grouped findings → download reports