AI Detection and Response

Detect agent risk.
Contain it fast.

General Analysis monitors coding agents, internal copilots, MCP servers, enterprise production agents, and shadow AI at the execution layer. See what each agent touched, why it mattered, and which response was taken.

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Agent inventory

AI agent surface

Enterprise, local, unknown, and shadow AI activity

Agents, endpoints, identities, tools, data, incidents, and response actions

Known agents
Monitored
Unknown agents
Under review
Tool paths
Mapped
Incidents
Prioritized
AgentLicenseSurfaceActivityRiskResponse
Claude Code
inventory record
Enterprise licenseCoding agentRepo, shell, filesMediumCommand gates
Codex
inventory record
Developer licenseCoding agentWorkspace tasksMediumRepo policies
Cursor
inventory record
Team licenseIDE assistantEditor + terminalMediumData controls
OpenClaw
inventory record
Self-hostedDesktop agentLocal automationHighLocal policy
DeepSeek
inventory record
Shadow AIBrowser + APICustomer exportCriticalBlock upload
Direct MCP server
inventory record
Unknown integrationTool gatewaySensitive tool outputCriticalPause MCP

Built for live agents

The response loop for agentic systems.

Observe01

Discover and trace every agent

Find known and unknown agents, then follow behavior through instructions, retrieved content, tools, browsers, files, and downstream changes.

Detect02

Score risky intent

Correlate signals across the execution chain to identify exfiltration, privilege abuse, destructive actions, and policy drift.

Respond03

Contain at the right layer

Block a command, require approval, redact sensitive output, pause a connector, or quarantine the session with evidence intact.

Harden04

Feed controls back

Promote confirmed incidents into red-team tests, runtime policies, ownership tasks, and regression suites.

aidr-policy.yaml
# Correlate events before choosing a response.

incident: agent-data-exfiltration
sources:
  - agent_inventory
  - endpoint_activity
  - prompt
  - retrieval_context
  - mcp_tool_result
  - terminal_command
match:
  sensitive_data: present
  destination: external
  agent_intent: unauthorized_transfer
respond:
  - block_tool_call
  - quarantine_session
  - open_security_case
evidence: full_trace_replay

Endpoint-native control

Coverage where agents actually execute.

AIDR runs from the managed endpoint so it can see local agents, browser copilots, IDE assistants, terminals, MCP servers, and shadow AI even when traffic never passes through a gateway.

Local first, context aware

The endpoint sensor records the action where it happens. The platform enriches that trace with identity, repository, SaaS, data, and MCP context so response decisions are tied to impact.

Local signal

  • Browser prompts
  • IDE and coding agents
  • Terminal commands
  • Local file access

Platform context

  • Identity and owner
  • Repository and SaaS scope
  • MCP server and data source
  • Secrets and document sensitivity

Response point

  • Block tool call
  • Pause MCP route
  • Stop command
  • Open incident with trace

Endpoint sensor

See local agent behavior

Capture prompt entry, browser use, IDE and terminal activity, file reads, MCP calls, package installs, and desktop automation before the action leaves the machine.

Agent inventory

Tie every agent to an owner

Map enterprise licenses, developer tools, self-hosted agents, browser assistants, direct MCP servers, and shadow AI into one inventory.

Tool and data path

Follow sensitive access

Correlate prompts and model traffic with repositories, secrets, local files, documents, SaaS scopes, APIs, and MCP data sources.

Response layer

Stop the risky action

Block an upload, pause an MCP route, stop a command, revoke a scope, require approval, or open an incident while preserving the full trace.

Detection lifecycle

AI incidents you can actually work.

AI Detection and Response gives security teams a clean operating layer for agent behavior. It connects live execution traces with asset context and turns risky behavior into contained, reviewable incidents.

Agent discovery and attribution

Find enterprise-managed and shadow agents, then attach owner, user, identity, platform, data access, tool permissions, and business context.

Full execution graph

Link prompts, responses, retrieved documents, tool calls, file access, commands, memory updates, and external actions to the same incident.

Agent-native detections

Identify direct and indirect prompt injection, tool result poisoning, data exfiltration, credential exposure, unsafe autonomy, and MCP misuse.

Evidence and response

Preserve policy version, affected asset, owner, exact trace, response action, and replay material while triggering containment.

How AI incidents move

Connect

Instrument the agent surface

Integrate with AI gateways, SaaS copilots, coding assistants, MCP servers, browser controls, endpoint telemetry, and identity systems.

Correlate

Add asset and posture context

Merge runtime events with agent inventory, shadow AI findings, tool permissions, repository ownership, knowledge-base sensitivity, and red-team findings.

Classify

Separate normal work from attack paths

Evaluate intent and impact across the session so a single benign-looking event can still be tied to a harmful chain.

Contain

Trigger the appropriate response

Block, redact, pause, revoke, quarantine, route to a human approver, or open a case with the evidence package attached.

Improve

Turn incidents into controls

Convert confirmed cases into detections, regression tests, red-team campaigns, and remediation tasks tied to the affected owner.

Containment

Response actions that fit the incident.

The product should reduce blast radius without turning every AI alert into a shutdown. Each response is tied to severity, asset sensitivity, user role, and the action the agent attempted.

Action01

Block

Stop a tool call, terminal command, external request, or data export before it reaches the next system.

Action02

Scope

Reduce permissions, pause a connector, revoke a token, or require approval for the rest of the session.

Action03

Quarantine

Hold a suspicious agent session while preserving the full trace and business context for review.

Action04

Retest

Replay the incident against future model, prompt, tool, and policy changes so the fix stays in place.

Guides and whitepapers

Field guides for the agent surface.

AIDR depends on knowing where agents live, what they can reach, and how to contain them. These guides cover the highest-priority deployment patterns behind that operating model.

Securing Coding Agents

General Analysis

Whitepaper

6 min read

How to Secure Coding Agents

A concise summary of the General Analysis technical whitepaper on securing Claude Code, OpenAI Codex, Cursor, Windsurf, Devin, GitHub Copilot, and Claude Cowork.

Download PDF

Securing Claude Cowork

General Analysis

Deployment guide

16 min read

How to Secure Claude Cowork

Claude Cowork brings Claude Code-style agentic work to local files, browsers, apps, plugins, and scheduled tasks. Here is how to put a middleman proxy, browser controls, computer-use limits, and enterprise monitoring around it before using it on real work.

Read guide

Detecting Shadow AI

General Analysis

Detection guide

13 min read

How to Detect Shadow AI

A practical guide to detecting shadow AI across browser extensions, SWG endpoint agents, network telemetry, SaaS logs, endpoint agents, AI gateways, and MCP gateways.

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MCP Server Security

General Analysis

PRIMER

16 min read

MCP Server Security: A Threat Model for Agent Tool Supply Chains

MCP servers put executable code, tool schemas, credentials, and agent context in one path. This primary-source threat model covers nine attack classes, current CVEs, and the controls that contain them.

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Claude Cowork vs Claude Code

General Analysis

FRAMEWORK

10 min read

Claude Cowork vs Claude Code: Security Differences for Enterprise

Claude Cowork and Claude Code share an agentic architecture but ship very different enterprise controls. A primary-source comparison of sandbox, network, audit-log, MCP, and decision-framework differences for security teams.

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Claude Compliance API

General Analysis

PLAYBOOK

13 min read

How to Audit Claude with the Compliance API

Anthropic's Compliance API exposes activity events, Claude.ai content, organization settings, and supported Cowork and Claude Code session transcripts. This guide explains current coverage, setup, retention, exclusions, and the controls that still need a separate enforcement layer.

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