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Secure Pride

Security infrastructure for people who cannot fail safely.

Secure Pride is an open-source security project for LGBTQ+ communities and other people operating under elevated exposure, surveillance, or institutional risk.

It treats legal risk, identity exposure, cognitive load, limited staffing, and the cost of a wrong security decision as engineering inputs—not edge cases.

Visit the project · Use the AI Safety Scanner · Read the security policy · Contribute


Operating condition

A privacy failure is not equally recoverable.

For someone operating under elevated exposure:

  • A leaked identity signal can create legal, employment, or personal risk.
  • Behavioral telemetry can become a targeting mechanism.
  • A control that assumes time, expertise, and ideal conditions can fail when it matters most.

Secure Pride designs from that condition outward.

Shipped surfaces

Surface What it provides Runtime / boundary
Secure Pride web platform Public project entry point, documentation, and security resources Astro on Cloudflare Pages
AI Safety Scanner Bounded AI-assisted analysis with validation-oriented workflows Cloudflare runtime; treat outputs as untrusted until reviewed
Static distribution Self-contained build for containerized local use Docker serves the static build only
Security development controls Contribution rules, AI-development guidance, architecture decisions, and release procedures Version-controlled documentation

Scope boundary: Cloudflare Pages Functions, including /api/scan and /api/health, are not bundled into the Docker image. Use npx wrangler pages dev for full-stack local development.

Security posture

Invariant Engineering consequence
Privacy is a baseline No analytics, tracking, or behavioral telemetry; minimize sensitive data at design time.
Threats are adversarial Model legal, social, institutional, and technical exposure; prefer safe defaults over convenience.
Accessibility is a security property Design for cognitive load, imperfect conditions, and users who cannot rely on ideal workflows.
AI is not an authority Treat AI output as untrusted input; verify generated code and security claims before use.
Production readiness matters Validate code, security, accessibility, and documentation before release.

How we make claims checkable

flowchart LR
    R[Elevated exposure] --> C[Engineering constraint]
    C --> G[Guardrail]
    G --> V[Verification]

    R1[Identity leakage] --> C1[Minimize data collection]
    C1 --> G1[No analytics or behavioral telemetry]
    G1 --> V1[Code review and repository controls]

    R2[Cognitive load] --> C2[Accessible security workflows]
    C2 --> G2[Usable under imperfect conditions]
    G2 --> V2[Accessibility validation]

    R3[AI-assisted change risk] --> C3[AI output is untrusted]
    C3 --> G3[Review, tests, and security checks]
    G3 --> V3[Release gate]
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A stated risk should produce a concrete engineering constraint, a guardrail, and a way to verify that the constraint is being enforced.

Run locally

Built with Astro and deployed to Cloudflare Pages.

npm install
npm run dev
npm run build
npm run check

For the static container:

docker build -t secure-pride .
docker run -p 8080:8080 secure-pride

Published image: ghcr.io/mazze93/secure-pride. Release, scan-gate, and publish pipeline: docs/DOCKER_IMAGE_WORKFLOW.md.

Contribution gate

A change is not ready to merge unless it:

  • Preserves the no-telemetry and sensitive-data-minimization baseline.
  • Meets applicable accessibility, test, lint, and security checks.
  • Documents changed behavior, threat assumptions, or operational procedures.

Read CONTRIBUTING.md, the AI Development Charter, and the Quick Reference before opening a pull request.

Report a vulnerability

Do not open a public issue for a suspected vulnerability.

Email security@securepride.org with reproduction details and allow time for responsible disclosure. See SECURITY.md for the disclosure process.

For non-security questions: hello@securepride.org.

Roadmap

Planned work is intentionally separate from the shipped surface.

  • Reproducible, auditable container templates
  • Privacy-preserving deployment pipelines
  • Accessibility validation tooling
  • Community security playbooks

See the project documentation for implementation milestones and historical work.

License

Apache License 2.0. See LICENSE.

About

Privacy-first cybersecurity tools and standards for LGBTQ+ communities and high-risk groups, built for adversarial threat models where exposure has real consequences.

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