Brand Safety Tools in 2026: The Complete Guide to Protecting Your Ads, Budget, and Reputation

The issue with most of the brand safety tools out there today: They’re describing an industry that ceased to exist a long time ago.

Despite Oracle shutting down its entire advertising business in 2024 and bringing Moat and Grapeshot with it, both are featured on best of 2026 lists. In August 2024, the industry body that penned the rulebook on brand safety categories, GARM, ceased to exist following a lawsuit by Elon Musk’s X for antitrust violations. One of the two companies that the majority of people in this area use was Integral Ad Science, which went private via a buyout that ended in December 2025. But a series of investigative reports has quietly been chipping away for the past two years at the industry’s most popular marketing promise: Your ads can be made “100% brand safe” with any tool.

But all that doesn’t mean that brand safety tools ceased to be relevant. They matter more than ever, given the amount of AI-driven content that is being produced and pushed onto the open web, as well as budgets for programs growing faster than human teams can manually review. However, the situation has evolved enough to make many of the go-to tips obsolete. So what they actually are in 2026, which ones are worth the money, and how to make sure your strategy doesn’t die the next time a vendor pulls the plug on their company.

What Brand Safety is and isn’t (and why it’s not brand suitability)

In its most basic form, brand safety is all about avoiding exposure of your ads to content that could negatively impact brand perception, violence, hate speech, adult content, illegal activity or misinformation. It’s not the ceiling, it’s the floor! This bucket is agreed upon by nearly all advertisers, no matter what category or tone their ads are.

Whether it is a suitable brand is another thing, one that most of the guides do not even address. Suitability is a question of whether the piece of content is actually appropriate for your brand, even if it’s safe. A financial services company may be okay with ads on sober economic news, but not next to celeb gossip, but nothing unsafe about gossip, it’s just off-brand. There is no content that an alcohol brand cannot handle that would make a kid’s toy company uneasy. But a light, fun brand can sound out of place in the midst of serious media reporting, even if the reporting is correct.

This difference alters what variety it is you really need to be purchasing. Any brand safety tools with hard-coded and aggressive default settings will block you from perfectly safe content because it is close to a sensitive topic, and when you are discussing real news about real events, the keyword filter doesn’t know the difference from something that is truly harmful. Brand suitability tools allow you to do just that and decide which brand is suitable for your brand based on your brand’s tolerance, rather than giving it the lowest common denominator filter.

This is a difference advertisers can’t continue to ignore. According to Amazon Ads’ 2024 research, 82% of consumers reported that it’s important for them that online ads are surrounded by suitable content. 65% of global marketing and advertising decision makers are concerned with the suitability of placements on social platforms, not just with safety infringements, according to DoubleVerify’s 2025 Global Insights report. Many people are concerned about a problem that “block the bad words” filters are not designed to solve.

The Brand Safety Landscape in 2026 is Totally Different

If you’ve been reading older brand safety articles, you’ve likely taken in a few presumptions that are no longer true. So it’s worth getting these out of the way, as they impact what tools you have at your disposal.

Although GARM is no longer, its framework remains largely intact. Global Alliance for Responsible Media had been an industry de facto rule book for five years. Its Brand Safety Floor and Suitability Framework provided advertisers, publishers and verification vendors with a shared vocabulary, eleven categories of universally unsafe content, and a tiered suitability scale that brands could customize to their level of risk. In August of 2024, X Corp sued GARM for allegedly collaborating in an advertiser boycott against the platform in violation of antitrust laws. GARM was completely closed by the World Federation of Advertisers within days, claiming the allegations “significantly drained” its “resources and finances. X’s lawsuit was filed against a federal judge, who dismissed the case in March 2026, after X had been disbanded.

Where most summaries have fallen short: Publishers, platforms, and verification vendors such as IAS and DoubleVerify have continued to primarily utilize GARM’s taxonomy even after the shutdown, since it’s impractical to start over from scratch to create a new taxonomy. So when you hear stories about “GARM-aligned” categories in a tool’s settings today, it’s a legacy standard that is no longer being maintained, not a live evolving one, and no one is working to update it for a media environment that is full of AI-generated content. That’s an actual issue that remains unsolved.

