January 14, 2026
12
minutes read
CTV ad fraud is no longer a fringe problem, it’s the quiet leak that turns “great” CTV performance into wasted ad spend and unreliable reporting. In this article, we’ll break down how CTV fraud actually works, why connected TV is uniquely vulnerable, and the practical steps marketers can take to protect their budgets without sacrificing scale.
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CTV is one of the most attractive channels in digital media because it combines television’s format with programmatic targeting and reporting. The downside is structural: the channel is fragmented (devices, apps, SSAI, intermediaries), measurement is inconsistent, and supply paths can get messy fast.
That matters because fraud doesn’t usually show up as a single obvious “bad app.” In CTV, fraud often shows up as slightly-too-good performance, unclear app transparency, or “direct” inventory that isn’t actually direct.
💡 If you want more context on how fast this channel is growing and what that means for planning, AI Digital has two dedicated pieces: CTV guide & connected TV stats.
If you’re planning or buying big-screen video, this guide will help you pressure-test what you’re buying and build practical defenses against CTV fraud and CTV ad fraud—without turning your team into a forensic lab.
CTV ad fraud is any deliberate manipulation that causes advertisers to pay for CTV impressions that aren’t legitimate—because they weren’t seen by real people, weren’t served in the claimed environment, or weren’t sold by an authorized seller.
Most fraud in CTV falls into one (or more) of these buckets:
CTV buying is still programmatic buying under the hood, which means the same ad tech plumbing (OpenRTB, exchanges, SSPs, verification, SPO) applies—just with CTV-specific twists like SSAI and device fragmentation.
💡 If you want a refresher on the mechanics, AI Digital’s programmatic advertising explainer is a useful baseline.
⚡ If you can’t clearly identify the app, the device, and the seller, you’re not buying “premium CTV”—you’re buying a guess.
CTV isn’t “more fraudulent” by nature. It’s more vulnerable because the ecosystem has several built-in properties that fraudsters can exploit.
Unlike desktop browsers (where the web stack is comparatively standardized), CTV delivery happens across:
That fragmentation makes it harder to apply uniform standards for measurement, viewability, and verification.
⚡ Fragmentation isn’t just a planning headache. It’s a perfect hiding place for mislabeling, because each device and app behaves a little differently.
One of the clearest CTV risk signals is missing or partial app transparency. DoubleVerify reported that only 50% of CTV impressions offered full app transparency in 2024, creating real blind spots for marketers.
When app transparency is missing, it becomes easier to hide spoofing, reselling, and unauthorized paths inside “CTV” labels that look acceptable in platform UI.
Server-side ad insertion (SSAI) improves streaming experience (less buffering, smoother playback), but it can reduce what the buyer can verify at the client level. Fraud thrives when the observer can’t directly validate playback conditions, device characteristics, or ad rendering events.
The market growth itself is a risk factor. IAB estimates U.S. CTV ad spend reached $23.6B in 2024 (up 16% YoY) and is projected to hit $26.6B in 2025—a pace of growth that keeps attracting fraud to any part of the supply chain that isn’t tightly verified.
Fraud in CTV rarely arrives as “fraud.” It arrives as inventory.
Here’s a practical way to think about the entry points:
In programmatic CTV, the buyer often relies on bid request data to understand:
If those signals are falsified—or if key fields are missing—the buyer’s ability to validate the environment collapses.
A common pattern in CTV fraud is inventory presented as “direct” that isn’t actually authorized as direct.
Pixalate’s SPO research found that 28% of CTV traffic with SupplyChain Objects marked ‘complete’ was sold by unauthorized “direct” sellers, representing an estimated $1.4B in global open programmatic CTV ad spend routed through those unauthorized sellers (Q3 2024).
Even if you don’t treat that dollar amount as a perfect “loss” figure, it’s a strong signal about how often supply chain declarations don’t match reality—and why “direct” labels alone shouldn’t satisfy your QA.
Supply path sprawl creates room for:
This is exactly why SPO isn’t just an efficiency play—it’s a fraud control practice.
💡 AI Digital’s perspective on supply-side optimization goes deeper on how curation and cleaner paths reduce waste.
