Credentials
Access that looks like text
API keys, tokens, passwords and connection strings become mixed into errors, examples or configuration files.
Corporate context also travels through personal accounts.
Shadow AI appears when work moves through tools or accounts the organization does not administer. An ordinary task can carry credentials, code or personal data beyond the intended environment.
It starts with a task that cannot wait.
Friction around access to an approved tool moves the work towards the option that is already available.
6:20 p.m. · production incident
A developer opens the AI tool they use at home, pastes a trace and finds the fault. Within minutes, the service is running again.
The same trace may contain tokens, internal paths or customer information and has travelled through an account IT does not administer.
40%
of surveyed organizations acknowledged unauthorized AI or usage outside oversight.
2025 State of AI Data Security Report. Self-reported survey of 921 IT and cybersecurity professionals; ±3.2% margin of error at a 95% confidence level. Open the report and methodology
Every service needs an explicit decision.
Policy combines access, risk, contract and technical compatibility. These three responses can coexist within the same organization.
Restrict
For unauthorized or incompatible services, and risks the organization will not accept.
Allow
Allow with TigerMoleFor workflows whose provider, account, processing and controls have been approved.
To add a local boundary for detected sensitive values on supported surfaces.
The organization retains the decision over each tool. TigerMole protects content in the supported workflows that remain open.
Sensitive values blend into ordinary work.
Risk rarely arrives with a label. It appears inside the material a person needs to explain the problem.
Code
Real operational context
Repository snippets, environment variables and internal details can expose more context than the task requires.
Personal data
Information linked to people
Names, email addresses, identifiers and customer data require a purpose and controls consistent with their processing.
Policy chooses the path. TigerMole protects the permitted route.
The local boundary sits after the access decision and before the AI provider. Technical evidence remains in the customer's environment.
Corporate policy
Defines the provider, account, purpose, data and accepted controls.
Access decision
Each service is restricted or allowed.
Restrict the service
The domain or application remains outside the approved workflow.
Allow
Work continues through a supported surface.
TigerMole · local boundary
Detects and locally replaces sensitive values before they leave.
AI provider
Receives the remaining content after detected values have been masked.
Local evidence
Technical metadata about detection and protection for internal review.
Deployment brings TigerMole's local protection together with contracts, DPAs, access controls, internal policies and provider assurances.
Examine the Security Evidence PackCommon questions about Shadow AI.
Adoption, authorization and technical coverage are related decisions with different owners and controls.
Does Shadow AI imply malicious behavior?
It can arise from urgency, speed or the lack of a suitable alternative. Review should consider the workflow, data, responsibilities and available training.
What does domain blocking provide?
It removes unauthorized or high-risk services. Approved workflows still need criteria for the content that may be sent.
Which part of Shadow AI does TigerMole cover?
Coverage corresponds to the surfaces and versions published as supported. A general application inventory requires complementary controls.
Review a real workflow before deployment.
The demo covers the exact intervention point, available coverage and the evidence retained under local control.