This New Browser Extension Blocks All Those Junky, Fake Brands on Amazon


If you’re an Amazon shopper, you’ve likely noticed fake brands flooding the website in recent years. A new extension made by developer Josh Pigford promises to hide the phony, cheaply made products and lets you shop like a normal person again. 

The extension, called Knockoff, is available for Firefox, Chrome and all Chromium-based web browsers such as Microsoft Edge, Opera and Brave. Since Pigford launched the extension on Tuesday, it’s gone viral, with tens of thousands of downloads. A few days before this week’s launch, Pigford posted on X, “Built a little chrome extension that lets you dim (or hide!) all the crap, mass-produced, fake brands on Amazon.” The post garnered 22,000 likes. 

It works pretty simply. Once installed, any products from fake brands, dropshippers or otherwise suspicious vendors are marked and grayed out, highlighting the more reputable brands you might actually know. There’s also an option to automatically hide the fake brands so you don’t even have to see them at all. 

In an interview with 404 Media, Pigford says that Knockoff is built on prior extensions that aim to do this, such as AmazonBrandFilter and Amazon Brand Detector. The extension, which runs locally, doesn’t require an account, doesn’t send data to any company servers and doesn’t cost anything. It’s also open source, and you can find the source code on GitHub

A screenshot showing phone cases being grayed out on Amazon

The extension’s functions are pretty simple to understand. If it’s grayed out, it’s likely a fake brand, but the extension does need some fine-tuning.

Joe Hindy/CNET

So, how well does Knockoff work?

Anything sounds good on paper, but the proof is in the pudding. I took Knockoff for a test drive to see how well it filtered the mass-produced junk. 

My trial wasn’t terribly complicated. I searched for a variety of products across several categories using Knockoff’s stock settings to see how well the extension would filter out the knockoff brands without any additional tuning. 

The short answer is that it did quite well. While searching for vacuum cleaners, it left most of the listings intact since they were from known brands including Shark, Bissell and Dyson. Only a few listings were grayed out, mostly because no brand name was listed in the product description. 

Solar lights fared much worse. Knockoff actively blocked dozens of listings for lack of brand names and also blocked listings from Jkimk, Technet, Tonulax and other unrecognized brands (most of which are stylized in all capital letters), while keeping listings for established brands, such as Brightown, a real company based in Raleigh, North Carolina.

A screenshot of Amazon showing products grayed out.

Some product categories did better than others. Solar lights were awash in fake brands, but vacuums only had a few.

Joe Hindy/CNET

Phone cases are where things start to get trickier. The extension blocked brands such as Supfine, Dumkery, Hiearcool and several others. However, it also blocked Torras, a well-known case brand with in-store stock at Best Buy, which holds thousands of global patents for many of its products. It doesn’t get much more real than Torras, but the company’s products were flagged because its name is stylized in all caps, which the extension checks.

Knockoff listed some lesser-known but still legitimate earbuds brands such as Tozo and Linsoul as real companies, while it properly flagged phony hand tool brands including Wgge and Horusdy. Brands that aren’t recognized by the extension often appear highlighted, but on the product page, the extension flags them as suspected fakes or entirely unrecognized. 

It helps that Knockoff has a system for reporting brands that are incorrectly labeled as legitimate (or wrongly marked as fake). If the extension flags a product as fake when it’s legit, you can click the badge and “report as a real brand.” Likewise, if the extension flags a product as legit when it’s really fake, you can click the badge and “report as junk” when you click on a badge over a brand that the extension recognizes. You may have to turn on badges for good brands in the settings to do this. 

A screenshot showing the Knockoff report feature.

Knockoff lets you report brands that are good or bad to help make the extension more accurate over time. All reports are handled by hand. 

Joe Hindy/CNET

There are some minor flaws with this approach. An example is the tool brand Spec Ops, which is a real brand, but Knockoff lists it as unrecognized and only gives me the option to “report as junk.” According to the GitHub page, all reports are logged and handled manually, but it doesn’t specify whether reports are logged based on which version of the report button users click. 

Knockoff is a good start for filtering junk

Overall, Knockoff is a useful extension in a digital marketplace dominated by AI-generated assets and unverified third-party products. 

When you’re shopping, the biggest benefit is avoiding low-quality off-brands. Even if you’re not actively shopping for anything, it’s fun (and terrifying) to see how many grayed-out product listings you can find in any given product category. We recommend turning on badges for known brands, but otherwise, the stock settings performed the best.

At the same time, Knockoff shows you brands likely to be fake on Amazon, but it doesn’t tell you which products are actually good or bad. Fake brands often come with fake or bot-written reviews more often than legitimate brands. 

Still, it all depends on what you’re shopping for. If all you need is a pack of zip ties for light cable management or to attach a tomato plant to a garden trellis, the ones sold by dropshippers will work just fine and save you a couple of bucks. 

And while Knockoff certainly makes it easier to shop for quality items, the extension still needs some fine-tuning and human analysis. 

Amazon driver bringing package up the stairs to the home

Knockoff certainly makes it easier, but it’s still good to know how to spot these yourself so when your package arrives, you’re happier.

Amazon

Avoid fake brands without the extension

An eagle-eyed shopper can spot a knock-off brand from a mile away if they know where and how to look at product listings. 

The first step, according to Russell Holly, director of commerce content at CNET, is to look for the brand outside of Amazon.com. “If it seems like a string of random characters and that brand name isn’t selling elsewhere, there’s a good chance the seller is not the manufacturer,” said Holly. 