⚡ CTV fraud doesn’t need to beat your strategy. It just needs to blend into your reporting.
You don’t need to memorize every variant. You do need to recognize the shape of the major schemes, what they break, and what data can expose them.
This is the CTV version of “identity fraud”—the impression claims to come from a premium TV device, even when it doesn’t:
💡 For broader context on fraud and supply protection principles that apply here (not just CTV), AI Digital’s “Safety in programmatic advertising” is a helpful companion.
When ads are stitched in server-side, fewer on-device signals make it easier for bad actors to fake where, how, and whether an ad actually ran:
⚡ When completion rates start looking perfect, treat it as a prompt to verify, not a reason to celebrate.
Here, the scam isn’t the impression volume—it’s the label on the inventory, where a low-quality app pretends to be a trusted one:
⚡ In CTV, the app name is the placement. If the app identity is fuzzy, everything else in your report becomes less reliable.
Instead of faking a device or an app, this approach fakes the viewer—using automation to simulate watching at scale:
💡 If you want a higher-level perspective on how automation can introduce blind spots across advertising systems (including traffic quality issues), AI Digital’s “Biggest AI blind spot” piece is worth reading.
This is supply chain fraud by paperwork and plumbing—legit inventory gets rerouted, repackaged, or sold by sellers who shouldn’t be in the path.
💡 AI Digital’s view on supply-side optimizationith AI connects this directly to outcome-based buying and cleaner paths.
CTV ad fraud isn’t just “wasted impressions.” It changes how your entire system learns.
DoubleVerify highlights “TV Off” as a persistent CTV waste problem—ads running even after a TV screen is turned off—and reports that media quality issues can cost advertisers an average of $700,000 in wasted spend per billion impressions without safeguards.
That’s before you get into spoofing, botnets, or misrepresentation.
Fraud often creates metrics that look like success:
If you optimize into those signals, you reinforce the fraud. Your bidder learns “this is what good looks like,” then buys more of it.
This is one reason “good” performance dashboards can mislead growth decisions.
💡 AI Digital’s breakdown of why marketing metrics can lie is relevant here—fraud is one of the fastest ways to turn correlation into false confidence.
If the algorithm is rewarded for cheap CPV/CPM and “perfect video,” it will naturally drift toward inventory that produces those signals cheaply—exactly the environments fraudsters manufacture.
A related challenge shows up in closed ecosystems too: when visibility is limited, it’s harder to verify what happened.
💡 If you’re balancing CTV across open and closed environments, AI Digital’s perspective on the hidden cost of walled gardens adds a useful lens on transparency risk.
This is the quiet cost: CTV ad fraud reduces confidence in the channel. Even if CTV is working, fraud makes it harder to defend results, expand budgets, and scale responsibly.
This is the section most teams want, so let’s make it operational.
Before you change tools, define what you will not buy.
A simple baseline many teams adopt:
If you do nothing else, this alone reduces your exposure to the most avoidable CTV fraud.
Fraud prevention is cheaper before you buy than after you buy.
Integral Ad Science’s 20th Media Quality Report release notes that fraud rates in non-optimized campaigns reached 10.9% by the end of 2024, and were 15x higher than campaigns using anti-fraud technologies.
Even if your CTV stack is different from the open-web benchmarks, the directional lesson holds: you want protection before the auction, not only after reporting.
SPO is often pitched as “reduce fees.” In CTV, it’s also “reduce places fraud can hide.”
Operationalize it like this:
💡 If you want a framework that connects SPO to outcomes (not just CPM savings), AI Digital’s DSP-agnostic buying model and supply-side strategy is a strong reference point.
This is a practical QA move that doesn’t require special tooling:
Any one of these can be legitimate. Together, they’re a reason to investigate.
Many CTV fraud issues aren’t solvable solely in a DSP UI. You need vendors and sellers to provide:
Industry standards are moving in that direction. For example, IAB Tech Lab has promoted approaches like device attestation in CTV to help validate that a device is what it claims to be (a direct counter to spoofing).
Verification vendors are essential—but they’re not a strategy by themselves.
