VYPR
researchPublished Nov 2, 2026· 1 source

Underground Market Thrives on Fake Reviews, AI-Powered Manipulation

Cybercrime forums are selling services to artificially inflate product ratings and remove negative feedback, with AI increasingly used to automate these deceptive campaigns.

Beneath the surface of legitimate online commerce, a thriving underground economy is dedicated to manipulating consumer perception through fake reviews. Cybercrime forums are increasingly advertising sophisticated "reputation management" services, offering everything from generating glowing five-star reviews to scrubbing negative feedback from platforms like Google, Trustpilot, and mobile app stores. This illicit trade directly undermines consumer trust and the integrity of online marketplaces.

Sellers in this space, often operating under pseudonyms, present their services as easily orderable commodities. For instance, one seller highlighted in recent research advertised the ability to flood products with positive ratings or remove detrimental comments, simply asking prospective buyers to specify the target platform. This commodification of reputation suggests a well-oiled operation designed to cater to businesses seeking to artificially boost their image or obscure legitimate customer complaints.

A significant trend emerging in this market is the adoption of artificial intelligence (AI) to automate and scale these fake review campaigns. Cybercriminals are leveraging AI to generate realistic, human-sounding feedback in large volumes, bypassing traditional detection methods that might flag mass-produced, identical reviews. This technological advancement allows for more convincing and harder-to-detect manipulation at an unprecedented scale.

The mechanics behind these operations are designed to evade platform scrutiny. Some sellers emphasize that reviews are posted manually by real individuals, offering guarantees against "non-drop" – meaning the feedback won't be flagged and removed by the platform. While this involves human actors, it doesn't imply genuine customer experience. The confidence in bypassing platform checks often stems from "private methods" that are closely guarded secrets, with some operators claiming to have posted thousands of fake reviews successfully.

Beyond inflating positive ratings, a lucrative segment of this market focuses on removing negative reviews. Businesses desperate to protect their image can pay substantial sums to have critical feedback taken down. While legitimate businesses can challenge fabricated reviews, these services raise concerns about the potential for genuine customer complaints to be targeted and removed, leaving consumers with an incomplete and misleading picture of a product or service.

The cost of these services varies significantly. While a single review removal might range from $100 to $200, prices escalate dramatically for more prominent platforms, with one seller advertising Airbnb review removal for around $1,100 per review. This high cost reflects the perceived value of controlling online reputation and the difficulty in removing authentic, albeit negative, feedback.

The integration of AI is also being discussed in the context of Google's E-E-A-T (Experience, Expertise, Authoritativeness, and Trustworthiness) guidelines. Discussions on underground forums reveal attempts to use AI to mimic these qualities in product reviews, aiming to artificially boost website rankings. Some users claim success in getting AI-generated reviews indexed by Google, indicating a potential new frontier in search engine manipulation.

To further mask their activities, scammers utilize "residential and mobile proxies." These tools route traffic through real internet connections, making it difficult for platforms to distinguish fake review activity from that of genuine consumers. By disguising the origin of their traffic, these operators aim to appear as everyday users, thereby increasing the longevity and believability of their fabricated reviews and reputation management schemes.

Synthesized by Vypr AI