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Proxy DB Engine

Python CLI Status Storage

Proxy DB Engine is a CLI-first public proxy harvesting and validation project focused on building a reusable proxy database rather than just scraping raw lists. It combines harvesting, protocol-aware validation, handshake hardening, tunnel-aware downstream proof, scoring, export, and calibration into one single-node workflow.

Why this repo exists

Most public proxy projects stop at collecting raw lists or doing shallow liveness checks. This repo is trying to push one layer deeper: keep a local proxy database, validate protocol behavior more honestly, keep evidence history, and produce shortlists that other projects can actually consume.

Current Status

The project is usable for research, batch validation, shortlist generation, and feeding downstream tooling. It has real harvesting, protocol-aware validation, downstream-proof tracking, export filters, and calibration support.

The honest real-world state right now is that public proxy quality is very poor. In a live 300-sample run, only a very small fraction survived the full evidence chain. That is useful information, not a failure of the tool.

Current Limitations

  • public proxy quality is extremely noisy in real-world runs
  • the project is not yet a finished answer for highly sensitive targets
  • there is no full TLS-native tunnel proof yet
  • threshold defaults are still recommendation-driven, not auto-applied
  • there is no API or dashboard layer yet

Features

  • harvest public proxy candidates from multiple sources
  • normalize and deduplicate candidates
  • protocol-aware validation with handshake-native hardening
  • tunnel-aware downstream proof tracking
  • scoring and shortlist generation
  • export, stats, refresh, and calibration commands

Architecture Snapshot

  • source adapters
  • normalization and dedupe
  • validation and protocol probes
  • scoring and aggregate state
  • SQLite-backed storage and history
  • calibration and threshold sweep outputs

Flow summary:

flowchart TD
    A[Public Sources] --> B[Normalization]
    B --> C[Deduplication]
    C --> D[Protocol Validation]
    D --> E[Handshake-Native Proof]
    E --> F[Tunnel-Aware Downstream Proof]
    F --> G[Scoring]
    G --> H[(SQLite State + History)]
    H --> I[Export]
    H --> J[Calibration]
    J --> K[Threshold Sweep]
    J --> L[Shortlists]
Loading

Detailed flow notes: docs/FLOWS.md

Quickstart

python3 -m venv .venv
. .venv/bin/activate
pip install -e .[dev]
proxydb harvest
proxydb validate --limit 300
proxydb export --format json --winning-protocol https --require-downstream-proof
proxydb calibrate --sample-limit 300

CLI Commands

  • proxydb harvest
  • proxydb validate --limit N
  • proxydb export --format {text,json,csv}
  • proxydb stats
  • proxydb refresh --limit N
  • proxydb calibrate --sample-limit N

Typical Workflow

  1. harvest public proxy candidates
  2. validate a batch against the current evidence chain
  3. export or inspect surviving candidates
  4. run calibration to produce threshold sweep artifacts and shortlists
  5. review shortlist quality before adopting thresholds operationally

Calibration Artifacts

Calibration runs currently emit structured JSON artifacts for:

  • summary metrics
  • threshold sweep results
  • overall shortlist
  • per-protocol shortlists

Example sample artifact: assets/sample-calibration-summary.json

Real Run Snapshot

From the first real medium sample run:

  • sample size: 300
  • downstream-proof successes: 4
  • winning protocol distribution: HTTPS only in that sample
  • outcome: usable shortlist existed, but survival rate was very low

That is exactly why the repo includes calibration and threshold sweep support.

Use Cases

  • research public proxy quality realistically
  • build shortlist feeds for downstream automation
  • compare protocol survival patterns
  • tune filtering thresholds from live batch evidence instead of guesswork

Security / Sanitization Notes

  • do not commit live database files, tokens, or sensitive runtime artifacts
  • calibration artifacts should stay sanitized and summary-oriented when published
  • sample output in this repo is intentionally limited to safe summary data

Roadmap

  • deeper live validation and threshold tuning
  • stronger per-protocol downstream proof
  • source quality intelligence
  • cleaner consumer-facing query surfaces
  • later API or dashboard layer only after the evidence model settles

About

High-performance proxy harvesting, protocol validation, and SQLite-backed pool manager.

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