Inside the Solarflare dataset.
Six capabilities that turn continuous proxy network observation into usable data for fraud, security, and data teams. No static blocklists. No runtime API dependency. Just a fresh observed signal delivered in a file your team can load directly.
Fresh observed proxy signals
Static IP databases lag behind real-world proxy infrastructure by weeks. Solarflare's dataset is observational and current: if an IP has recently appeared in proxy network behaviour, the next delivery captures that signal. Use it to catch the long tail of residential and mobile proxy traffic that traditional vendors miss.
- Continuous network testing, weekly delivery
- Captures residential and mobile proxy IPs
- Designed for recency, not historical coverage
- Complements MaxMind, IPinfo, and internal feeds
Recurring file delivery
Solarflare delivers each dataset as a structured file that your team can load into an internal database, data lake, fraud platform, or enrichment pipeline. Weekly delivery is standard, with cadence tailored for Enterprise requirements.
- Weekly delivery by default
- Secure file download access
- Stable schema and field dictionary
- No runtime API dependency
Bulk-ready formats
Load the dataset in bulk and join it against click streams, payment logs, account cohorts, or historical events. Standard deliveries are available as CSV or JSONL, with a consistent record structure across refreshes.
- CSV or JSONL delivery
- Designed for large IP datasets
- Per-IP signal detail
- Consistent schema across deliveries
Last-seen timestamps
Recency matters in risk decisions. An IP observed yesterday is a different signal than an IP last seen six months ago. Solarflare exposes last_seen on every record so your risk model can weigh fresh observations more heavily — and decay older ones automatically.
- ISO-8601 last_seen on every record
- Configurable freshness windows
- Decay-friendly for risk models
- Distinguishes hot, warm, cold observations
Confidence scoring
Confidence reflects how many independent observations support the signal, how recent they are, and how cleanly the IP's behaviour matches proxy infrastructure. Low-confidence signals are great for step-up verification; high-confidence signals are ready for hard blocks.
- low / medium / high confidence levels
- Network-type classification included
- Threshold-friendly for fraud rules
- Tuned for false-positive sensitivity
Cross-network connections
Solarflare isn't a replacement for your existing stack — it is a fresh observed proxy dataset you can join with MaxMind, IPinfo, internal fraud models, bot-detection tools, SIEMs, and threat-intelligence platforms. No runtime dependency and no rip-and-replace project.
- Plugs into MaxMind, IPinfo, and others
- Connects fraud, SIEM, bot-detection, and threat intel
- Works with warehouses, SIEMs, and internal databases
- Stable, documented file schema
Want to test your IP data against Solarflare?
Start with a sample file or send us a list of IPs for a match report. You'll see the same fields, schema, and recency context available in recurring dataset deliveries. No commitment.