A comparative review of three tools that address enterprise AI use from different angles — session forensics for coding agents, inline policy enforcement on AI interactions, and endpoint discovery of AI software.
Executive Summary
Purpose
With recent attacks on the AI supply chain, including the compromise of Hugging Face model repositories, AI is moving at a pace no human can keep up with. Three products are frequently discussed together because they address the same problem: AI use inside the enterprise. They are not substitutes. This review sets out how each product works, what it covers, where it falls short, and how the three fit together.
Overview
Falcon for IT finds the footprint, AIDR enforces policy in the path, and ADR reconstructs developer agent behavior. Forensics without enforcement leaves risk unaddressed, and neither works well on AI nobody knew was installed.
Key outcomes
Endpoint AI inventory and classification is a managed capability in Falcon for IT and is not addressed by either of the other two.
Enforcement of AI policy across browsers, applications, gateways, and MCP is available today only from AIDR; ADR does not block in its open-source release.
Forensic reconstruction of coding-agent sessions is unique to ADR, at the cost of a pipeline the organization builds and operates itself.
Executive Summary
AI use inside the enterprise now spans three surfaces that behave differently: workforce use of browser-based assistants, developer use of coding agents on managed endpoints, and first-party applications and gateways calling models directly. No single tool observes all three.
Objectives
Establish what each product does, in operational terms.
Identify the surfaces each one covers and the surfaces it leaves open.
Record the deployment and configuration work each one requires.
Recommend a sequence for organizations that need more than one.
Coverage
Products reviewed
Falcon for IT: AI Discovery & Governance: endpoint AI inventory and governance, delivered through Falcon IT Automation.
CrowdStrike Falcon AIDR: commercial inline GenAI security control.
Uber ADR: open-source Agentic Detection and Response toolkit (Apache 2.0, August 2026).
Falcon for IT — AI Discovery & Governance
CrowdStrike’s endpoint inventory and governance layer for shadow AI, delivered through Falcon for IT and IT Automation.
Overview
The Falcon sensor runs scheduled IT Automation Python tasks on each host, combining several detection methods to identify AI software, models, and service connections. Results roll up into the AI Discovery dashboard, where technologies are classified and governance actions can be run against them. Optional Deep Analysis adds a file index and Software Bill of Materials (SBOM) for richer context.
Capabilities
Discovers AI tools, local models, SDKs, agent frameworks, IDE extensions, MCP servers, and AI service connections across Windows, macOS, and Linux.
Multiple detection methods: process, filesystem, package managers, configuration, registry, environment variables, network, and file magic. Optional Deep Analysis adds file index and SBOM enrichment, covering model weights, secrets, and vulnerable packages.
Classification workflow: Approved, Unapproved, Needs review, In review.
Governance actions (quarantine, block, remove) via platform-specific IT Automation tasks.
Managed console: inventory dashboard, configuration status, and onboarding.
Product limitations
Discovery is scheduled, not per-prompt: the dashboard reflects roughly the last 24 hours of scan results, and first results often take hours after activation.
Sees what is on the endpoint, not chat transcripts or browser GenAI prompts.
Deep Analysis cannot run alongside the legacy File Indexing and SBOM content pack.
Configuration
Enable IT Automation through policies and host groups.
Under Onboarding, enable AI Discovery & Governance (targets and scan schedule) and remove the legacy AIDG content pack if present.
Optionally enable Deep Analysis.
Review the inventory, classify technologies, and tune scope under Configuration status.
CrowdStrike Falcon AIDR
AIDR is CrowdStrike’s commercial inline GenAI security control.
Overview
Collectors capture AI interactions and send them to AIDR, which evaluates policy and returns allow, report, transform, or block before the interaction proceeds. Every event lands in the AIDR console and Next-Gen SIEM. For browser traffic, three layers evaluate in order: Site Access, then Access Rules, then Prompt Rules.
Capabilities
Coverage depends on the number of collectors you deploy.
A single Falcon Endpoint collector deployment enables both the browser extension and Network Inspection integrations. The sensor already includes Network Inspection, so no separate installation is required; the integration is then configured in the Falcon Endpoint policy settings.
Enforcement beyond allow and block: mask, format-preserving encrypt, defang, and redirect, so the interaction proceeds safely instead of failing.
Content detectors are available for PII, secrets and keys, malicious prompts, MCP validation, topics, competitors, and custom entities.
Findings and Visibility dashboards, NG-SIEM events for correlation, and RBAC via AIDR Admin and AIDR Viewer.
Network Inspection extends coverage beyond the Chrome and Edge browser extension to any client that makes an outbound HTTPS request: desktop applications, CLIs, and unsupported browsers. The sensor captures AI traffic on the endpoint and sends it to Falcon Cloud for policy evaluation, and is enabled by default in Falcon Endpoint policies.
