AI Agent Exposure Review
A fixed-scope assessment for an agreed business unit or workflow set. Scope, access, testing, timing, deliverables, fees, and responsibilities are confirmed in writing.
Independent AI agent security
Control what AI agents can do.
Fugitive Intelligence helps security and platform teams map in-scope agents, define action-level authority, require accountable approval for consequential actions, and preserve structured evidence. Start with a fixed-scope AI Agent Exposure Review.
Fugitive Control concept
Illustrative
Customer Support Agent
REQ-7F3A
Requested action
Issue refund
Transaction
$1,250 USD
Target system
Payments API
Customer tier
Enterprise
Agent identity verified Pass
Customer scope matched Pass
Refund exceeds autonomous limitEscalate
Human approval required
The action would pause for an authorized finance approver, with the decision context recorded.
Offering status
Available services and developing software are labeled separately.
Clear scope matters in security. A public product vision is not the same as a delivered capability, certification, or contractual commitment.
Fugitive Control
The platform page describes a target architecture for identity, authority, action policy, approval, containment, and evidence. It is not represented as generally available.
Focused pilot discussions
A pilot may be considered for one or two consequential workflows after technical review. Only a signed agreement defines what will be delivered.
Company scope Fugitive Intelligence is an independent AI security company—not a government, law-enforcement, private-investigation, bail-enforcement, fugitive-recovery, or public tip-line service. Review trust, scope, and availability.
Why action-level security
An AI agent can change a business system.
The risk is not that every agent will become “rogue.” An agent may be over-permissioned, manipulated, misconfigured, compromised, or simply wrong while it can act.
That creates a practical question: may this identified agent perform this specific action, for this user, on this data, through this tool, under the current conditions?
Delegated authority needs enforceable boundaries.
Incomplete inventory and ownership
Agents, embedded features, model integrations, and MCP servers may appear faster than ownership and system records are updated.
Broad delegated authority
Agents may inherit user credentials or service tokens that permit more data access and more actions than the current task requires.
Tool calls create real effects
Untrusted context, a reasoning error, or a compromised component can become a refund, message, data export, code change, or privileged API request.
Evidence is split across systems
Chat history, identity logs, data access, approvals, gateway events, and downstream results are often stored separately and reviewed too late.
Fugitive Control roadmap
Control the action, not just the conversation.
Fugitive Control is being developed as a vendor-neutral path for mapping agents, defining authority, evaluating actions, routing approvals, supporting selective containment, and recording what happened.
Discover
Map in-scope agents, models, owners, tools, MCP servers, credentials, sensitive data paths, and unattended workflows.
Map the action graphAuthority
Define a resolvable identity and bounded authority for each in-scope agent, including action scopes, limits, boundaries, and expiration.
Define the mandateGuard
Allow, deny, redact, limit, transform, or escalate tool calls before they reach the underlying business system.
Review action policyTrace
Preserve a searchable action record with identity, context, data access, policy decisions, approvals, and outcomes.
Review the action recordAssurance
Plan repeatable tests and organize control evidence for security reviews, governance reporting, customer assurance, and investigations.
Plan assurance evidenceContain
Design selective revocation for an agent, credential, tool, workflow, tenant, destination, or action class, with evidence preservation and safe restoration.
Design containment
The product vision
Keep AI on mission.
Make identity, authority, action policy, accountable approval, containment, and evidence part of the workflow before autonomy expands.
Review the target architectureBetween intent and impact
A clear path for consequential actions.
The target architecture does not need to decide whether an AI is “good.” It needs enough identity, authority, context, and policy to decide how a requested action should be handled.
01
Identify
Resolve the agent, initiating user, workflow, model, and tool.
02
Evaluate
Compare requested access, data, value, recipient, and context to policy.
03
Enforce
Allow, deny, redact, constrain, or require accountable human approval.
04
Record
Preserve the decision context, approval, execution result, and responsible parties for later review.
Private browser diagnostic
Estimate your AI agent exposure.
Answer five control questions. The score is calculated locally in your browser and is not transmitted or stored.
Initial focus areas
Start where a workflow has measurable business impact.
The first use cases focus on workflows near sensitive data, customer boundaries, code, money, operational systems, or regulated decision processes. Examples are illustrative and not legal or compliance advice.
AI-native B2B SaaS
Prepare agent capabilities for enterprise review with clear tenant boundaries, tool controls, and evidence.
- Cross-tenant boundaries
- Production tool calls
- Customer assurance evidence
Financial services
Define transaction authority, separation of duties, and access boundaries for financial and operational workflows.
- Transaction thresholds
- Separation of duties
- Model and data protection
Healthcare technology
Review patient, tenant, purpose, recipient, and minimum-necessary boundaries for healthcare technology workflows.
- Sensitive data paths
- Purpose-bound access
- Human clinical oversight
Insurance
Review authority, human oversight, and traceability across underwriting, claims, documents, and customer communications.
- Decision traceability
- Approval controls
- Decision and control evidence
Founding design-partner program
Validate the control model against one real workflow.
The program is intended for teams with an identifiable agent, accountable owner, consequential tool path, and willingness to define success and safety boundaries in writing.
- Begin with a paid, fixed-scope exposure review
- Select one or two workflows after technical readiness review
- Define capabilities, data handling, testing, support, and acceptance in a signed scope
- No claim of general availability, certification, or guaranteed outcome
Practical field resources
Use the control model before an engagement.
Free educational materials for security, engineering, governance, procurement, enterprise sales, and board conversations. They are not certifications or legal advice.
inventory → authority → action → evidence
Printable checklist
AI Agent Exposure Checklist
Forty concrete checks across inventory, identity, tools, data, approvals, containment, logging, and governance.
Open checklistagent → MCP gateway → enterprise tool
Engineering field guide
MCP Security Field Guide
A defensive baseline for identity, token handling, tool integrity, input validation, egress, sandboxing, and evidence.
Read the field guideautonomy + authority = accountable risk
Executive brief
The New Non-Human Insider
Explain agentic risk to a board without reducing the discussion to prompts, hallucinations, or generic AI policy.
Open the board briefidentity · authority · action · evidence
Plain-language reference
AI Agent Security Glossary
Shared definitions for agents, tool calls, MCP, delegated authority, human approval, containment, and evidence.
Open the glossaryCommon questions
Security that starts with authority.
Is Fugitive Control generally available?
No. Fugitive Control is in founding development. The platform page describes the target architecture. Any design-partner pilot requires a separate written scope.
Is Fugitive Intelligence another prompt-injection filter?
No. Prompt and content analysis can provide useful signals, but the core design question is whether an identified agent has authority to perform a specific action under the current conditions.
Does this replace identity, API gateways, DLP, SIEM, or cloud security?
No. The target design uses existing systems as context and enforcement partners. It connects agent identity, delegated authority, tool intent, sensitive data, approval, containment, and action evidence across the stack.
Does an exposure review certify that our agents are secure?
No. It is a scoped assessment and control-planning engagement, not a certification, audit opinion, legal determination, warranty, or guarantee that every issue has been found.
Does the company investigate fugitives or accept crime tips?
No. Fugitive Intelligence is an AI security company. It is not affiliated with government or law enforcement and does not provide private-investigation, bail-enforcement, fugitive-recovery, or public tip-line services.
What is the clearest first engagement?
Start with the fixed-scope AI Agent Exposure Review. It maps an agreed environment, identifies high-impact action paths, documents control gaps, and produces a prioritized plan. Final scope and fees are confirmed in writing.