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aisecurity.llc

Secure SDLC

Our Secure SDLC applies security review, threat modeling, testing, dependency management, and human review to the platform, SecEng Copilot, integrations, generated packets, training products, and professional-services tooling we build.

Public policy summaryPrelaunch / customer-ready draft

We build the same product and service surface we describe in our Trust Center. Security-sensitive changes get extra review, and the SDLC is designed to catch auth, evidence, AI, payment, and integration risks before release.

SDLC Snapshot

  • Security review for security-sensitive changes.
  • Threat modeling for auth, integrations, AI, evidence, and testing workflows.
  • Code review for production changes.
  • Dependency scanning and dependency review.
  • Secrets scanning.
  • Schema validation at system boundaries.
  • Testing where practical, including security-focused regression coverage.
  • Release checks before deployment.
  • Human review of AI-assisted code and content.
  • Vulnerability intake, triage, and remediation.
  • Documentation updates for trust, legal, and security-impacting changes.

Security-Sensitive Change Categories

These changes receive elevated review because they can affect authorization, evidence handling, payments, or customer trust:

  • Auth and session changes.
  • Organization, workspace, role, and entitlement changes.
  • Legal, finance, IT, and security delegation changes.
  • SSO, SAML, OIDC, and SCIM changes.
  • Stripe, checkout, and seat provisioning changes.
  • Private-offer, SOW, and contract workflow changes.
  • Packet, report, and evidence rendering changes.
  • SecEng Copilot changes.
  • Model-provider, prompt, retrieval, or workspace-context changes.
  • Browser extension changes.
  • Native app changes.
  • Connector and OAuth scope changes.
  • Runtime proxy, model gateway, or trace handling changes.
  • Code scanner, adversarial range, or RAG harness changes.
  • Database migrations and RLS or policy changes.
  • Uploaded-file and artifact-handling changes.
  • Trust-center and legal route changes.

Design Review and Threat Modeling

We review design changes for the failure modes that matter most to this product line:

  • Tenant and workspace isolation.
  • IDOR and broken authorization.
  • Role and entitlement escalation.
  • Evidence and artifact exposure.
  • Private-offer and contract packet exposure.
  • Prompt and evidence leakage.
  • Connector and OAuth scope abuse.
  • Copilot misuse or overreach.
  • Payment and seat-provisioning abuse.
  • Testing authorization and ROE boundary failures.
  • Public claim and attestation misuse.
  • Unsafe handling of target details, logs, traces, prompts, or reports.

Implementation Controls

  • TypeScript and schema validation at the boundary where data enters the system.
  • Explicit authorization checks on the server side.
  • Privileged secrets handled server-side only.
  • No service-role keys in browser code.
  • Least privilege and secure defaults.
  • Safe error handling and logging without secrets.
  • Input validation and output encoding where relevant.
  • Dependency review before adoption and release.
  • Secure handling of migrations.
  • Review of generated or AI-assisted code before merge.

AI-Assisted Development and Review

  • AI may assist with drafting, code review, analysis, refactoring, tests, and documentation.
  • AI-generated code and content require human review.
  • Security-sensitive paths require extra scrutiny.
  • Customer secrets and restricted customer evidence should not be pasted into AI coding tools unless the applicable agreement and processing path permit it.
  • AI assistance does not replace security review.

Testing and QA

  • Unit tests where useful.
  • Integration tests for API and state transitions.
  • Browser and end-to-end tests for customer journeys.
  • Auth and role tests.
  • /scope and /start funnel state tests.
  • Anonymous-to-authenticated continuation tests.
  • Stripe test mode for checkout and entitlements.
  • Packet generation tests.
  • Contract, ROE, and evidence flow tests.
  • SSO and SCIM fixtures where available.
  • Regression tests for security-sensitive routes.

Release and Change Management

  • Preview or staging review where available.
  • Feature flags if used.
  • Migration review before deployment.
  • Rollback planning for security-sensitive releases.
  • Monitoring after sensitive releases.
  • Route and metadata updates when product surfaces change.
  • Updating Trust Center docs when product behavior changes.
  • Reviewing customer-facing legal and security copy when capabilities change.

Vulnerability Management

  • Dependency updates.
  • Vulnerability disclosure intake.
  • Triage and severity assessment.
  • Remediation tracking.
  • Verification and retest.
  • Customer notice where appropriate.
  • Lessons learned flow back into the SDLC.

Special Review Gates

The following changes require elevated review before release:

  • New AI provider or model route.
  • New OAuth scope or connector.
  • New browser extension permission.
  • New native app capability.
  • New way to ingest or upload evidence.
  • New way to generate public-facing claims.
  • New payment or entitlement workflow.
  • New admin or role permission.
  • New red-team or pentest workflow.
  • New cloud or testing boundary feature.

Secure SDLC - aisecurity.llc - Last updated June 27, 2026

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