Fakespot is dead: How to spot fake reviews without it

If you saw the notification in your browser, you already know that Fakespot dies on July 1st, 2025. For those unfamiliar, Fakespot was a browser extension that analyzed Amazon reviews and gave products a letter grade (A-F) based on review authenticity. Incredibly useful for avoiding misleading product listings. Now, millions of users are losing that protection.

I spent several days testing every Fakespot alternative I could find. One gave perfect scores to products drowning in fake reviews. Another hasn't worked properly since 2021. A third had fake reviews for itself on its own website.

Here's exactly what works, what doesn't, and how to protect yourself until better tools arrive.

Why Mozilla killed Fakespot

Mozilla announced the shutdown of Fakespot in May 2025:

We acquired Fakespot in 2023 to help people navigate unreliable product reviews using AI and privacy-first tech. While the idea resonated, it didn't fit a model we could sustain.

In other words, it wasn't making money.

What they didn't mention is that late last year, Amazon changed the way reviews can be accessed. Now you need to log in to see more than a handful of reviews. That single change probably completely broke Fakespot's ability to work the way it always had.

Meanwhile, fake reviews have gotten smarter. AI can now generate reviews that pass basic detection. Without Fakespot, we're back to guessing.

The disappointing state of "alternatives"

ReviewMeta - The abandoned pioneer

ReviewMeta has been around since 2015, but founder Tommy Noonan announced in 2021 that he was burnt out after 12 years. He was leaving to become an EMT and looking for someone to take over.

Today, the site exists in limbo. Sometimes it loads, sometimes it doesn't. The Chrome extension (30k users, 3.6 stars) often just bounces you to the homepage instead of analyzing products.

Verdict: ❌ Unreliable. More broken than working.

NullFake - Well-intentioned but ineffective

Shift8 Web launched NullFake a couple weeks ago as an open-source option. I applaud the transparency - all the code is right there on GitHub.

But here's the thing: I tested products I know have fake reviews. Products where all the reviews were clearly written by ChatGPT, with reviewers leaving dozens of 5-star reviews for various products in short spans of time. Products where every reviewer uses the exact same broken English phrases. NullFake gave most of them perfect scores.

Verdict: ⚠️ Not ready. The developer is improving it, but currently not a reliable replacement for Fakespot.

RateBud - Red flags everywhere

This one hurts because, while not as good as Fakespot, a site called "RateBud" does actually catch some fakes. But look closer and you'll see a lot of sketchy behavior from the developer:

• The site embeds affiliate links without telling you.
• They post fake Reddit recommendations for their own projects pretending to be a happy user.
• The Chrome extension has 10 users and the project has no online presence, yet the site claims 100,000+ users and highlights glowing testimonials.

Conclusion: 🚨 Avoid. A fake review detector using fake reviews in their own marketing is peak irony.

What actually works

After all the disappointment in existing tools, there are only two methods that I can consider for protecting myself from fake reviews.

Method 1: AI analysis

"Just use ChatGPT" is a bit of a cop-out, but it works better than every dedicated tool I tested. Here's what I've been doing:

1. Copy the Amazon URL
2. Open ChatGPT (or other AI assistant)
3. Paste this prompt:

Analyze this Amazon product for fake reviews: [URL]

Look for:
- Bursts of positive reviews in a short period of time
- AI writing style
- Similar phrases across different reviewers
- Generic descriptions that could fit any product
- Reviews about a different product
- Reviewer accounts that only review certain brands

Tell me:
1. Trust score from 1-10
2. How confident you are in the score
3. Biggest red flags

It only takes a few seconds, costs nothing, and seems to work decently. I suspect ChatGPT will run into the same technical limitations as Fakespot, but whatever it's doing, it seems to be working for now.

Method 2: Manual detective work

Until better tools emerge, your own analysis remains the gold standard:

1. Sort by "Most Recent" - Fake review campaigns dump reviews in batches. If you see ten 5-star reviews in a week after months of silence, run.
2. Focus on the extremes - Review farms don't do nuance. They write either glowing 5-star reviews or angry 1-star attacks on competitors. You rarely see fake reviews with 3-star ratings.
3. Watch for copy-paste phrases - I recently almost bought an action camera on Amazon before I noticed all the recent reviews contained the exact phrase "crystal clear video quality." Identical phrasing = coordinated campaign.
4. Look for brand name-drops - "This RandoTrash360 vacuum cleaner is life-changing!" No one talks like that except Amazon sellers using marketing speak to rank higher in search results.
5. Check reviewer profiles - If a review looks suspicious, click on the reviewer's profile. You may see patterns like bursts of positive reviews, or a reviewer who only reviews certain brands.
6. Recognize AI writing - Look for things like overuse of emoji, excessive em dashes (—), or that notorious "uncanny valley" writing style.

Building something better

After watching Mozilla kill a tool millions depended on, I realized the issue isn't just technology - it's ownership. Corporate tools die when budgets shift. Hobbyist side projects die when developers burn out.

But the fake review problem isn't going away. It's only going to get worse. That's why I've started building a browser extension for detecting fake reviews called TrueStar.

How TrueStar will succeed where Fakespot failed:

Fakespot's fatal flaws:

• Heavy corporate overhead at Mozilla
• No viable revenue model
• 2016-era technology Amazon eventually blocked
• Zero transparency about how it worked

TrueStar's approach:

• Modern AI - Latest models that are more accurate than Fakespot's dated algorithms
• Realistic business model - Free tier for casual users, affordable premium for regular shoppers
• Built to last - Not dependent on corporate budgets or the whims of a single individual contributor
• Open source - All code will be publicly available so users can verify how it works, contribute, or build their own tools

Coming features:

• Chrome/Firefox/Safari extension
• Amazon support at launch, expanding based on demand
• Developer API access
• Community-driven improvements

Let's fix this mess together.

-Bryson