How it works

From raw traffic to enforced protection

Every ad request flows through a continuous seven-stage workflow. Nothing is judged on a single indicator, and nothing stops being re-evaluated.

Protection pipeline

Seven stages, running continuously

Step 1

Collect

Traffic and performance signals received from the DSP.

Step 2

Enrich

External reputation and network intelligence added.

Step 3

Analyze

AI, statistical, behavioral and rule-based analysis.

Step 4

Detect

Suspicious patterns and high-risk entities identified.

Step 5

Assess

Signals combined into a risk level.

Step 6

Protect

Configured protection actions applied.

Step 7

Re-evaluate

Continuous reassessment of new and historical data.

Traffic analysis

Every signal. One brain.

AI Defender ingests and correlates the full breadth of traffic, source and performance data available inside your platform.

Ad requestsImpressionsClicksConversionsPublishersDomainsApplicationsPlacementsSite IDsSource IDsIP addressesUser agentsDevicesOperating systemsBrowsersNetwork informationTraffic volumeClick behaviorConversion behaviorSource performanceHistorical performance patterns
Enforcement

Real-time protection & automated source protection

Once risk is assessed, AI Defender acts — instantly on traffic, and progressively on the sources behind it.

Real-time protection

Applied as traffic is processed, within the policy you configure.

  • Flag suspicious activity
  • Reject high-risk traffic
  • Restrict identified sources
  • Apply filtering policies
  • Add entities to protection lists
  • Trigger deeper analysis

Enforcement behavior is fully configurable — from monitor-only to automatic rejection of high-risk traffic.

Automated source protection

Protection lists are maintained automatically across every entity type, with escalation instead of one-shot bans.

IPsPublishersDomainsApplicationsSite IDsSource IDsPlacement IDsUser agents
FlaggedReviewedRestrictedBlacklisted

Escalation thresholds are configurable to the client's risk strategy.

Historical AI analysis

Patterns single requests can never show

Scheduled periodic analysis reviews accumulated traffic and performance data, so slow-moving fraud and quality decay surface before they cost real budget.

Repeated source-quality issues
Long-term anomalies
Traffic-quality trends
Publisher performance changes
Abnormal traffic concentration
Recurring fraud indicators
Unexpected performance changes
Sources needing investigation

Protect your DSP. Protect your advertisers.

See how AI Defender analyses your live traffic, surfaces fraud signals and enforces protection policies automatically inside your DSP.