GreyNoise is a strong scanner-intelligence and SOC noise-reduction product. If your team needs to understand internet-wide scanning, investigate noisy alerts, prioritize vulnerability activity, or build scanner-informed blocklists, GreyNoise is worth evaluating.

FraudGuard solves a different problem: affordable, API-first IP reputation for production systems that need to decide whether traffic should be allowed, challenged, or blocked.

If you are looking for a GreyNoise alternative because you need IP risk decisions inside a login flow, signup form, checkout system, API gateway, WAF workflow, fraud queue, or customer-specific policy engine, FraudGuard is the better fit.

Quick Answer

Need Better Fit
Scanner context, SOC triage, threat hunting GreyNoise
Dynamic scanner-informed firewall blocklists GreyNoise
App/API request-path decisions FraudGuard
Lower-cost IP reputation API FraudGuard
No mandatory sales call or annual contract for standard plans FraudGuard
Custom security workflows built around IP risk data FraudGuard

Both products are useful. They are not the same tool.

The Main Difference

GreyNoise helps answer:

  • Is this IP part of broad internet scanning?
  • Is this alert likely background scanner noise?
  • What tags, CVEs, or scanner behaviors are associated with this IP?
  • Should a SOC analyst spend time on this event?

FraudGuard helps answer:

  • Should this request be allowed, challenged, or blocked?
  • Is this IP risky for my application, API, signup flow, or customer account?
  • Does my customer policy whitelist, blacklist, geoblock, or rate-limit this request?
  • Can I explain the decision with evidence?

That distinction matters. Analyst context is valuable, but production systems need a decision.

Pricing and Buying Friction

As of June 17, 2026, GreyNoise’s public pricing page lists GreyNoise Block at $9,999/year for organizations under 2,500 employees. GreyNoise also offers a 14-day trial for Block, and broader platform access is positioned through sales-led plans for larger organizations, MSSPs, and enterprise buyers.

FraudGuard pricing is public and API-focused:

Plan Monthly Cost Annualized Includes
Starter $29/mo $348/year 1M requests/month
Professional $99/mo $1,188/year ACE v2, custom lists, geoblocking, rate limiting, 5M requests/month
Business $299/mo $3,588/year Offline Threat Database, Attack Stream, BotGuard, 25M requests/month
Enterprise $599/mo $7,188/year 100M listed monthly requests, priority support, bulk lookup workflows

That means FraudGuard Starter is roughly 3.5% of the listed GreyNoise Block annual price. Even FraudGuard Enterprise is below the listed GreyNoise Block annual price while listing 100M monthly API requests.

FraudGuard has also been in business for 11 years, and we have never raised pricing on our standard plans. That matters for teams trying to build security controls with predictable long-term costs.

FraudGuard standard plans also avoid the common buying friction:

  • public pricing
  • public documentation
  • free public lookup
  • direct trial path
  • no mandatory sales call for standard plans
  • no annual contract for standard plans

Custom engineering, dedicated data delivery, or customer-specific architecture work may require a separate agreement. But if you want the standard IP reputation API, you should not need a sales process just to find out whether it is affordable.

Where GreyNoise Is Strong

GreyNoise documentation describes scanner-intelligence classifications such as benign, malicious, suspicious, and unknown. GreyNoise also provides tags, Visualizer workflows, RIOT/business-service context, CVE-related intelligence, API access, feeds, and GreyNoise Block.

That is useful for:

  • SOC triage
  • threat hunting
  • vulnerability prioritization
  • internet scanner research
  • reducing noisy alerts
  • scanner-informed perimeter blocklists

If those are your primary use cases, GreyNoise may be the right tool.

Where FraudGuard Wins

FraudGuard is built for teams that need IP intelligence to drive production controls:

  • native allow, challenge, and block recommendations
  • risk level, confidence, and reason codes
  • honeypot-observed attack evidence
  • customer whitelist, blacklist, geoblock, and rate-limit context
  • high-volume API economics
  • bulk lookup and offline database workflows
  • flexible support for custom security workflows

This matters because not every risky request should become a permanent firewall block. Some traffic should be challenged, rate limited, routed to review, allowed because of a customer whitelist, or handled differently based on business rules.

FraudGuard is built for that app/API policy layer.

Full API Example

GreyNoise Community API examples are useful for scanner context: noise, riot, classification, name, Visualizer link, and last-seen date.

FraudGuard ACE v2 is designed to return an enforcement-ready decision with risk, evidence, customer policy context, infrastructure context, network data, and geography in one response. This is the full example response from the FraudGuard ACE v2 IP Intelligence documentation:

{
  "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"
  }
}

GreyNoise output helps explain scanner context.

FraudGuard output helps enforce customer policy.

Custom Security Work

FraudGuard is a small technical team. For customers that need flexibility, that is an advantage.

If your use case requires a custom feed, WAF workflow, offline database format, enrichment pipeline, abuse-review process, MSP workflow, or application-specific enforcement pattern, FraudGuard can work directly with you to design a practical solution around FraudGuard data.

That does not mean every custom request is automatically included in standard pricing. It means you can have a technical conversation with the people building the product instead of being forced into a rigid package.

Bottom Line

GreyNoise is a strong product for scanner intelligence, SOC triage, threat hunting, CVE context, RIOT/business-service context, and scanner-informed perimeter blocklists. If that is the job, it is worth evaluating.

FraudGuard is the better choice when the job is production IP reputation: app and API decisions, allow, challenge, and block outcomes, customer-specific policy controls, honeypot-observed attack evidence, public pricing, no mandatory sales call, and no annual contract for standard plans.

It is also the more practical option for teams that want flexibility. If your security workflow needs a custom feed, WAF pattern, offline data format, enrichment pipeline, MSP workflow, or other architecture around IP risk data, FraudGuard can work with you directly.

Try FraudGuard free - use the public lookup tool, start a trial, integrate the API directly, or email hello@fraudguard.io to talk through a custom security workflow built around FraudGuard data.

Looking for more competitive comparisons? Check out FraudGuard vs AbuseIPDB: Community Reports vs Observed Attack Evidence, FraudGuard vs IPinfo: Geolocation Alone Is Not Threat Intelligence, and FraudGuard vs CrowdSec: Host Remediation vs API-Level Threat Decisions.