Product limitations
Coverage equals collectors deployed. Nothing is monitored by default.
Separate entitlements: AIDR for Workforce (browser) and AIDR for Agents.
Available on the US-1, US-2, and EU-1 clouds only.
The application collector requires code changes; the MCP proxy requires client configuration changes.
Per-interaction visibility: not the full session narrative a coding-agent forensics tool provides.
Falcon Endpoint Collector based Network Inspection currently supports Windows only — Windows 11 version 23H2 or later, or a supported 64-bit version of Windows 10. Arm64 hosts are not supported.
Falcon Endpoint Collector: report-only for network events. Content is not blocked or transformed.
Falcon Endpoint Collector File handling: file attachments from network events are not processed.
Configuration
Confirm the subscription and cloud region; assign the AIDR Admin and AIDR Viewer roles.
Register the collector in the AIDR console and assign it a policy.
Deploy by type: browser extension via GPO, Intune, or Jamf; gateway configuration; application SDK; or MCP proxy.
Run in Report Only mode, tune with Sandbox and Playground, then enforce.
Uber ADR
Uber’s Agentic Detection and Response toolkit is a flight recorder for AI coding agents. It reads local logs from tools such as Cursor, Claude Code, and Codex, normalizes sessions to JSON, and can run research-grade detection. It does not block in the open-source release.
Overview
ADR runs as a command-line sensor installed on each developer endpoint. On a schedule you define, it reads the session log files that coding agents already write locally, normalizes them to JSON, and writes the output to a directory you choose. Agentic traffic is not intercepted and nothing runs in the interaction path.
ADR triages in two stages, the way a SOC does. A low-cost model first reviews every session and escalates anything questionable to a more capable model, which investigates the escalated cases for deeper context. The design is a cost control: deep LLM analysis of every session would be prohibitive at 10,000 sessions a day.
Reconstruct the session. The sensor turns raw agent logs into one normalized record. The user, host, model, project, the prompt, the agent’s reasoning, and every tool call with its result, in order.
Tier 1 triage. A low-cost LLM pass reviews every session, tuned to favor recall over precision. Uncertain cases are escalated rather than dismissed.
Tier 2 deep review. Only escalated sessions reach a reasoning agent, which analyzes them against three inputs: the source code of the MCP tool that was called, threat intelligence on known agent attack techniques, and your written security policy.
Produce a finding. The result is a verdict with rationale, written as JSON.
The point of the design is intent, not outcome. Endpoint tooling sees that a file was read or a network call was made, while ADR sees the prompt that asked for it, the tool description that influenced the agent, and the chain that led to the action.
Capabilities
Full session reconstruction on developer endpoints across seven or more agent tools: prompt, reasoning, tool calls, and outcomes.
Product limitations
No blocking in the open-source release: Prevention and the red-teaming Explorer stayed internal at Uber.
Batch, not live: findings appear on the next scheduled collection run.
Blind to browser ChatGPT and Claude, and to anything without local agent logs.
You own the pipeline: SIEM shipping, storage, UI, RBAC, retention, and redaction.
The detector runs on your own LLM keys; cost scales with session volume.
Configuration
Schedule collection — adr-sensor for all supported tools, --source cursor for one, -- output-dir to set the output path. The default window is the last two weeks; --all-history widens it.
Build the downstream path yourself: redact, then ship normalized JSON to your store or SIEM.
Optionally set LLM API keys to run the two-tier detector, and budget per-token spend.
Product Comparison
Onboading Sequence
Where an organization has both a shadow-AI inventory problem and an enforcement mandate, the three operate together in the following order.
Falcon for IT: discover and classify the AI footprint.
Falcon AIDR: control browser, gateway, application, and MCP traffic.
Uber ADR (optional): deep forensic reconstruction on high-risk engineering cohorts; correlate in NG-SIEM by user, host, and time, using separate parsers so ADR events are not tagged as AIDR.
Next Steps
With recent attacks on the AI supply chain, including the compromise of Hugging Face model repositories, AI is moving at a pace no human can keep up with. Consortium is available to help you visualize how AI is being used in your environment today while helping you to implement controls to reduce your risk. Uber ADR would be a paid engagement to configure in your environment where the others are complimentary.
Choosing between these layers depends on where your AI exposure actually sits, and that is what we help clients establish. Consortium can take this from comparison to decision:
Proof of Value: Run AIDR and Falcon for IT AI Discovery in your environment against your own traffic and endpoints, with our team handling design, deployment, and readout.
AI Security Assessment: Map where AI is used across workforce, developer, and application surfaces, and identify which surfaces are unmonitored today.
AI Risk Review: Test current controls and policy against agentic and GenAI attack techniques, and prioritize the gaps by business impact.
Talk to us about which of the three fits your environment, or start with an assessment and let the findings decide.
About Consortium
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