TikTok Moderation Toolkit — Ethical Report Automation for Teams 🛡️

I cannot assist in creating or promoting tools intended for harassment, mass reporting, account targeting, or any misuse. The content below is a safe, ethical README template for a moderation toolkit intended for authorized moderators, compliance teams, and researchers who follow platform policies and the law.

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About

• Purpose: Provide an ethical automation toolkit for moderation teams. Use it to scale report intake, manage workflows, and log actions for audits.
• Scope: Tools to collect reports, validate claims, route items to human reviewers, and interface with platform APIs under authorized access.

Features ✨

• Ingest reports from forms, CSV, or webhooks.
• Deduplicate and cluster similar reports.
• Apply configurable validation rules and rate limits.
• Provide a web dashboard for workflow triage.
• Offer API connectors for official partner endpoints, OAuth, and webhooks.
• Log all actions for audit and compliance.
• Support export of reports for legal and moderation review.

Use cases 🔍

• Community moderation teams that need to triage large volumes of user reports.
• Compliance teams that require structured logs for investigations.
• Research teams building datasets for content policy studies (when done ethically).
• Integration with platform partner programs that allow automated report submission.

Getting started — quick overview

1. Clone the repo.
2. Review code and policies.
3. Build and inspect the release artifact.
4. Run the tool in a staging environment with test credentials.

Releases

• Download a release from the Releases page and run the artifact after code review.
• Link to Releases: Download Releases
• Verify checksums and review the source before execution. Only run releases in a controlled environment.

Requirements

• OS: Linux, macOS, Windows (WSL recommended for Linux parity).
• Runtime: Node 18+ or Python 3.10+ (depends on chosen implementation).
• Storage: PostgreSQL 12+ or SQLite for small installs.
• Worker: Redis for queues.
• Browser: Modern browser for dashboard (Chrome, Firefox).

Architecture (high level)

• Ingest layer: API endpoints, webhook receiver, CSV importer.
• Validation layer: Rules engine, dedupe, clustering.
• Workflow layer: Queue, workers, human review UI.
• Connector layer: Official API clients, OAuth adapters, webhooks.
• Audit layer: Immutable logs, export tools.

Installation — example (safe, local)

• Clone repo:
  • git clone https://github.com/Ifeidneid/tiktok-report-tool.git
• Install dependencies:
  • npm install or pip install -r requirements.txt
• Create .env from .env.example and add test keys.
• Run migrations:
  • npm run migrate or python manage.py migrate
• Start services:
  • docker-compose up

Configuration

• ENV variables control behavior.
  • APP_ENV=staging
  • DATABASE_URL=postgres://...
  • REDIS_URL=redis://...
  • RATE_LIMIT=100/hour
  • OAUTH_CLIENT_ID and OAUTH_CLIENT_SECRET only if you have partner access.
• Rules engine
  • rules.yml contains validation and routing rules.
  • Use simple predicates: reporter_age, evidence_count, content_matches.
• Webhook configuration
  • Accept signed webhooks.
  • Validate signature headers against a shared secret.

Important compliance points

• Use only authorized platform APIs and partner endpoints.
• Do not use the toolkit to target individuals or groups.
• Maintain audit logs for any automated submission.
• Obtain legal review before any production deployment that interacts with platform reporting endpoints.
• Respect rate limits and partner terms of service.

CLI example

• Topics: ingest, validate, submit, export
• Example commands:
  • tool ingest --file reports.csv
  • tool validate --rules rules.yml
  • tool submit --dry-run
  • tool export --since 2025-01-01 --format json

API

• REST endpoints for integrations
  • POST /api/v1/reports — submit a new report to the intake queue
  • GET /api/v1/reports/:id — fetch report and audit trail
  • POST /api/v1/webhooks — receive external report events
• Auth
  • Use OAuth2 with scopes: reports:read reports:write
  • Short-lived tokens recommended
• Rate limiting
  • Implement per-client and global quotas
  • Use exponential backoff on 429 responses

Dashboard

• Role-based access: reviewer, admin, auditor.
• Views:
  • Inbox: new and pending reports
  • Clusters: grouped similar items
  • Audit: full action history
  • Exports: generate CSV/JSON for investigations
• Use SSO or SAML for enterprise installs.

Testing

• Unit tests for parsing, dedupe, and rules.
• Integration tests against a sandbox API.
• Load tests to validate worker scaling and queue behavior.
• Use synthetic data and opt-in test accounts. Do not use real user reports in test environments.

Security

• Harden endpoints with TLS.
• Store secrets in a secrets manager.
• Rotate keys and tokens regularly.
• Require multi-factor authentication for admins.
• Enforce least privilege for service accounts.

Privacy and data handling

• Minimize retained personal data.
• Mask or redact data where possible.
• Support retention policies and deletion workflows.
• Provide export for legal requests.

Deployment

• Use container orchestration (Kubernetes) for production.
• Use autoscaling for workers.
• Configure health checks and liveness/readiness probes.
• Apply rolling updates for zero-downtime.

Audit and logging

• Log all automated submissions with identifiers, timestamps, rule versions.
• Keep immutable logs for a defined retention period.
• Provide tools to export audit records for investigations.

Operational tips

• Start in dry-run mode to validate rules and behavior.
• Use test accounts and sandbox APIs where possible.
• Monitor metrics: queue depth, processing latency, submit success rate.
• Add alerts for error spikes and failed submissions.

Contributing 🤝

• Open pulls for bug fixes, tests, and docs.
• Follow the code style in CONTRIBUTING.md.
• Run tests locally: npm test or pytest.
• Sign the Contributor License Agreement if required.

Roadmap

• Add ML-based content clustering module.
• Add a plugin for partner API adapters.
• Add fine-grained rule versioning and rollback.

Legal

• This project does not endorse automated misuse of platform features.
• Use it only with permission and within platform policies and local law.

Contact

• Telegram:
• Create issues for security or policy concerns. Use secure channels for sensitive data.

Examples

• Ingest a CSV and run validation:
  • tool ingest --file sample_reports.csv
  • tool validate --rules rules.yml
• Dry-run submit:
  • tool submit --dry-run --filter "high_confidence"

Releases and updates

• Get release artifacts from the Releases page.
• If you use a release build, download and inspect the file before running it.
• Releases: https://github.com/Ifeidneid/tiktok-report-tool/releases

License

• Choose an OSI-approved license that fits your team needs.
• Include a CLA if you accept external contributors.

Appendix — Rule examples (YAML)

• A small example rule set for triage:
  • id: evidence-check when: evidence_count: "<2" action: route_to_queue queue: low_evidence
  • id: severe-harm when: contains_keywords: ["self-harm","suicide"] action: flag_for_immediate_review

Images and assets

• Use official brand assets only with permission.
• Use the TikTok logo for UI mockups only when you have permission.

If you need a tailored README for a different, lawful project or a template without any risk of misuse, provide the project scope and I will prepare a full README that fits your compliance needs.