In the era of effortless online shopping, we've all been there: excitedly unboxing a package only to find something less than perfect. Maybe the item arrived scuffed, spoiled, or just not as advertised. Traditionally, snapping a quick photo of the issue and sending it to the seller has been enough to secure a hassle-free refund. E-commerce giants have built their customer-friendly policies around this simple system—visual proof from buyers to verify claims. But as generative artificial intelligence tools become more sophisticated and accessible, this foundational trust mechanism is starting to crack under pressure.
Fraudsters are increasingly turning to AI to create convincingly doctored or entirely fabricated images (and even videos) of damaged goods. These fake visuals allow them to claim refunds while keeping perfectly good products, exploiting lenient return policies designed for genuine customers. This isn't just a niche problem; it's a growing wave that's hitting online marketplaces hard, particularly in high-volume shopping regions, and spreading globally.
How the Scam Works: From Everyday Tools to Sophisticated Deception
Generative AI platforms—think tools like Midjourney, DALL-E, or similar apps available on smartphones—make it incredibly easy for anyone to alter photos. A buyer receives an intact item, takes a real picture, then uses AI prompts to add mold to fruit, cracks to ceramics, or tears to fabric. The result? An image that looks authentically damaged, complete with realistic shadows, textures, and lighting.
In some cases, scammers go further by generating entire scenes from scratch. Videos can be faked too, though they're trickier and often reveal inconsistencies upon closer inspection. The beauty (or danger) for fraudsters is that these tools require no advanced skills—just a few descriptive words—and the output can fool even attentive human reviewers, especially when support teams are overwhelmed with high volumes of claims.
Certain product categories are especially vulnerable:
- Perishables like fresh seafood or produce: Sellers rarely require returns due to spoilage risks, so a photo of "dead" arrivals is often enough for an instant refund.
- Low-value items such as cosmetics or household goods: The cost of processing returns outweighs the item price, leading to "refund without return" policies.
- Fragile objects like glassware or mugs: Fake cracks or breaks are simple to simulate digitally.
These kinds of manipulated visuals are becoming commonplace in refund disputes, turning what should be straightforward customer service into a battlefield of authenticity.
Real-World Examples: The Telltale Signs of AI Fakery
One particularly notable incident involved a seller of live crabs on a popular short-video platform in China. A customer claimed most of the crabs arrived lifeless, submitting photos and videos as evidence. Some crabs appeared to have "escaped" the box, while others were shown being prodded lifelessly.
The seller, with decades of experience in aquaculture, spotted red flags immediately. Dead crabs don't typically hold unnatural poses, like legs rigidly upward. More damning were inconsistencies across submissions: varying counts of male and female crabs between clips, and even one with an impossible extra leg. Authorities investigated, confirmed the media was AI-fabricated, and the buyer faced consequences—highlighting this as an early high-profile case drawing official attention.
Similar complaints have flooded seller forums: images of shredded bedding with nonsensical shipping labels (text rendered as gibberish by AI's occasional struggles with language), or ceramic items "torn" in ways that defy physics—like layered peels impossible for hard materials.
I finally found a solution for keeping my bedsheets popping off of ...
Other reports include rusty electric toothbrushes (despite stainless components), moldy fruits that started pristine, or undercooked meals in food delivery apps altered to look raw.
These aren't isolated pranks. During major sales events, like massive shopping festivals, refund requests spike dramatically, with many backed by suspiciously perfect "damage" photos.
The Global Scale: Not Just One Region's Problem
While this trend gained early traction in fast-paced e-commerce markets with generous no-return refund options, it's rapidly going worldwide. Fraud prevention firms report surges in AI-altered images for claims, with increases of over 15% in recent periods. Organized groups amplify the issue, flooding retailers with coordinated bogus requests—sometimes worth hundreds of thousands in a short burst—using techniques like IP rotation to evade detection.
The accessibility of AI lowers the entry barrier dramatically. What once required Photoshop expertise now takes seconds on a phone app. And crucially, the fakes don't need to be flawless; busy review teams often approve based on quick glances.
Fighting Back: AI vs. AI and Evolving Defenses
Sellers aren't sitting idle. Some are deploying AI detection tools to scan submitted photos for signs of generation—unnatural pixel patterns, inconsistent lighting, or anatomical errors (like extra limbs). Chatbots analyze claims in real-time, flagging suspects.
Platforms are responding too: scrapping easy "refund-only" for certain categories, introducing buyer credit scores based on history, or requiring video proof (harder for current AI to fake consistently).
But detection isn't perfect—AI generators improve daily, and false positives could alienate honest shoppers. Watermarking mandates for AI content exist in some places, but they're easily stripped.
The Broader Implications: Trust as the Casualty
This scam wave flips an earlier issue where sellers used AI-enhanced product images, making real arrivals disappointing. Now, buyers weaponize the same tech, eroding mutual trust.
E-commerce thrives on assuming most participants are honest. When that's undermined, everyone loses:
- Sellers face financial hits and frustration.
- Platforms risk reputational damage and higher fraud costs.
- Genuine customers may see stricter policies—mandatory returns, longer reviews, or fewer refunds—worsening the experience.
In extreme cases, retailers might tighten rules across the board, punishing the majority for the actions of a few.
Long-term, solutions could include advanced verification (e.g., blockchain-tracked images), mandatory multi-angle videos, or integrated AI detectors in apps. Regulations pushing transparent AI labeling and accountability for misuse are emerging.
Looking Ahead: Balancing Convenience and Security
As we head deeper into 2026, AI's double-edged sword in shopping is clear. It powers personalized recommendations and seamless experiences but also enables deception at scale. The key is adaptation: platforms investing in smarter fraud tech, users staying vigilant (e.g., sellers documenting shipments meticulously), and regulators catching up.
Ultimately, rebuilding trust means evolving beyond "a picture tells a thousand words." In the age of generative AI, we need systems where proof is harder to forge. Until then, that next refund request might come with a side of skepticism.
Online shopping's convenience is worth preserving—but only if we can keep it honest.
