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Residential Proxy Detection API
Offer an API that scores whether a request likely comes from a residential proxy, rotating infrastructure, or evasive automation by combining ASN, TLS, header, and behavior signals. This addresses the gap between outdated datacenter blocklists and the reality of modern proxy abuse.
Why this matters
You cannot rely on old assumptions anymore. Attackers no longer show up only from obvious cloud ranges with sloppy fingerprints; they rotate identities, mimic browsers, and hide behind consumer-looking networks. At the same time, blanket bans on whole network categories create angry legitimate users. You need a better signal layer than simple IP lists, but building that internally means ongoing research, data collection, and tuning that most teams cannot spare. A specialized scoring API becomes attractive when your abuse costs are rising and your in-house rules are no longer keeping pace.
- · Built for Fraud teams, community platforms, SaaS products with account abuse issues, and developers running custom traffic filtering stacks..
- · Most likely monetization: SaaS subscription.
The Pain · Narrative
You cannot rely on old assumptions anymore. Attackers no longer show up only from obvious cloud ranges with sloppy fingerprints; they rotate identities, mimic browsers, and hide behind consumer-looking networks. At the same time, blanket bans on whole network categories create angry legitimate users. You need a better signal layer than simple IP lists, but building that internally means ongoing research, data collection, and tuning that most teams cannot spare. A specialized scoring API becomes attractive when your abuse costs are rising and your in-house rules are no longer keeping pace.
Score Breakdown
Market Signal
Go-to-Market
Product and security teams at online services already seeing signup abuse, scraping, or ban evasion from residential and rotating proxies.
A few hundred thousand potential API consumers, with a smaller high-value initial segment
cold outbound
$99/month
5 design partners sending production traffic samples and 2 converting to paid pilots in 30 days
MVP Scope · 1–2 weeks
- Build an API endpoint that accepts IP, TLS fingerprint, headers, and simple behavioral metadata
- Integrate public ASN and network reputation datasets
- Create an initial heuristic model for datacenter, residential-looking, and suspicious rotating traffic
- Log scored requests and analyst feedback for future model tuning
- Return confidence scores with human-readable reasoning fields
- Add SDKs for Node, Python, and Go
- Implement basic cluster detection for repeated suspicious patterns across customer traffic
- Create a dashboard with top offending networks and score distributions
- Add webhook alerts for sudden increases in risky traffic
- Recruit pilot customers from communities discussing scraping and abuse prevention
Differentiation
Why This Might Fail
Self-rebuttal — the most important trust signal
- 1Well-funded incumbents in fraud and risk scoring may already cover enough of this problem for larger customers.
- 2Without meaningful network effects and enough traffic data, the model may not outperform simpler internal heuristics.
- 3Some prospects may be unwilling to send sensitive request metadata to a third-party API.
Evidence Summary
How AI synthesized this insight — no verbatim quotes
Several comments pointed out that modern bad traffic often rotates TLS signatures, spoofs browser identity, and uses residential proxies that defeat datacenter-based blocking. Others argued that good and bad traffic are increasingly hard to separate with static categories. This pattern supports a commercial opportunity for a continuously updated scoring layer that helps product teams make finer-grained enforcement decisions.
Action Plan
Validate this opportunity before writing code
Recommended Next Step
Build
Strong demand signals detected. Real pain, real willingness to pay — start building an MVP.
Landing Page Copy Kit
Ready-to-paste copy based on real Reddit community language — no editing required
Headline
Residential Proxy Detection API
Sub-headline
Offer an API that scores whether a request likely comes from a residential proxy, rotating infrastructure, or evasive automation by combining ASN, TLS, header, and behavior signals. This addresses the gap between outdated datacenter blocklists and the reality of modern proxy abuse.
Who It's For
For Fraud teams, community platforms, SaaS products with account abuse issues, and developers running custom traffic filtering stacks.
Feature List
✓ Real-time risk scoring API ✓ Combined fingerprint model using ASN, TLS, headers, request cadence, and reputation data ✓ Webhook updates for newly detected proxy clusters ✓ Policy modes for soft challenge, monitor-only, and hard block ✓ Analyst dashboard with cluster trends and confidence levels
Where to Validate
Share your landing page in r/HN · front_page — that's exactly where these pain points were discovered.
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