Rug Pulls: How to Spot One Before You Buy

Few crypto scam categories are as damaging or as well-documented as rug pulls, and Felix Bick’s How Not to Get Scammed by AI Trading Apps gives this pattern a thorough, practical treatment in Chapter 30.

Bick defines a rug pull as occurring when developers of a cryptocurrency project abandon it and abscond with investor funds, typically after building initial hype and liquidity. The book usefully distinguishes between two forms: a “hard” rug pull, where developers simply withdraw all liquidity and disappear, and a “soft” rug pull, where developers gradually sell their large token holdings while remaining nominally active, quietly draining value from remaining holders.

The chapter explains why this pattern is so common specifically in decentralized finance and new token launches: anonymous teams can create a project, attract deposits or liquidity, and disappear within days or even hours, leaving no legal recourse for victims in most cases given the anonymity involved.

What makes this chapter genuinely valuable is its concrete due diligence checklist. Bick recommends checking whether liquidity is “locked” — time-committed in a way that prevents developers from withdrawing it early — through an independent, verifiable locking service; reviewing whether the development team is publicly identified with a traceable history; and checking whether the project’s smart contract has been audited by a reputable, named security firm.

Each of these checks is something an ordinary investor can actually perform before buying a new token, rather than relying purely on marketing claims or community enthusiasm. This is characteristic of the book’s overall approach — Bick consistently converts abstract warnings into specific, checkable actions.

For anyone tempted by a new, exciting token launch, this chapter of How Not to Get Scammed by AI Trading Apps offers Felix Bick’s essential pre-purchase due diligence routine, potentially saving readers from one of crypto’s most common and devastating scam patterns.