Run FraudGuard ACE locally with SQLite and CSV.
The Offline Threat Database is built for environments where live API calls are not practical for every decision. Instead of sending every lookup across the network, teams can download FraudGuard threat intelligence in local database formats and run enrichment, blocking, and large-scale analysis inside their own infrastructure with zero API latency and zero request-by-request overhead.
What it is built for
Firewalls, SIEM pipelines, WAF enrichment, internal data lakes, fraud review queues, and any workflow that wants FraudGuard intelligence without live external dependency.
Why teams buy it
The Offline Threat Database gives teams line-rate local access to FraudGuard intelligence when API calls are not the right operational tradeoff.
Why teams choose offline intelligence instead of live API lookups
The live FraudGuard API is the right answer for many workflows. The Offline Threat Database exists for the others: massive event volume, restricted networks, tight latency targets, and environments where local control matters more than per-request round trips.
Zero lookup latency
Keep the decision local so blocking, enrichment, and scoring can happen at system speed inside your own environment.
High-throughput enrichment
Process huge log volumes without turning every row into a live external API transaction.
Data-residency-friendly workflows
Keep logs, IPs, and enrichment logic on your side of the boundary when the environment or customer contract requires it.
Simple integration surfaces
Use familiar local database and flat-file patterns in places where API integrations are awkward or impossible.
How the Offline Threat Database fits into production
The Offline Threat Database gives teams the same general intelligence family behind FraudGuard's live products, but in a form that can be distributed, queried, and refreshed locally. That matters for security teams running high-volume detection, firewall operators pushing policy locally, and environments where an internet dependency in the query path is unacceptable.
Some teams use it for SIEM enrichment, some for firewall block decisions, some for air-gapped review tooling, and some because they want to keep abuse analytics inside their own data plane. The product is intentionally practical: simple formats, simple update paths, and clean compatibility with internal tooling.
That makes it one of the easiest ways to operationalize FraudGuard intelligence outside the live API model.
Download once, query locally
Keep the data near the systems that need it instead of creating a remote dependency for every decision.
Use familiar data formats
SQLite and CSV make the product easy to integrate into both modern pipelines and older operational tooling.
Refresh on the right cadence
Choose the update schedule that matches your plan and your operational tolerance for freshness windows.
Fit sensitive environments
Support high-governance or network-restricted systems where a live external API is a policy problem.
Typical offline intelligence workflow
The operational model is intentionally direct: download, load, query, refresh.
Download the package
Pull the current SQLite or CSV dataset according to your plan's refresh model.
Load it into local tooling
Stage the data where firewalls, SIEMs, ETL jobs, internal services, or analysts can query it directly.
Run local intelligence decisions
Enrich events, score IPs, or build enforcement logic without leaving the environment for each request.
Refresh on schedule
Update the local data on the cadence that matches your plan and operational needs.
Where the Offline Threat Database is most useful
Offline intelligence is especially valuable in workflows where local control, scale, or infrastructure constraints outweigh the convenience of a live API call.
Firewall and network enforcement
Apply FraudGuard intelligence directly in systems that already make local block or allow decisions.
SIEM and data-lake enrichment
Enrich very large event volumes without turning the pipeline into a live lookup bottleneck.
WAF and request-log analysis
Score attacker infrastructure locally across blocked-request logs, traffic archives, and historical review jobs.
Air-gapped review tooling
Keep intelligence available in environments that cannot query live external services at all.
Fraud-review backends
Support internal fraud models and review workflows with local IP intelligence at scale.
Batch analytics and replay
Run large historical jobs where a live per-record API call would be too slow or too expensive.
Best-fit Offline Threat Database customers
This product is strongest where local intelligence execution is not a nice-to-have but an operational requirement.
Air-gapped or restricted environments
Teams that need FraudGuard intelligence available locally because external lookups are not allowed in the query path.
High-volume security pipelines
Operators who enrich enormous event volumes and want a simpler, cheaper local path than API-per-record processing.
Latency-sensitive enforcement teams
Environments where local query speed and infrastructure independence are more important than live network lookups.
Put FraudGuard intelligence inside the systems that need to move fastest
The Offline Threat Database gives teams a direct way to use FraudGuard data locally for high-throughput enrichment, restricted-network workflows, and enforcement paths where live lookups are the wrong architecture. That is what makes it so useful in real production environments.