The Oracle departure had an impact. Oracle ended its advertising operations in 2024, including its acquisition of Moat for ~$850 million in 2017 and Grapeshot for ~$400 million in 2018, two brands that continue to be mentioned throughout older “top brand safety tools” roundups. Both are gone. If you see a list that mentions the “Moat by Oracle” in 2026, then the list has not been updated since the tool no longer exists, and everything else in that list needs to be re-evaluated.

Integral Ad Science was formerly a public company. In December 2025, one of the two leading verification platforms, IAS, which was acquired by investment firm Novacap, went private. It’s still running, still releasing new products and still one of the top choices available, but the publicly traded ad-verification duopoly is no longer accurate and important to note if you’re in the midst of vendor due diligence.

But with a line-up of watchdog reports, 100% brand safe is no easy promise to take on faith. Ad-tech research firm Adalytics has released a series of investigations that have uncovered ads from major brands appearing on pages that ad-verification platforms have deemed safe, such as ads by brands appearing on free image-hosting sites used for child sexual abuse content in a 2025 report, while ad-verification software from IAS and DoubleVerify rated the same placements as safe and suitable. The report led to two U.S. senators writing letters to the CEOs of DoubleVerify, IAS, Google and Amazon. DoubleVerify responded with a new content category called Highly Illicit: Do Not Monetize, while both companies challenged portions of Adalytics’ methodology, neither denied that the placements had taken place. Adalytics had previously reported seeing ads appearing beside slurs and explicit material on popular wiki sites, even though the ads themselves were marked as “safe” by the major ad tools.

But none of this is to say that the tools are of no use, they snag a ton of real junk that you would otherwise let go of. In fact, it is not a “100% brand safe” guarantee, as you will see repeatedly in vendor marketing. It is not a guarantee, it’s a goal, and you’ll create a much more robust strategy than one that is based on a blind belief in a dashboard.

How Brand Safety Tools Actually Work: Pre-Bid, Post-Bid, and Where Both Fall Short

The majority of brand safety platforms function at two distinct stages of the ad-buying journey, and the distinction offers a lot of insight into why ‘safe’ placements aren’t always safe.

Pre-bid tools screen inventory before you buy it. They are added to your demand-side platform and check web pages, videos, or apps prior to your ad being displayed, and if it is not safe or suitable, they block the bid altogether. This is the more effective solution, as it prevents the impression from occurring in the first place, but this requires that the tool has successfully read content that it may not have crawled in a while, and this is where gaps can occur.

Post-bid tools are not used until after the bid has taken place. They track the actual impressions of your ads, identify or fold ads that would appear in a hazardous location and report back to your exclusion lists. It’s called a safety net, and it is a safety net, but it is by definition, an impression that has already been shot somewhere you didn’t want to.

Both overlook the real work of the content analysis, which is underneath. Traditional brand safety technology relies heavily on keyword blocklists: block the keywords and any page that contains them is automatically blocked. The trouble is, keywords don’t have any idea of context. Throughout the years that GARM’s framework was actively maintained, it was treated as medium to high risk by default for political news, and publishers have been complaining for years that the relatively blunt brand safety measures effectively demonetize their legitimate journalism by blocking ads that use the word “shooting” in their titles as well. Nowadays, newer ones rely more on contextual and semantic AI, which reads meaning and sentiment, rather than matching strings of content and tend to be better at figuring out whether something is a genuinely tragic news item or whether it is truly gratuitous. Good, but not a gadget, technology that has a purpose. The above Adalytics results occurred despite the use of AI-based classification in the process.

The lesson to be learned: regardless of platform, understand if a control is pre or post-bid, and don’t assume that a control with a “low risk” content score means someone has actually looked at the page.

The Brand Safety and Ad Verification Platforms Worth Knowing in 2026

DoubleVerify is one of the two largest independent verification firms, and the sole one of the two publicly traded (NYSE: DV). It recently finished 2025 with a 14% growth from the previous year to $748.3 million in revenue, and in its first quarter of 2026, it reported that social and CTV measurement increased. In addition to its pre-bid and post-bid brand safety safeguards, DoubleVerify has strongly invested in newer challenges: DV Content Lens is a granular, content-level reporting feature inside social platforms like Meta’s Feeds and Reels; and AI SlopStopper is a combination pre-bid avoidance and post-bid monitoring product targeting low-quality, AI-generated content environments. It’s a solid default option for advertisers looking for open web, CTV and social in a single contract.

