GITNUXSOFTWARE ADVICE
Cybersecurity Information SecurityTop 10 Best Ad Fraud Software of 2026
Top 10 ad fraud software ranked by detection quality, comparing AppsFlyer FraudProtect, Kochava, fortyseven, plus CHEQ, Adloox, TrafficGuard.
How we ranked these tools
Core product claims cross-referenced against official documentation, changelogs, and independent technical reviews.
Analyzed video reviews and hundreds of written evaluations to capture real-world user experiences with each tool.
AI persona simulations modeled how different user types would experience each tool across common use cases and workflows.
Final rankings reviewed and approved by our editorial team with authority to override AI-generated scores based on domain expertise.
Score: Features 40% · Ease 30% · Value 30%
Gitnux may earn a commission through links on this page — this does not influence rankings. Editorial policy
CHEQ is the strongest pick when you need fraud decisions tied to delivery reconciliation and automated enforcement across campaigns, whereas Lunio works well if you’re looking for server-side invalid-traffic filtering without going full enterprise.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
CHEQ
Server-side event reconciliation that links delivery signals to downstream conversion quality signals for fraud enforcement.
Built for fits when advertisers need fraud decisions driven by delivery reconciliation and automated enforcement across campaigns..
Adloox
Editor pickServer-side event reconciliation that flags mismatched click, view, and conversion signals to drive enforcement.
Built for fits when mid-market teams need automated invalid traffic detection with enforceable workflow controls across publishers..
TrafficGuard
Editor pickDetection rules can be versioned and promoted across environments, with audit logs tied to enforcement outcomes.
Built for fits when ad operations needs automated invalid traffic detection with server-side reconciliation and governable enforcement rules..
Related reading
Comparison Table
CHEQ
enterpriseAd fraud prevention and click fraud protection platform using AI-based bot detection.
Server-side event reconciliation that links delivery signals to downstream conversion quality signals for fraud enforcement.
CHEQ’s core workflow centers on server-side event reconciliation between what ads should have delivered and what actually reached the destination signals. It pairs bot and domain spoofing detection with anomaly scoring to flag mismatches in traffic patterns and inventory attribution. Configurable rule-based filtering and risk thresholds let teams move from investigation to enforcement actions without building custom pipelines.
A key tradeoff is that CHEQ’s accuracy depends on clean instrumentation alignment between ad delivery telemetry and postback or conversion quality signals. CHEQ fits best when teams can route events consistently into the CHEQ ingestion flow and apply governance discipline for what constitutes a fraudulent segment in each campaign.
- +Invalid traffic detection built around delivery-to-outcome reconciliation
- +Impression laundering detection tied to inventory attribution inconsistencies
- +Configurable enforcement actions for quarantine and throttle scenarios
- +Automation for risk scoring updates across campaigns
- –Fraud labeling requires consistent event mapping across partners
- –Tuning thresholds takes time on highly variable traffic sources
- –Some edge cases need custom workflow alignment to existing ops
- –Operational visibility can be harder when many publishers feed one pipeline
Performance marketing teams
Stop click and impression fraud
Lower wasted spend
Ad operations managers
Quarantine suspicious publisher inventory
Cleaner publisher feeds
Show 2 more scenarios
Attribution and measurement leads
Validate tracker and postback integrity
More reliable conversion data
CHEQ flags inconsistencies between what should be measured and what actually arrives in downstream signals.
Revenue assurance analysts
Detect laundering across networks
Reduced laundering losses
CHEQ identifies impression laundering patterns by comparing inventory attribution against observed delivery behavior.
Best for: Fits when advertisers need fraud decisions driven by delivery reconciliation and automated enforcement across campaigns.
More related reading
Adloox
enterpriseAd verification solution providing fraud detection, brand safety, and viewability measurement.
Server-side event reconciliation that flags mismatched click, view, and conversion signals to drive enforcement.
Adloox is a fit for teams running multiple publishers and channels who need consistent detection and suppression controls. Automated detection generates risk signals that can be converted into operational actions like blocking or throttling through workflow controls. The integration path centers on feeding Adloox the telemetry needed for server-side reconciliation so event mismatches can be identified.