Use them to:
But keep internal decision rules about what inventory you’ll accept.
💡 If you’re building a more transparent buying approach across multiple DSPs and supply partners, AI Digital’s Smart Supply and Open Garden philosophy is directly aligned with that goal.
This is where teams get stuck, so let’s split responsibility cleanly.
You can’t fix the whole ecosystem, but you can shrink your risk surface.
Buying controls – These choices determine which inventory even has a chance to enter your plan:
Measurement controls – If your measurement rules are loose, fraud gets to hide inside “acceptable” reporting:
Optimization controls – Guardrails here stop your models from learning the wrong lessons from contaminated data:
💡 AI Digital’s DSP-agnostic model is useful here because it emphasizes keeping decision rights with the advertiser rather than defaulting to any single platform’s incentives.
This is where you should push hard in vendor reviews and QBRs.
Supply-side accountability – This is about proving who is allowed to sell the impression—and removing anyone who isn’t:
Device and SSAI integrity – Vendors need to make the environment verifiable, especially when SSAI reduces what buyers can see:
Operational standards – Baseline standards make fraud prevention consistent, repeatable, and enforceable across partners:
A useful macro lens here: TAG’s 2024 U.S. Ad Fraud Savings Report estimates anti-fraud standards and programs resulted in $10.8B in savings in 2023, reducing likely IVT losses dramatically. That’s the argument for why ecosystem-wide discipline matters—not just individual advertiser settings.
CTV fraud is not going away. But the control surface is changing.
Here are the trends most likely to shape the next phase:
As mentioned previously, IAB projects continued CTV growth through 2025. But the bigger signal is structural: it also expects digital video to capture nearly 60% of total TV/video ad spend in 2025, extending the shift of money (and attention) toward streaming environments. That makes supply integrity, seller authorization, and device validation even more important because the stakes keep rising.
Expect faster adoption of device-level validation, because the industry now has proof that “counterfeit CTV” isn’t theoretical.
In an October 2025 study, CleanTap demonstrated that low-cost counterfeit setups (e.g., Raspberry Pi + emulators) could successfully receive premium CTV ads—ads from 54 brands (including nine Fortune 100) were served through transactions spanning five sell-side and four demand-side platforms, and 100% of the counterfeit activity was accepted into live auctions.
That’s the backdrop for standards work like IAB Tech Lab’s device attestation support in the Open Measurement SDK (OM SDK), which launched with support on Apple devices and Fire TV and is designed specifically to counter device spoofing with privacy-preserving attestations.
Fraud is shifting from noisy, brute-force patterns to “quiet” automation that imitates real viewing behavior. DoubleVerify’s Fraud Lab has tied that acceleration directly to GenAI: it reported an over 20% surge in new fraud schemes, alongside an almost 60% increase in audio and video streaming fraud schemes and variants, and noted that bot fraud schemes targeting streaming platforms produced 269% more variants in 2023.
That pace forces defenders to evolve too — verification is moving toward faster pattern recognition, upstream filtering, and better authentication signals (rather than relying on slower, downstream reporting). The net trend is simple: the “easy” bots aren’t the main threat anymore; it’s the ones designed to look normal.
Supply-chain scrutiny is becoming a baseline buying requirement because open CTV still shows frequent seller misrepresentation—even when the bidstream includes SupplyChain Objects (SCOs). Pixalate’s CTV Apps SCO verification research found that 29% of app traffic with an SCO failed verification due to unauthorized sellers, and 36% of purported direct sellers in that traffic were unauthorized.
When that level of mislabeling is possible, “set it and forget it” buying stops being defensible. Over the next 12–24 months, more buyers will treat SCO checks, seller verification, and SPO discipline as ongoing governance—similar to how brand safety moved from periodic audits to continuous controls.
💡 If you want a broader view of where media is heading (and how CTV fits into the 2026 planning picture), AI Digital’s media trends 2025 overview and media trends report 2026 are a good companion reads.
CTV is too valuable to ignore and too complex to buy casually.