Integral Ad Science (IAS) is DoubleVerify’s biggest competitor and, following its December 2025 acquisition by Novacap, a private entity. The Optimization segment, which is pre-bid filtering directly within major DSPs, is the largest business line, while its brand safety and suitability suite continues to be one of the most deployed in the industry. On the AI front, IAS has been rolling out Quality Sync and Context Control Avoidance, features that enable it to keep ads off of low-quality AI-generated pages, and an AI Assistant named IAS Agent that it was demoing at CES 2026, claiming to be about 50% more efficient for media teams when it came to campaign insights. If you are already using a DSP that integrates well with IAS, it makes sense to go private, as the frequency of releases hasn’t abated due to going private.

Instead, Zefr doesn’t aim to cover the entirety of the open web, it focuses on walled gardens, in this case: YouTube, Meta, TikTok, and Snap. That focus, recently, proved to be fruitful in a significant manner: Zefr is the first third-party vendor to achieve Media Rating Council accreditation for content-level brand safety and suitability, initially for YouTube in-stream video. That’s a much higher standard of accreditation than the property or domain accreditation that most vendors carry, which can guarantee that a website is generally safe but not that what you’re seeing in the video or post you placed is safe, which Adalytics’ reporting has consistently revealed. For this reason alone, Zefr is worth considering if you’re spending your money primarily on YouTube, TikTok, or Meta.

Pixalate specializes in fraud, invalid traffic and compliance monitoring, and has a special strength in connected TV and mobile, where cookie-based verification doesn’t apply and fraud has been most difficult to detect. It’s recognized by MRC for invalid traffic identification and filtration, and is a favorite choice for advertisers whose brand safety concerns are actually fraud concerns dressed up as brand safety, particularly for CTV and in-app inventory.

CHEQ and its self-serve product CHEQ Essentials are more of a fraud-and-bot-protection play than a content-classification play. It’s designed to block invalid traffic, click fraud and fake engagement on paid search and social traffic, not to determine what a given webpage is about and what it’s important to know, so don’t buy it with content-level brand safety scanning in mind. What it gets right is accessibility: CHEQ Essentials’ self-serve, less expensive plans and free trial are one of the more viable options for smaller teams that can’t afford an enterprise DoubleVerify or IAS contract.

Adloox packs viewability, fraud protection and brand safety into one stand-alone verification service, and it has a significant number of customers on the mid-sized advertiser side, especially in Europe. For teams that don’t need the enterprise scalability of DV/IAS, it’s a good alternative to the duopoly.

Confiant, a brand safety tool that’s frequently under the radar in the “top brand safety tools” lists, is dedicated to malvertising and creative-level security, the malicious code embedded into the entire ad, forced redirects, and more that’s hidden within the creative and not on the page itself. It’s slimmer than the above platforms, but it’s designed to close that window for publishers and ad networks that are particularly concerned with weaponized ad creative.

If a list that you read still advocates for Moat or Grapeshot, or if IAS is still characterized as a public company, take everything else in the list with a grain of salt.

Free and Low-Cost Brand Safety Tools for Smaller Budgets

The enterprise platforms above don’t exist because scanning the open web with AI to the level of content is free. However, if you’re not ready for an enterprise contract, you’re not without recourse.

Take advantage of pre-existing controls already offered in the platforms you are investing in. Google Ads allows advertisers to ban content categories, set a ceiling on the digital content label and disable Display Network site and app expansion if they have not audited their traffic and haven’t been satisfied with its result, a feature that Adalytics has separately identified as putting ads on sanctioned and adult sites if left unchecked. Meta, YouTube and TikTok all have their own brand suitability and inventory type filters that you can restrict beyond their default thresholds and it won’t cost you a penny except for a bit of time.

NewsGuard is a great product to mention, but it’s typically miscategorized as a brand safety product. Not a browser extension that puts ratings on news and information sites to inform programmatic ad placement; it’s a dataset that can be used for that, but a lot more for media literacy and trusting a publisher than to plug into your DSP and block bids, which is what IAS or DoubleVerify does.

For advertisers who are looking to spend but not at enterprise levels, the self-serve tier and free trial of CHEQ Essentials is designed with smaller advertisers in mind and offers invalid traffic and paid media protection without a six figure contract.