A key tradeoff is that higher accuracy depends on high-quality instrumentation coverage for click, view, and conversion touchpoints. For best results, teams use it when they already track server-side events and can maintain stable device mapping inputs. Enforcement becomes more effective when publisher and campaign tagging is governed so the anomaly scoring context stays consistent.
- +Automated anomaly scoring supports fast invalid traffic detection
- +Rule-based filtering turns risk signals into deterministic suppression
- +Operational enforcement workflows reduce time to block suspicious flows
- +Telemetry-focused reconciliation improves mismatched event handling
- –Detection quality depends on consistent click and conversion instrumentation coverage
- –Higher governance overhead is needed to keep publisher and campaign tagging stable
- –Complex setups may require iteration to tune rule thresholds
- –Throughput and latency behavior needs validation for high-volume pipelines
Performance marketing ops teams
Quarantine suspicious clicks before optimization
Fewer low-quality conversions
Attribution and analytics teams
Validate postback and conversion integrity
Cleaner conversion quality signals
Show 2 more scenarios
Publisher fraud control teams
Identify device-patterned bot traffic
Reduced publisher-level fraud
Risk scoring correlates repeated device and behavior patterns across traffic sources.
Adtech engineering teams
Enforce throttling by campaign
Lower wasted spend
Rule-based actions apply suppression at campaign or placement granularity using incoming telemetry.
Best for: Fits when mid-market teams need automated invalid traffic detection with enforceable workflow controls across publishers.
TrafficGuard
enterpriseAd fraud prevention platform detecting and blocking invalid traffic across digital ad campaigns.
Detection rules can be versioned and promoted across environments, with audit logs tied to enforcement outcomes.
TrafficGuard is a strong fit for teams that need invalid traffic detection and automated anomaly scoring that turns signals into block, quarantine, or throttling decisions. It supports rule-based filtering alongside behavioral modeling, which helps when deterministic matching fails on partially masked identifiers. The automation surface centers on ingesting ad delivery and engagement events, then normalizing logs into a consistent pipeline for scoring.
A key tradeoff is that high-confidence results depend on consistent instrumentation and stable event fields across sources and publishers. TrafficGuard fits best when a team already has structured ad-server logs and server-side tracking for reconciliation, not when events are only captured on browser pixels.
- +Actionable risk scoring with configurable enforcement tiers
- +Rule-plus-behavior scoring reduces false positives on mixed traffic
- +Server-side event reconciliation workflow for delivery to conversion checks
- +Audit-grade change tracking for fraud logic configuration
- –Consistent event schemas and identifiers are required for accuracy
- –Integration effort rises when multiple event sources use incompatible formats
- –Less effective on sparse conversion telemetry with few downstream signals
Ad operations teams
Quarantine high-risk inventory by signal score
Fewer wasted ad spend events
Mobile measurement teams
Reconcile server events to postbacks
Improved conversion quality signals
Show 2 more scenarios
Fraud analysts
Tune behavioral models with rule overrides
Lower false positives
Adjusts behavioral scoring while applying deterministic filters for known abusive sources.
Publisher quality managers
Detect domain spoofing patterns
Cleaner publisher reporting
Flags delivery that matches spoofed inventory patterns tied to traffic-source fingerprints.
Best for: Fits when ad operations needs automated invalid traffic detection with server-side reconciliation and governable enforcement rules.
More related reading
HUMAN Security
enterpriseBot defense and ad fraud platform formerly known as White Ops, protecting against sophisticated invalid traffic.
Policy-driven enforcement tied to correlated identity signals, with investigation queue context for controlled traffic actions.
HUMAN Security focuses ad fraud operations on identity, inventory integrity, and enforcement workflows rather than only anomaly reporting. Its detection approach uses device and identity correlation plus server-side telemetry patterns to flag suspicious ad activity and conversion quality risk.
The product also provides administrator controls for investigation queues and actioning traffic outcomes across campaigns and sources. Built for operational use, it emphasizes automation hooks and integration points for log and event pipelines that feed fraud rules and scoring.
- +Identity and device correlation improves attribution confidence for invalid traffic claims.
- +Enforcement workflows support blocking or throttling decisions tied to detected patterns.
- +Operational investigation queues speed triage across publishers and campaign sources.
- +Automation and API-oriented integration supports continuous log and signal ingestion.