Holly also says to pay closer attention to negative reviews, since brands very often only fake positive reviews. Negative reviews can be a better indicator of quality problems that may help explain why a product is cheaper than others in the same category. 

Similarly, you can also look for a brand’s product support. If the only way to report a problem is directly to Amazon, Holly says you’re most likely dealing with a dropshipper that doesn’t offer product support if something breaks. 

Another way to spot a fake brand is to find the same product sold under multiple brands. An example is a Broserengy alarm clock, Bluetooth speaker, phone charger combo. It is nearly identical to this product from Fansbe, including the RGB lights at the bottom, the placement (and labeling) of the buttons and the auxiliary USB port around the back for charging an accessory. These are two subtly different versions of the same product.





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25 AI employees who talk to each other and run my company without me.

Most CEOs don’t have time to play with AI.

Maybe they use ChatGPT to write an email or as a sparring partner, but that’s about it.

And I get it. Between back-to-back meetings, managing people, and putting out fires, when are you supposed to sit down and experiment?

But a few months ago, I started playing with agents, and it’s changed the way I think about scaling a company.

Baby Steps

It started with a single agent I built in Claude Cowork. It was a super-powered EA, which read my emails, checked my calendar, and gave me a morning brief. It helped me manage my to-do list, clarify my priorities, and set reminders.

It was really helpful. But what I really wanted was a full support team.

I wanted multiple agents, talking to each other, running on their own schedules, and working without me needing to be involved.

So I started building my own AI organisation. Finance, marketing, sales, strategy and relationship management… even Agent Resources (the HR equivalent).

Department by department, role by role, the organisation started to grow.

Burning the Ships

As more and more work was being taken on by agents, it became clear I didn’t need as large a support team.

So I took the decision to ramp down my human org, and invest in creating more agents.

Like Cortés, I burned the ships so there was no chance of retreat, and this forced me to figure out how to make an AI organisation work.

What used to be run by a Chief of Staff, a Head of Ops, and a Founder Associate is now run by my AI organisation and an EA.

I currently have 25 AI employees which cost about $2,500 a year to run. They replace over $250,000 a year in salaries, along with several SaaS tools I no longer use.

My AI employees manage accounts receivable and financial projects. They analyse my social media and create new pieces of content for my review. They proactively draft emails to help me build important relationships. 

I estimate I’ve got a 100X return on investment on my Claude Max plan.

How to Build an AI Support Team

Within a year or two, every leader will have their own AI organisation, each designed to fit the way they think and work.

When I show CEOs what I’ve built, their reaction is always the same: “I want this.”

So how do you go about building your AI support team?

Here are the three stages, although in practice they overlap a lot.

Stage 1: Connect Your Data

Before your agents can do anything useful, they need your knowledge.

You’ll need to connect your emails, meeting transcripts, data from your existing systems.

This stage is brutal, especially if you need to give the system historical data.

I spent entire nights feeding in data one chunk at a time, taking care not to overload the models with too much context.

Stage 2: Build the Workflows aka. Employees

Each AI employee is a workflow: a prompt that outlines a set of instructions, data it can access, and the output it creates.

Creating workflows is when things start to feel exciting.

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It’s quite addictive.

Stage 3: Get Your Employees to Work Together

It turns out many of the challenges of building an AI organisation are the same as a human one.

For example, my Chief of Staff acts as a messenger between me and my other AI employees. It reads all their reports, keeps track of what’s happening across the organisation.

But a few weeks in, the volume of reports generated by AI employees grew out of control.

One day, my AI Chief of Staff said to me: “Dave, there’s a lot for me to read. Do you really need me to read every single report?”

In other words, it was overwhelmed.

We want our chiefs of staff (human or AI) to be our interface with the world, but we often forget how much context this requires.

This led us to redesign our reporting systems, and create some Python scripts to make the work more efficient.

Be Careful With Subagents

Another familiar problem came from how AI agents spawn subagents to do things in parallel.

One evening, I’d kicked off a CRM project. About fifteen minutes in, I checked the progress and realised I hadn’t been clear enough.

I stopped the process and asked the agent to ‘undo’ what it had done.

A minute later, I looked at my data folders, and half of them were missing. As in deleted.

“Where are my files?” I asked, as beads of sweat started to form on my brow.

“This is my fault. The subagents overwrote the data files. I’m sorry.”

You’re sorry?

It turns out your agents will “subcontract” out their work to subagents… except these subagents don’t have the full context and often make mistakes.

Also, they aren’t the tidiest of agents either, often leaving random summary files littered around your filing system.

Luckily, my files were in Dropbox so I was able to recover the 571 files it deleted.

The Agents Are Coming

Now, someone skilled at building agent systems can do the work of dozens, maybe even hundreds of people.

I’m about a month away from having an AI organisation that can run my business with only minor involvement from me.

However, this poses a real challenge for CEOs.

In The Innovator’s Dilemma, Clay Christensen shows that incumbents get disrupted not because they make bad decisions, but because they make good ones.

They keep investing in what’s working today and rationally ignore the scrappy new thing that isn’t good enough yet.

Until it is.

For many CEOs, right now keeping their people is a good decision. AI agents aren’t reliable enough to replace a great team.

But within just a few years, smaller teams who leverage agents will outperform larger teams who don’t.

So if you haven’t started building with agents yet, consider this your permission to start.

Related Reading: 

 

Originally published on April 1st, 2026

 





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