IPQualityScore is a broad fraud detection platform. Its products cover proxy and VPN detection, IP fraud scoring, bot detection, email validation, phone validation, transaction scoring, device-related signals, and more.

That breadth is useful. It also makes the comparison with FraudGuard more specific than “which vendor is better?”

If you need an all-in-one fraud scoring suite with email, phone, transaction, and proxy tools, IPQualityScore may be a fit. If you need a focused IP reputation API that shows observed attack evidence and returns an allow, challenge, or block recommendation, FraudGuard is the cleaner alternative.

The strongest FraudGuard argument is not breadth. It is depth in one valuable category: first-party honeypot observations converted by ACE v2 into explainable IP decisions at a fair, published price.

What IPQualityScore Does Well

IPQualityScore’s proxy detection documentation says its API can analyze IP reputation, detect proxies, VPNs, and Tor connections, and estimate the probability of fraudulent activity. Its example response includes fields such as:

  • fraud_score
  • proxy
  • vpn
  • tor
  • recent_abuse
  • frequent_abuser
  • high_risk_attacks
  • abuse_velocity
  • bot_status
  • connection_type
  • ISP, ASN, organization, and geography fields

IPQS also publicly says it uses proprietary honeypots, traps, crawlers, and live-site threat intelligence network signals.

That means the issue is not that IPQS lacks data. The issue for some buyers is that the public response model is oriented around fraud and proxy scoring fields, while FraudGuard is oriented around showing the attack evidence and decision context behind an IP verdict.

FraudGuard’s Different Focus

FraudGuard ACE v2 is built to explain why an IP recommendation was made. The documented response model can include:

  • recommendation.action
  • recommendation.evidence_summary
  • risk level and confidence
  • confidence factors
  • observed attack families
  • 24-hour, 7-day, and 30-day activity windows
  • targeted services, protocols, and ports
  • infrastructure classification
  • customer whitelist, blacklist, and geoblock context
  • stable reason codes and human-readable reasons

That is the core difference: FraudGuard is optimized for teams that need to defend a production traffic decision later.

Why FraudGuard’s Honeypot Findings Matter

Honeypot data is valuable because it catches behavior before a customer has to experience the attack directly. A source IP that probes decoys, hits multiple services, repeats patterns across time windows, or targets AI and web endpoints is leaving evidence that can be used in production enforcement.

ACE v2 is the layer that makes those findings usable. It does not just say “high risk.” It can expose the observed activity, attack families, recency, confidence factors, and a direct action. That is the gap many teams feel with generic fraud scores: they get a number, but not the case file.

Real ACE v2 Decision Example

Here is a real ACE v2 single-lookup response:

{
  "ip": "8.216.12.173",
  "recommendation": {
    "action": "block",
    "evidence_summary": "This IP was observed performing 3 total attack events across 2 FraudGuard honeypots in the last 7 days, including 2 Jenkins probing events and 1 HTTP/WAF probing event, most recently on May 26, 2026 at 19:31 UTC.",
    "cache_ttl_seconds": 14400
  },
  "classification": {
    "primary": "web_scanner",
    "secondary": [
      "multi_service_scanner",
      "honeypot_attacker",
      "ai_automation",
      "hosting_provider"
    ]
  },
  "risk": {
    "level": 5,
    "label": "critical",
    "confidence": 85,
    "confidence_factors": [
      "recent_activity",
      "repeated_activity",
      "multi_honeypot_reach",
      "specific_attack_signature",
      "multiple_attack_types",
      "multiple_target_services"
    ]
  },
  "observed_activity": {
    "observed": true,
    "attack_families": [
      "web_probe"
    ],
    "activity": {
      "pattern": "burst",
      "trend": "burst",
      "attack_events_24h": 3,
      "attack_events_7d": 3,
      "attack_events_30d": 3,
      "distinct_attack_types_30d": 2,
      "distinct_target_services_30d": 2,
      "distinct_target_ports_30d": 2,
      "first_seen": "2026-05-26T15:45:54+00:00",
      "last_seen": "2026-05-26T19:31:59+00:00"
    },
    "attacks": [
      {
        "type": "jenkins_login_page_probe",
        "service": "jenkins",
        "protocol": "http",
        "destination_port": 8080,
        "attack_events_24h": 2,
        "attack_events_7d": 2,
        "attack_events_30d": 2,
        "honeypots_reached_24h": 1,
        "honeypots_reached_7d": 1,
        "honeypots_reached_30d": 1,
        "first_seen": "2026-05-26T15:45:54+00:00",
        "last_seen": "2026-05-26T15:45:57+00:00"
      },
      {
        "type": "waf_attack",
        "service": "http",
        "protocol": "http",
        "destination_port": 80,
        "attack_events_24h": 1,
        "attack_events_7d": 1,
        "attack_events_30d": 1,
        "honeypots_reached_24h": 1,
        "honeypots_reached_7d": 1,
        "honeypots_reached_30d": 1,
        "first_seen": "2026-05-26T19:31:59+00:00",
        "last_seen": "2026-05-26T19:31:59+00:00"
      }
    ],
    "last_observed_attack": {
      "event_type": "waf_attack",
      "service": "http",
      "protocol": "http",
      "destination_port": 80,
      "observed_at": "2026-05-26T19:31:59+00:00"
    }
  },
  "attributes": {
    "ai_automation_suspected": {
      "detected": true
    }
  },
  "reasons": [
    {
      "code": "abusive_activity_observed",
      "message": "Abusive activity observed by FraudGuard ACE",
      "severity": "high"
    },
    {
      "code": "scanner_activity_observed",
      "message": "Scanner or probing activity observed",
      "severity": "medium"
    },
    {
      "code": "honeypot_interaction_observed",
      "message": "Interaction observed across FraudGuard honeypot infrastructure",
      "severity": "high"
    },
    {
      "code": "waf_attack_activity_observed",
      "message": "HTTP/WAF attack activity observed",
      "severity": "high"
    },
    {
      "code": "activity_within_7_days",
      "message": "Activity observed within the last 7 days",
      "severity": "high"
    }
  ],
  "customer": {
    "ip_in_whitelist": false,
    "ip_in_blacklist": false,
    "ip_in_geoblock": false
  },
  "infrastructure": {
    "type": "hosting_provider",
    "provider": "Alibaba Cloud",
    "is_tor_exit": false,
    "is_public_proxy": false,
    "is_vpn": false,
    "is_hosting_provider": true,
    "is_residential_proxy": false,
    "is_mobile_network": false,
    "is_satellite_network": false,
    "is_shared_exit": false,
    "is_ai_agent": false,
    "first_seen": "2026-05-18T02:44:12+00:00",
    "last_seen": "2026-05-18T15:07:09+00:00",
    "updated_at": "2026-05-18T15:07:09+00:00"
  },
  "network": {
    "asn": 45102,
    "asn_org": "Alibaba US Technology Co., Ltd.",
    "isp": "Alibaba",
    "organization": "Alibaba",
    "prefix": "8.216.12.0/24",
    "connection_type": "Corporate"
  },
  "geography": {
    "country": "Japan",
    "isocode": "JP",
    "state": "Tokyo",
    "city": "Tokyo",
    "postal_code": "102-0082",
    "timezone": "Asia/Tokyo",
    "latitude": 35.6893,
    "longitude": 139.6899
  },
  "metadata": {
    "request_id": "acev2_example_single_lookup",
    "generated_at": "2026-05-27T00:47:35+00:00",
    "schema_version": "2.0.0",
    "api_version": "2.0.0",
    "engine": "ace_v2"
  }
}

The important field is evidence_summary. It turns an automated risk decision into something support, fraud, engineering, and security teams can understand.

Pricing Context

As of June 2026, IPQualityScore’s public pricing page lists a free tier with 1,000 lookups per month and 35 lookups per day, a Startup plan from $99/month with 5,000 lookups per month, SMB Basic from $499/month with 10,000 lookups per month, and SMB+ from $999/month with 75,000 lookups per month.

FraudGuard pricing lists:

  • Starter: $29/month, 1 million requests/month
  • Professional: $99/month, 5 million requests/month, ACE v2 included
  • Business: $299/month, 25 million requests/month
  • Enterprise: $599/month, 100 million requests/month

If your buying need is broad fraud validation across many identity fields, compare the full product scope carefully. If your buying need is high-volume IP reputation with explainable threat decisions, FraudGuard is priced much more directly for that use case.

This is where FraudGuard is unusually strong: Professional includes ACE v2 at $99/month with 5 million monthly requests. That gives teams access to honeypot-derived evidence and direct IP decisions at a cost that fits real production experiments, not only enterprise procurement cycles.

Bottom Line

IPQualityScore is a broad fraud scoring suite. FraudGuard is a focused, evidence-based IP reputation and threat-decision platform.

For email, phone, and multi-attribute fraud validation, evaluate IPQualityScore on its breadth. For IP-based traffic enforcement where your team needs to explain and tune every allow, challenge, and block decision, evaluate FraudGuard. The reason to choose FraudGuard is the combination of honeypot findings, ACE v2 evidence, and fair high-volume pricing.

Review ACE v2, test IP Lookup, or compare plans.

Related comparison: FraudGuard vs Shodan.