AI Agent Security Assessment

Security intake for custom AI agent platforms.

Scoped access Evidence checklist Email evidence package

Client Details

Assessment request

Questionnaire

Platform security context

01Platform overview

Business context, users, tenants, and highest-risk agent behavior.

  • Product name and short description
  • Target users and customer types
  • Current stage: prototype, beta, production, or customer-facing production
  • Single-tenant or multi-tenant model
  • Sensitive or regulated data the system may handle
  • What the agent can see, decide, and change
  • Worst realistic failure scenario
02Architecture and data flow

How requests, prompts, files, tools, model responses, and data move through the system.

  • Frontend, Vercel API/serverless, backend services, database, storage, queues, and webhooks
  • Where the custom agent loop runs
  • How long-running jobs are handled
  • Which environments exist: development, preview, staging, production
  • Third-party services and integrations
03Assessment access

Least-privilege access needed to validate the implementation.

  • Staging/test URL
  • Test user account
  • Test admin/support account if applicable
  • Test tenant with sample data
  • Source repository or source export
  • Vercel project settings export or screenshots
  • Database schema, migrations, and policy exports
  • Logging/monitoring samples or dashboard access
04Authentication and authorization

Identity, roles, tenant mapping, session handling, and enforcement points.

  • Auth provider and flow
  • Role and permission model
  • Where authorization is enforced
  • Tenant/user/account mapping
  • Admin/support access and impersonation model
  • Session expiration, revocation, MFA, invites, and password resets
05Database and tenant isolation

Schema, row-level controls, backups, and cross-tenant protection.

  • Database provider and version
  • Tenant isolation design
  • Row-level security or equivalent policy model
  • Backend validation rules
  • Backup/restore process
  • Data export and deletion process
  • Production data access list
06AI agent harness

Prompts, custom orchestration, tools, memory, retrieval, and action guardrails.

  • System prompts and instruction layers
  • Agent orchestration code
  • Tool/function definitions
  • Tool allowlists by tenant/user
  • Memory and retrieval configuration
  • Human approval gates for risky actions
  • Model provider, models, and data retention settings
  • Behavior tests or evaluations
07Prompt injection and abuse cases

Expected behavior under hostile prompts, malicious files, and unsafe tool requests.

  • Ignore previous instructions / reveal system prompt
  • Malicious uploaded document
  • Malicious webpage summarized by the agent
  • Cross-tenant ID manipulation
  • Attacker-controlled webhook request
  • Secrets/logs/schema disclosure request
  • Destructive action request
  • Cost spike or infinite-loop attempt
08APIs and webhooks

Route inventory, schemas, auth requirements, signature checks, replay protection, and rate limits.

  • API route list
  • Auth requirements per route
  • Request and response schemas
  • Webhook endpoint list
  • Signature verification and replay protection
  • Idempotency handling
  • Rate limits by route, user, tenant, and IP
09Files, uploads, and storage

Upload limits, private storage, signed URLs, file scanning, embeddings, and deletion.

  • File storage provider
  • Allowed file types and size limits
  • Private access model
  • Signed URL expiration
  • File scanning/validation
  • Whether files are sent to models or vectorized
  • Deletion of files and embeddings
10Secrets and key management

Environment variables, key rotation, token scope, git history, and blast radius.

  • Redacted environment variable inventory
  • Secret storage locations
  • Key rotation process
  • Third-party token inventory
  • Production access list
  • Git secret scanning results
  • Blast radius of model, database, and webhook key leakage
11Logging and incident response

Request logs, agent/tool-call logs, redaction, alerts, audit trails, and kill switches.

  • Sample request/auth/agent/tool-call logs
  • Sensitive data redaction approach
  • Who can view logs
  • Alert rules for auth failures, errors, costs, data exports, and webhook failures
  • Admin audit logs
  • Incident response process
  • Kill switch for compromised agents, tenants, integrations, or tools
12Privacy and compliance

Policies, subprocessors, model-provider data use, retention, consent, and regulated workloads.

  • Privacy policy and terms
  • Data retention policy
  • Subprocessor list
  • Data sent to model providers
  • Model training/retention settings
  • Deletion/export request support
  • HIPAA, COPPA, FERPA, PCI, GLBA, SOC 2, GDPR, CCPA obligations

Evidence

Documents to provide

Check the documents you are including, then email the completed intake package and supporting evidence to sean@mathena.com.

Email supporting documentsSend the checked items and the generated intake package to sean@mathena.com. Use redacted exports or test data wherever possible.

Scope Controls

Testing boundaries

This prepares a local JSON copy of the answers and opens an email addressed to sean@mathena.com.