Live Honeypot Attack Telemetry
Stream real-world attacker traffic, payload signals, scanner fingerprints, and ACE-enriched threat context directly into your detection, fraud, abuse, and threat intelligence workflows.
What Attack Stream Delivers
Attack Stream gives qualified teams direct access to the adversary-side telemetry behind FraudGuard ACE, packaged for operational use instead of static lookup-only intelligence.
Attacker Infrastructure
Live source IPs, network ownership, hosting context, scanner clusters, activity windows, and signals that help teams separate background noise from meaningful risk.
Payload and Session Signals
Command attempts, exploit probes, authentication behavior, protocol metadata, and session-level event details captured from FraudGuard honeypot infrastructure.
Scanner Fingerprints
Patterns that identify repeat scanners, botnets, automation frameworks, credential-stuffing infrastructure, and emerging campaigns before they land in customer logs.
ACE-Enriched Context
FraudGuard Attack Correlation Engine enrichment adds risk context, historical correlations, severity indicators, reputation signals, and related attacker observations.
Normalized Event Schemas
Work with consistent event fields for source, protocol, timestamp, observed behavior, raw signal, ACE context, and customer-defined filters.
Controlled Data Scope
Filter by protocol, severity, data class, volume, retention, and raw field access so teams receive the signal they can responsibly operationalize.
Built on FraudGuard's Proprietary Sensor Network
Attack Stream is not scraped, recycled, or repackaged public intelligence. It is powered by FraudGuard-operated honeypot infrastructure, long-running attacker observations, and retained telemetry that helps ACE understand how hostile systems behave over time.
Proprietary Infrastructure
FraudGuard operates and maintains its own distributed sensor network, giving customers access to first-party attacker observations instead of delayed third-party summaries.
50+ Honeypot Services
The network currently supports more than 50 honeypot service profiles across common internet-facing protocols, with ongoing expansion as attacker behavior shifts.
Retained Historical Context
FraudGuard retains meaningful telemetry so ACE can correlate repeat infrastructure, recurring scanners, changing payloads, and behavior that only becomes obvious over time.
Constantly Updated Nodes
Sensors are updated as new services, probes, abuse patterns, and exploit families emerge, keeping the feed useful as attackers change tactics.
Who Gets Approved
Attack Stream is valuable because the data is direct, fresh, and sensitive. Access is intentionally gated so the feed supports responsible defensive use and does not become an uncontrolled resale channel.
Approved Internal Use
Best fit for verified organizations using the feed inside their own security, fraud, abuse, or intelligence workflows.
- SOC and threat intelligence teams
- Fraud, abuse, and trust and safety teams
- Detection engineering and incident response
- Cloud, marketplace, financial, SaaS, and platform security teams
Reviewed Case by Case
Some uses are valid but need tighter terms because they involve third-party environments or broader exposure.
- MSSPs and MDR teams supporting named customers
- Security consultants with clear customer authorization
- Academic or private research programs with defined scope
- High-volume use, long retention, or broad raw payload access
Commercial Licensing
Commercial embedding is available, but it is handled separately from standard internal-use access.
- Redistribution, resale, or public bulk publishing
- Embedding telemetry into a paid security product
- Using the feed to power a competing reputation or threat-intel API
- Commercial model training or customer-facing lookup products
How Teams Consume the Feed
Attack Stream can be delivered as operational telemetry, batch intelligence, or a filtered signal feed depending on how your team plans to use the data.
Push Webhooks
Receive JSON events at an HTTPS endpoint for low-latency enrichment, alerting, blocking, and fraud scoring workflows.
Pull API
Poll recent events with cursor-based access, time windows, severity filters, protocol filters, and raw versus enriched field controls.
Object Storage Drops
Land scheduled JSONL, CSV, or custom exports in S3-compatible storage for data lakes, offline analytics, and retention-controlled review.
SIEM and SOAR Pipelines
Shape the feed for Splunk, Elastic, Sentinel, Chronicle, SOAR playbooks, or generic HTTP collectors used by your operations team.
Message Streams
For high-volume customers, FraudGuard can support Kafka, Kinesis, Pub/Sub-style, or customer-managed streaming patterns.
Filtered Indicator Feeds
Consume a narrower feed of high-confidence IPs, domains, scanner tags, and ACE risk context for WAFs, firewalls, and blocklists.
Pricing is based on access level and intended use
Attack Stream is offered as a premium FraudGuard data product. Pricing is quoted per customer and scales with event volume, raw field access, retention, support needs, delivery path, data scope, and whether the feed is used internally or embedded into a commercial product.
- Live honeypot events and attacker infrastructure signals
- ACE-enriched context for internal workflows
- Raw, enriched, filtered, or hybrid feed options
- Data scope definition and responsible-use terms
Separate commercial category
Standard access is scoped for approved internal use. Redistribution, resale, public indicator publishing, commercial model training, competitive reputation products, and embedding FraudGuard telemetry into a customer-facing security product require a separate commercial or OEM data licensing agreement.
This lets defensive teams use the data aggressively inside their own environments while giving vendors, platforms, and data products a clear licensing path.
Discuss LicensingRequest Access to FraudGuard Attack Stream
Email FraudGuard with your organization, intended use case, preferred delivery path, and whether you need internal-use access or commercial licensing.
hello@fraudguard.io