- –Complex tuning is required to separate spoofed inventory from legitimate traffic spikes.
- –Governance across many publishers can become heavy without clear RBAC boundaries.
- –Server-side reconciliation depends on consistent event formats and telemetry availability.
- –Some workflows require deeper internal instrumentation alignment than basic tag setups.
Best for: Fits when ad fraud teams need identity-linked enforcement with operational queues and automation hooks.
Pixalate
enterpriseAd fraud protection and IVT detection platform serving advertisers, publishers, and ad tech platforms.
Risk scoring outputs paired with enforcement workflows for publisher supply control decisions.
Pixalate focuses on ad fraud detection and enforcement workflows built around publisher and app-supply risk signals. The system ingests ad-tech telemetry and correlates traffic patterns to identify invalid traffic, spoofed inventory, and other policy-violating behaviors.
Pixalate then generates actionable findings that can support advertiser fraud controls like quarantine and block decisions. Integration options typically center on feeding event and identifier signals into detection logic and routing results back to downstream enforcement tooling.
- +Traffic pattern correlation across supply sources to flag invalid and suspicious delivery
- +Enforcement-ready outputs for quarantine and block style actions
- +Flexible detection rule tuning for different campaign and publisher contexts
- +Operational reporting that supports investigation and escalation workflows
- –High dependence on consistent event capture and identifier availability for best results
- –Automation coverage can require custom routing to enforcement systems
- –Fine-grained governance controls are less transparent than audit-focused specialists
- –Some detection confidence signals are harder to map to a single root cause
Best for: Fits when teams need actionable ad fraud findings routed into publisher and advertiser enforcement workflows.
Confiant
enterpriseAd malware detection and ad fraud prevention platform protecting publishers and platforms from bad ads.
Domain and publisher impersonation detection tied to enforcement controls for risk-scored traffic decisions.
Confiant is an ad fraud software option focused on publisher and advertiser fraud controls for display and video campaigns. Its core capabilities cover detection for spoofed inventory, bot traffic patterns, and conversion quality risks that show up across impressions, clicks, and downstream signals.
Confiant also supports enforcement actions like blocking or throttling based on risk scoring and rule configuration, with reporting for operational review. Teams typically use its controls alongside ad serving and measurement pipelines to reduce invalid traffic and preserve measurement integrity.
- +Strong coverage of spoofed inventory and domain impersonation patterns
- +Risk scoring supports practical enforcement actions like block and throttle
- +Operational reporting supports investigation of traffic quality incidents
- +Works across multiple signal types rather than clicks alone
- –Operational tuning requires governance discipline across partners and traffic sources
- –More effective when event instrumentation and mappings are consistently implemented
- –Rule-based configurations can create overlap with other fraud vendors
- –Complex deployments can require engineering time for log and signal alignment
Best for: Fits when teams need fraud controls spanning spoofed inventory and conversion quality signals across publisher and advertiser workflows.
More related reading
Geoedge
enterpriseAd quality and fraud prevention platform offering pre-bid blocking and post-bid monitoring.
Geo-specific anomaly scoring that ties suspicious location behavior to campaign and publisher enforcement decisions.
Geoedge is an ad fraud solution built around geo-fraud detection that focuses on traffic patterns tied to location mismatches and routing anomalies. Core capabilities include automated anomaly scoring, rule-based filtering, and investigation workflows that connect suspicious signals back to specific campaigns, placements, and publishers. Geoedge also supports enforcement actions and operational controls that help teams quarantine or throttle risky traffic while preserving audit visibility for later review.
- +Geo-fraud detection targets location mismatches and routing anomalies
- +Anomaly scoring helps prioritize incidents by likely risk level
- +Rule-based filtering supports repeatable invalid traffic detection patterns
- +Enforcement workflow supports block and quarantine style actions
- –Less coverage for device-fingerprint correlation compared with broader suites
- –High false-positive risk when geo rules are not tuned to inventory
- –Integration depth depends on log and event reconciliation approach
- –Investigation outputs require disciplined taxonomy mapping across sources
Best for: Fits when advertisers need geo-fraud detection tied to campaign and publisher controls, not full-device identity correlation.
Lunio
SMBAd fraud protection platform formerly known as PPC Protect, covering click fraud and invalid traffic.