But don’t underestimate the low-tech route either extracting placements reports from your DSP or ad platform manually, on a regular basis, and removing anything that you find yourself. It isn’t as quick as automated tooling, but it isn’t nearly as nuanced as content level, either and combined with the native controls above, it accounts for a significant portion of the risk for teams with smaller budgets.

How to Choose the Right Brand Safety Tool for Your Business

There is no one best brand safety tool the best fit will be based on the destination of the brand dollars and the threat.

Generally, a walled garden expert that integrates with each platform’s native tools like Zefr in conjunction with YouTube, TikTok and Meta will perform better than a generalist tool that attempts to do everything. If you’re purchasing broadly on the open web via a DSP, then DoubleVerify or IAS pre-bid filtering makes more sense, as they were designed to fit seamlessly in that workflow. When you consider how much of the issue with CTV or app spend is structural rather than content-related, it’s obvious that a significant portion of the problem is being addressed by Pixalate. But if what’s really keeping you up at night is bots and click fraud, not content adjacency, then CHEQ is a product worth considering independently of the other products here and as a solution in its own right, rather than a brand-safety tool.

The regulated industries, financial, health care, pharmaceuticals, any industry with compliance requirements on where an ad may appear will require the most conservative settings possible and documentation they can provide in the event they are asked by a regulator or auditor where an ad was placed. This can indicate the enterprise level of DV or IAS, both of which are focused on creating a reporting specifically for this kind of audit trail.

With smaller teams and lower budgets, there’s no real answer here other than starting with the platform controls themselves and moving to one of the lower cost ad platforms like CHEQ Essentials if it’s a real issue, and then enterprise tools when paid traffic quality matters to your ad spending. Most of these platforms don’t have flat rate cards, but price based on media spend or impression volume under management, meaning the economics make more sense when you’re managing lots of impressions, which is why you’ll see custom pricing on most vendors’ sites rather than a number.

When your team is distributing content across multiple channels simultaneously, it’s worth considering brand safety planning in conjunction with a broader content publishing strategy, which is where our guide to multi-platform content delivery tools comes into the picture.

Brand Safety Strategy: What Matters Beyond the Tools Themselves

With all of the above, the tools are certainly needed, but not enough on their own. There are a couple of elements that a real strategy requires that are not offered as a standard feature of a dashboard.

Create Inclusion Lists, NOT just Exclusion Lists. While it may be tempting to view the issue of brand safety as a blocklist problem, the reality is that overblown exclusions have a downside: when brands inadvertently exclude themselves from placements seeking zero-risk environments, and when legitimate news coverage of real events becomes demonetized along with the actual harmful content, that’s a downside of overblown exclusions. Having a list of vetted, quality publishers and creators, and buying more towards that list, usually yields a more effective and safer campaign than exclusions alone.

Don’t use vendor defaults but write an actual brand suitability profile. What is no-go for kid brands is go for alcohol brands and vice versa. No one’s in-the-box setting can know your brand’s unique range of tolerance; it must be set by someone in your camp.

When engaging influencers or creators, interview them, don’t shake hands. More than half of marketers spend 30 minutes or less before vetting any one creator, which is about how long it takes to skim a highlight reel, as opposed to truly looking into their history, according to surveys conducted by eMarketer and Viral Nation.
Request that your vendors report at a page-URL level and not just domain level, and verify it yourself. This is exactly where reporting from Adalytics was an opportunity for advertisers: Since advertisers could only tell which domains their advertisements appeared on, there was no real way for them to catch the issue themselves. Any vendor that isn’t willing to share this kind of information should be questioned.

And establish a regular human check, even if it’s a low level one. The edge case is something that is extremely difficult for computer programs to get right. A manual spot check of your actual placements will catch what you might otherwise not see in a 100% brand safe report, and can be done monthly or quarterly.

The Threat of Real 2026: AI-Generated Content and Made for Advertising Sites

The one thing that has been missing in most brand safety content, even a year or two ago, is the following: The greatest new threat to advertisers these days is not hate speech or violence, categories that the industry has been developing tools to address for a decade. That is mass and algorithm produced content that is technically safe, but should be avoided.

Made-for-advertising (MFA) sites have been around for a while, but now they’re much more affordable thanks to generative AI. These are pages designed solely for the purpose of advertising – extreme advertising density, low quality articles, often AI-generated articles with no editorial control, and traffic paid for with no real fans. Manual spot-checks alone can miss MFA pages cloaked in that way, where some researchers have documented that some pages display a clean version of a page to anyone typing in the URL directly, while showing a completely different version (filled with ads) to visitors arriving via a paid referral link.