The safest way to approach CTV ad fraud isn’t to panic or to assume every anomaly is theft. It’s to build a repeatable operating model:
When you do that, CTV becomes what it’s supposed to be: a scalable, measurable, high-impact video channel without the hidden leakage that quietly eats ROI.
If you want clearer control across planning, optimization, and reporting, AI Digital’s Elevate combines an AI planning assistant, predictive forecasting, and always-on optimization, including real-time inventory analysis via multi-DSP integrations and “Ask Elevate” for plain-language performance explanations.
And if you’d like to talk through any of the insights in this article — or sanity-check what you’re seeing in your CTV buys — reach out to us directly.
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Audience segmentation and insights
Identify and categorize audience groups based on behaviors, preferences, and characteristics
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Automate ad creation, placement, and optimization across various platforms
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Monitor and analyze public opinion about a brand across multiple channels in real time
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Analyze data to predict optimal campaign approaches, channels, and timing
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Generate content ideas, predict performance, and optimize distribution strategies
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It’s common enough that you should treat it as a baseline risk, not an edge case. DoubleVerify says that without adequate protections, more than 1 in 4 CTV video impressions would fail minimum criteria for fraud-free, viewable, brand-safe, and brand-suitable delivery. Separately, Pixalate’s Q2 2025 analysis of open programmatic traffic with SupplyChain Objects found 14% of CTV app traffic failed verification due to an unauthorized seller, and 15% of “complete-chain” CTV traffic was sold by unauthorized direct sellers—a strong signal that seller misrepresentation is still routine in CTV supply paths.
It depends on how you define “worse.” DV reports bot fraud makes up 65% of CTV fraud, and that share is 14% higher than in other digital channels, which suggests CTV is especially attractive for bot-driven schemes. On the other hand, Pixalate’s Q2 2025 SCO verification results show mobile apps had a higher “failing verification” rate (35%) than CTV apps (14%) and desktop web (10%), even though CTV showed a higher rate of unauthorized direct selling than web. The practical takeaway: CTV isn’t automatically “more fraudulent,” but its fraud often hides behind weaker transparency and premium pricing.
No, AI can reduce risk, but it won’t “solve” fraud on its own because attackers also adapt quickly. DV notes that in just one quarter it identified 12 new CTV bot variants, and that a single bot variant can drive more than $7.5M per month in wasted media at typical CPMs. What’s changing the game is combining detection with stronger authentication signals, like IAB Tech Lab’s device attestation support in the OM SDK, which lets buyers verify genuine devices via privacy-preserving attestations from manufacturers.
Ask for proof you can audit: “Will you provide app transparency (bundle/app name) at scale, and what percentage of impressions have it?”; “Can you show the SupplyChain Object and confirm sellers are authorized via app-ads.txt/sellers.json?”; “What pre-bid IVT/fraud controls are running, and are they independently validated?”; “Do you support OM SDK measurement and device attestation where available?”; “Will you provide log-level data or equivalent diagnostics for investigations, and what’s your makegood/refund policy for invalid traffic?” The reason to be direct is simple: unauthorized selling is still measurable in the ecosystem, including in traffic that claims a “complete” chain.
There isn’t a single universally accepted global number for CTV-specific fraud losses because measurement and classification differ by vendor and market, but the wider picture is clear: Juniper Research forecasts global advertising spend potentially lost to fraud rising from $84B in 2023 to $172B by 2028. Within CTV specifically, DV’s analysis shows how quickly losses can scale—estimating more than $7.5M per month in waste from just one bot variant at average CPMs.
To protect your budget from connected TV fraud, start by tightening what you’re willing to buy: prioritize inventory with clear app transparency, validated supply paths (authorized sellers and a clean supply chain), and independent verification running pre-bid where possible. Then monitor for “too perfect” patterns—like uniform completion rates or suspicious delivery spikes—and be ready to cap spend, isolate the specific apps/sellers causing anomalies, and block quickly while you request diagnostics and makegoods.
Some of the top ad verification tools used for CTV and broader digital include DoubleVerify, Integral Ad Science (IAS), Human Security (HUMAN), and Pixalate; many marketers also rely on measurement partners like Comscore or Nielsen for audience validation, depending on the campaign’s goals and buying setup.