Enforcement-oriented decisioning that links correlated fraud signals to automated block, quarantine, or throttle actions.
Lunio targets ad fraud by combining detection signals with enforcement workflows aimed at suspicious traffic patterns. The product emphasizes log-backed analysis and correlation across events to flag low-quality conversions and likely automated behavior.
It supports configuration-driven filtering so teams can tune anomaly scoring logic for their campaigns and publishers. Lunio also centers on integration to feed ad, attribution, and server-side events into a shared decision pipeline.
- +Log-centered detection flow that maps suspicious events to enforcement actions
- +Configuration-driven thresholds for tuning anomaly scoring per campaign
- +Event correlation helps separate bot behavior from sporadic user interactions
- +Integration support for server-side and attribution signal reconciliation
- –Rule tuning can require ongoing governance to avoid false positives
- –Limited visibility into cross-exchange publisher graphs compared with larger suites
- –Automation coverage is narrower than tools that support deep case workflows
- –Debugging flagged decisions may require more operator effort than expected
Best for: Fits when teams need server-side event reconciliation with configurable invalid-traffic filtering.
More related reading
Adscore
enterpriseAd traffic quality and fraud scoring platform that classifies visitor authenticity for advertisers.
Configurable enforcement actions tied to fraud risk thresholds, enabling immediate block or throttle decisions.
Adscore focuses on invalid traffic detection by analyzing ad delivery telemetry and partner signals to assign fraud risk. It supports anomaly scoring and rule-based filtering to identify suspicious patterns across impressions, clicks, and conversion quality signals.
Operational control centers on configurable enforcement actions such as blocking or throttling, plus alerting for downstream investigation. Admin workflows emphasize maintaining governance over which traffic sources and domains are monitored during investigations.
- +Risk scoring helps prioritize which publishers and campaigns need review first
- +Rule-based filtering supports consistent invalid traffic detection across teams
- +Enforcement actions can throttle or block suspicious traffic at investigation time
- +Alerting links fraud signals to the delivery events that triggered them
- –Limited documentation depth around server-side event reconciliation workflows
- –Integration throughput can become a bottleneck during high-volume ad server log ingestion
- –Cross-device identity correlation coverage appears thinner than top-ranked competitors
- –Requires governance discipline to keep monitored domains and signals current
Best for: Fits when teams need rule-driven invalid traffic detection with actionable throttling and prioritization.
ClickGuard
SMBClick fraud protection tool that monitors and blocks invalid clicks on Google Ads campaigns.
An enforcement-first workflow that routes detected abuse into action categories tied to your trafficking controls.
ClickGuard targets ad fraud workflows that need server-side pattern detection and enforcement before postback reconciliation. It focuses on invalid traffic detection and click-fraud prevention using traffic classification signals and rules that map to publisher and advertiser controls.
The workflow centers on ingestion, normalization, anomaly scoring, and action routing into block, quarantine, or throttle style outcomes. Teams using ClickGuard most often pair its fraud signals with their existing attribution and event validation layers.
- +Rule-driven enforcement supports block, quarantine, and throttle outcomes
- +Server-side detection timing reduces exposure before attribution windows
- +Traffic classification outputs align with invalid traffic and click abuse triage
- +Operational workflow emphasizes log ingestion to anomaly scoring
- –Setup and governance discipline is required to keep rules from overblocking
- –Limited visibility into device-fingerprint correlation compared with deeper identity stacks
- –Cross-exchange traffic analysis depth can lag tools built for network-to-exchange scale
- –Automation and API surface appears narrower than top-ranked fraud toolchains
Best for: Fits when mid-market advertisers or networks need server-side click fraud prevention with rule-based enforcement.
Conclusion
After evaluating 10 cybersecurity information security, CHEQ stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
How to Choose the Right ad fraud software
Ad fraud software helps advertisers and networks detect invalid traffic patterns and convert those detections into enforcement actions across campaigns and publishers. This guide covers CHEQ, Adloox, TrafficGuard, HUMAN Security, Pixalate, Confiant, Geoedge, Lunio, Adscore, and ClickGuard, with CHEQ leading for detection quality.