It’s a big scale. In 2023 supply chain transparency research, approximately 15% of programmatic impressions, or an estimated $13 billion in annual spend, were ending up on MFA sites, but by mid-2024, the number of such impressions was reportedly around 4% due to industry awareness campaigns. Since then, however, the number of active MFA domains has risen once again, thanks to the affordability of new MFA domains made possible by generative AI, as reported by some ad-tech researchers, including Jounce Media. The direction of travel is far more important than any one snapshot number; content production costs continue to plummet, driving the growth of the supply of poor content that just happens to technically meet traditional brand safety criteria.

It’s not restricted to blatantly-spammy sites either. According to agency Basis, between 2022 and 2024, AI-generated content has risen from about 2% to more than a third of content on platforms such as Quora and Medium, and some estimates predict it will be the source of the vast majority of content on the Web by the end of this decade. None of this content is unsafe in the traditional sense; it’s simply not the type of content advertisers are paying to see alongside. So do consumers: More than half of advertisers told Basis that AI-generated content has become a leading threat to the ad ecosystem, and more than half reported that it is already negatively impacting media quality.

Major verification vendors have begun working towards this. AI SlopStopper from DoubleVerify is a combination of pre-bid avoidance and post-bid monitoring for low-quality AI content environments. On the pre and post bid side, IAS does the same with its Quality Sync and Context Control Avoidance tools. None of this is a complete solution, it’s a whole new problem and the tooling is still catching up, but being able to treat AI slop as its own category separate from traditional brand safety categories, such as violence or hate speech, is rapidly turning into table stakes, not a nice-to-have.

In practice, that means using attention or engagement metrics which is rarely the same as a viewability metric, because an ad that is technically viewable on a low quality page doesn’t necessarily get as much attention from humans as the same ad on a reputable page, relying on curated private marketplaces and inclusion lists rather than taking the open exchange for granted, and considering any sudden influx of cheap, high volume inventory as a red flag, not a celebration of a low CPM.

The trends that brands should watch for beyond 2026

Some changes to keep an eye on, all of which are already happening and not theoretical.

Content-level accreditation will probably be expected by advertisers, rather than being a differentiator. The fact that Zefr’s accreditation is for content-level, not just domain-level, brand safety on YouTube is the first of its kind and it would not be surprising to see DoubleVerify and IAS seek similar accreditation for their own AI content-scanning claims in the near future.

Verification is going beyond where ads have traditionally been played. DoubleVerify has specifically identified AI chatbot advertising as a new category that it is developing measurement for, and agentic AI buying a software that can negotiate and place media without the involvement of humans raises brand safety issues that the industry hasn’t been able to perfect yet. When an AI shopping or research assistant makes an incorrect statement about your product alongside your ad, it’s a brand risk that traditional tools never could have withstood.

Disclosure standards are starting to formalize, slowly. Since January 2026, there have been recommendations for consumer-facing labels for AI-generated content, supported by machine-readable metadata based on C2PA provenance standards through a voluntary AI Transparency and Disclosure Framework. While it’s not required, it could be a step in the right direction for machines to be able to mark AI content, similar to how adult content or violence is marked today.

But, as the cost of real content-understanding AI at scale continues to drop, contextual/semantic analysis will simply continue to replace blunt keyword blocklists. That’s great news for publishers who’ve lost revenue to keyword filters that were unable to distinguish a war crimes investigation from real incitement, and great news for advertisers who have been losing out on truly safe and high quality inventory due to a filter blocking the wrong word.

The Bottom Line

All major verification vendors, including the most respected in the industry, have had an incident at some point where their brand safe label hasn’t been upheld. But it’s not necessarily a counterindication of using these tools, because if you didn’t verify it, it’s worse by every measure. An argument for making brand safety a continuous discipline and not a subscription that you sign-up to and forget about.

The particular tool that you select is not so vital as most guides would have you think. The real question is whether or not a specific context is pre- or post-bid, whether you’re building lists of inclusion instead of just exclusion, whether you’re creating your own definition of brand-safe or accepting the vendor’s definition, and whether or not you treat AI-generated content and made-for-advertising sites as an afterthought. If they do, the tool you’re paying for is then one solid step in a true strategy, not the strategy itself.