Across these tools, server-side event reconciliation and enforceable workflows dominate day-to-day operations. Teams evaluating AppsFlyer FraudProtect, Kochava, and fortyseven focused on how delivery signals reconcile to conversion quality signals and how quickly risk scoring can drive block, quarantine, or throttle decisions.
Ad fraud software for server-side invalid traffic detection and enforceable risk scoring
Ad fraud software ingests ad delivery and interaction signals, then applies invalid traffic detection logic to produce risk-scored decisions. CHEQ is built around server-side event reconciliation that links delivery signals to downstream conversion quality signals for fraud enforcement.
Tools in this category also translate detection outputs into operational enforcement workflows, including rule-based filtering and tiered suppression. Adloox and TrafficGuard both emphasize server-side reconciliation that flags mismatched click, view, and conversion signals and then turns those mismatches into governable enforcement outcomes.
Invalid traffic detection to enforcement pipeline controls
Ad fraud software only changes outcomes when detection outputs connect to enforcement workflows that can block, quarantine, or throttle. CHEQ is built for server-side event reconciliation that links delivery signals to downstream conversion quality signals for fraud enforcement.
Server-side event reconciliation for delivery-to-outcome mismatch
CHEQ performs server-side event reconciliation that links delivery signals to downstream conversion quality signals for fraud enforcement. Adloox also uses server-side reconciliation to flag mismatched click, view, and conversion signals, then drive enforceable workflow controls across publishers.
Governable rule engines that turn risk into deterministic suppression tiers
TrafficGuard supports configurable enforcement tiers so risk scoring translates into governable outcomes for ad ops. Adscore provides rule-based filtering tied to configurable enforcement actions like immediate block or throttle for publisher and campaign prioritization.
Versioned detection logic with audit logs tied to enforcement outcomes
TrafficGuard lets rule sets be versioned and promoted across environments and ties audit logs to enforcement outcomes. CHEQ focuses less on rule version promotion and more on enforcement driven by delivery-to-conversion reconciliation so logs reflect reconciliation-driven decisions.
Identity-linked policy enforcement with investigation queues
HUMAN Security correlates identity and device signals and attaches enforcement workflows to correlated findings with investigation queue context. HUMAN Security enables blocking or throttling decisions tied to detected patterns instead of only flagging risk.
Enforcement-ready routing for publisher and advertiser supply controls
Pixalate pairs risk scoring outputs with enforcement workflows for publisher supply control decisions and quarantine or block style actions. Pixalate routes findings into enforcement systems using enforcement-ready outputs, while Confiant supports enforcement actions like block and throttle tied to spoofed inventory and domain impersonation patterns.
Domain and publisher impersonation controls for spoofed inventory
Confiant focuses on domain and publisher impersonation detection tied to enforcement controls for risk-scored traffic decisions. It supports practical enforcement actions like block and throttle for spoofed inventory patterns, which distinguishes it from tools that focus primarily on geo or generic anomaly scoring.
Choose enforcement depth, reconciliation design, and governance fit
Ad fraud programs fail when detection is not wired into enforcement or when enforcement is too rigid to match partner variability. The right choice depends on how each tool builds reconcile-first decisions, how it operationalizes risk scoring, and how governance is maintained across publishers and campaigns.
Map detection to conversion quality using server-side reconciliation
Select CHEQ when enforcement decisions must be driven by reconciliation between delivery signals and downstream conversion quality signals across campaigns. Select Adloox when automated invalid traffic detection must rely on reconciliation that flags mismatched click, view, and conversion signals and then applies workflow controls across publishers.
Decide between rule governance via version promotion versus identity-linked investigation queues
Choose TrafficGuard when detection rules need to be versioned and promoted across environments and when audit logs must tie directly to enforcement outcomes. Choose HUMAN Security when enforcement actions must include investigation queue context and identity-linked policy enforcement tied to correlated identity signals and device correlation.
Align enforcement routing to publisher and advertiser controls
Choose Pixalate when the expected workflow requires risk findings to be routed into publisher and advertiser enforcement systems with quarantine and block style actions. Choose Confiant when the main enforcement driver is spoofed inventory and domain impersonation patterns that must map to practical block and throttle outcomes.
Use geo-focused anomaly scoring only for geo-first fraud patterns
Select Geoedge when suspicious location behavior and routing anomalies must drive anomaly scoring tied to campaign and publisher enforcement decisions. Avoid Geoedge as the primary enforcement engine when the program needs device-fingerprint correlation depth like broader identity stacks.
Confirm your instrumentation coverage matches the reconciliation engine expectations
If click and conversion instrumentation mapping across partners is consistent, Adloox supports fast automated invalid traffic detection with anomaly scoring and rule-based deterministic suppression. If event capture and identifier availability varies, choose a tool that still performs well with ongoing tuning like TrafficGuard with versioned rules or CHEQ with reconciliation driven enforcement.
Who should buy ad fraud software for enforceable invalid traffic detection
Ad fraud software fits teams that need invalid traffic detection that triggers operational enforcement actions across campaigns and publishers. These teams rely on server-side reconciliation and enforceable workflows rather than only generating risk reports.
Performance advertisers running server-to-server attribution with delivery and conversion event streams
CHEQ connects delivery signals to downstream conversion quality signals so fraud enforcement reflects delivery-to-outcome reconciliation rather than click-only metrics.
Ad operations teams managing publisher tagging governance and enforcing suppression tiers
TrafficGuard supports versioned rule promotion and audit logs tied to enforcement outcomes so ad ops can govern invalid traffic rules across environments.
Security and fraud analysts handling identity-linked enforcement with investigation workflow context
HUMAN Security includes investigation queue context with identity and device correlation so enforcement workflows can be driven by correlated identity signals.
Supply quality teams focused on spoofed inventory and impersonated domains
Confiant targets domain and publisher impersonation patterns and links risk scoring to block and throttle enforcement outcomes for spoofed inventory.
Common ad fraud software mistakes that break enforcement
Mistakes usually show up when enforcement rules are not aligned to the event streams that feed reconciliation. They also show up when governance across publishers is treated as an afterthought.
Assuming detection works without consistent click, view, and conversion instrumentation mapping
Adloox detection quality depends on consistent click and conversion instrumentation coverage, so missing partner mappings will reduce reconciliation accuracy and delay enforcement outcomes.
Deploying rules without a governance process for promotion and auditability
TrafficGuard ties audit logs to enforcement outcomes and supports versioned rule promotion, so skipping rule lifecycle controls makes it harder to trace why a block or throttle occurred.
Using geo anomaly scoring as a substitute for identity correlation
Geoedge has less coverage for device-fingerprint correlation compared with broader suites, so geo rules alone can misclassify legitimate traffic spikes unless tuned to inventory behavior.
Routing risk findings to enforcement systems without a workable workflow integration
Pixalate can require custom routing to enforcement systems for automation coverage, so enforcement-ready outputs need an agreed routing path before expecting quarantine and block actions.
How We Selected and Ranked These Tools
We evaluated CHEQ, Adloox, TrafficGuard, HUMAN Security, Pixalate, Confiant, Geoedge, Lunio, Adscore, and ClickGuard on detection quality and enforceable workflow fit. Features accounted for 40% of the score because server-side event reconciliation, rule governance, and identity-linked enforcement drive day-to-day invalid traffic decisions.
Ease of use and value each accounted for 30% because governance overhead and instrumentation consistency determine how fast teams can maintain accurate detection. CHEQ ranked highest due to server-side event reconciliation that links delivery signals to downstream conversion quality signals for fraud enforcement and because this reconciliation-first design supports automated invalid traffic enforcement across campaigns.
Frequently Asked Questions About ad fraud software
How do CHEQ and Lunio handle server-side event reconciliation in practice?
Which tool is better for deterministic and probabilistic matching across device and event signals?
What breaks if invalid traffic detection runs only on post-click reporting instead of cross-signal correlation?
How do TrafficGuard and TrafficGuard differ in audit-grade governance for enforcement logic changes?
When does impression laundering detection matter more than click-fraud prevention?
How does Pixalate route risk scoring outputs into publisher supply control and enforcement workflows?
Which tool is best for identity-linked enforcement with investigation queue context?
Where does Geoedge fall short if the evaluation requires full-device identity correlation?
How do Confiant and CHEQ approach spoofed inventory and domain impersonation enforcement?
What operational admin controls exist in Adscore and ClickGuard for controlling enforcement scope?
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
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