AI x Crypto Lesson 6: Risk Management and Scams

Before we dive in, take this Crypto and Blockchain Cheat sheet - a quick, printable snapshot you can keep open while you read!

Lesson 6: Scams, Rug Pulls, and “How I Don’t Get Wrecked”

If I’m being honest, the biggest reason beginners quit crypto is not charts. It is the feeling of getting tricked.

Crypto is powerful, but it’s also a playground for scammers because:

• transactions are fast

• transfers are hard to reverse

• and beginners are usually moving too quickly

So in this lesson, I’m going to show you how I think about scam risk, what patterns I look for, and how I use AI tools as my second brain to slow me down and keep me safe.

I’m not trying to make you paranoid. I’m trying to make you prepared.

1) The first mental shift: coins are usually safer than random tokens

This is the simplest “risk filter” I use:

• Coins (BTC $BTC ( ▲ 0.4% ) , ETH $ETH ( ▲ 0.53% ) , BNB $BNB ( ▲ 0.06% ) ) are the “base layer” assets of their own networks.

  • Example: ETH is the coin you use to pay gas on Ethereum.

  • Example: BNB is the coin you use to pay fees on BNB Chain.

• Tokens are assets built on top of those chains (ERC-20 / BEP-20), and anyone can create them.

That second part matters.

Example:
It’s hard to “fake Bitcoin” on the Bitcoin network. But it’s very easy for someone to create a token called something like:

• “BitcoinX”

• “BTC 2.0”

• “Wrapped BTC Rewards”
  …and make it look legit to a beginner.

One thing I always keep in mind:

“Treat random new tokens like street food in a new city. It might be amazing… or it might send you to the hospital.”

2) The scam categories I see the most

2.1 Rug pulls (DEX-focused)

A rug pull is when a project’s insiders drain value and leave investors holding a worthless bag. Binance Academy defines it as developers abandoning a project and running off with investor funds, often involving liquidity pools and smart contract tricks.

Simple example:
A team launches a token on PancakeSwap with a TOKEN/BNB pool. People buy. The price pumps. Then the team removes liquidity (or dumps huge supply) and the chart collapses.

This connects directly to what your course teaches: liquidity is non-negotiable because without it, the token can’t trade and if liquidity gets pulled, trust dies instantly.

2.2 Honeypots (buyable, not sellable)

This one is evil because it feels normal at first.

Example:
You buy a new token on a DEX and it works. But when you try to sell… the transaction fails every time. That means the contract has rules that block sells (or only allow sells for whitelisted wallets).

That’s why I never trust “it’s pumping” as proof of legitimacy. I want proof the token is tradable both ways.

2.3 Phishing and fake support

This is one of the most common ways beginners lose everything.

Example:
You ask for help in a Telegram group. Someone DMs you pretending to be “MetaMask support.” They ask for your seed phrase or send a “wallet sync” link. If you do it, you’re done.

The FTC’s guidance is blunt for a reason: real businesses and government agencies won’t message you out of nowhere demanding payment in crypto, and unexpected links/messages are classic scam behavior.

2.4 Address poisoning

This scam is growing because it targets human behavior, not the blockchain itself.

What it is: Attackers send tiny “dust” transactions so their lookalike address shows up in your recent transaction history, hoping you copy the wrong one later. Chainalysis breaks down how address poisoning works, and Binance Academy also has a dedicated explainer on it.

Example:
You’ve sent USDT to your exchange address before. A scammer sends you a tiny transaction from an address that looks similar. Later, you’re in a rush, you copy the “recent” address… and you send your real funds to the scammer.

2.5 “Investment manager” / pig-butchering style scams (slow burn)

This is where scammers build trust over days/weeks, then push you into a fake platform or fake “guaranteed strategy.”

This isn’t rare and it is huge. Reuters reported Chainalysis findings that scam revenue likely hit record levels in 2024, with “pig butchering” and GenAI making scams more scalable.

Example:
Someone you “met” online shows screenshots of profits and says “I can help you.” You end up sending money to a wallet or website that you can’t withdraw from. Classic!

3) The on-chain safety signals I actually trust

This is where your course content becomes extremely practical.

3.1 Liquidity lock = trust

Liquidity pools are the market, and without liquidity the token cannot be traded and gets labeled untradable or scammy.

And for rug-pull defense, it highlights locking or burning LP tokens as the main investor trust signal.

So when I look at a new token, I ask:

• Is there real liquidity?

• Is it locked?

• For how long?

Even as a founder, this matters. Locking liquidity isn’t just “nice”, it prevents you from getting wrecked by rug-pull accusations later.

3.2 KYC / audit badges

PinkSale badges like KYC and Audit exist to help investors judge seriousness and reduce rug-pull mechanisms, and audits help identify vulnerabilities.

I personally treat this as:

• Badge = signal, not guarantee

• No badge = higher caution, not automatic scam

It’s still a useful filter, especially for beginners.

4) My “slow down” checklist

When I’m about to interact with a token, I run this mental checklist:

• Am I looking at the correct chain?

  • Example: USDT $USDT ( ▼ 0.0% ) exists on Ethereum, BNB Chain, Tron, etc. Same name, different networks.

• Am I using the correct contract address?

  • Example: fake “USDC $USDC ( ▲ 0.5% ) ” tokens exist everywhere.

• Is liquidity real and locked?

• Does selling actually work (not just buying)?

• Do the socials look like humans, or bots shouting “to the moon”?

• Is the project making insane promises?

  • “Guaranteed profit”, “100x daily”, “risk-free staking”. I treat these as red flags instantly.

This is not about becoming a detective. It’s about avoiding obvious traps.

5) The exact AI tools I use in this lesson (and how)

I’m going to be very specific here, because AI will give useless advice unless you know how to use it properly.

Tool 1: Claude - “My logic auditor”

What I use it for: Long documents and consistency checks.

How I use it: I paste tokenomics + roadmap and ask:

“Act like a skeptical investor. List red flags, missing details, and any way this could rug or trap users.”

Claude is good at catching things like:

• “Community-first” but huge team allocation unlocked

• Vague promises with no mechanism

As you can see, the answer from Claude is as skeptical as it was told to be. Instead of using emotional language, Claude pointed out why the structure of this project is dangerous which is extremely helpful in lieu of giving a "trust me bro” vibe. This helps beginners learn how to question a project logically.

Tool 2: Perplexity - “My reality checker”

What I use it for: Quickly verifying claims with sources.

How I use it: I ask:

“Is this project reputable? Any known incidents? Summarize what credible sources say.”

It’s especially useful when a token claims partnerships, audits, or “featured on major sites.” Furthermore, it teaches user on how to evaluate credibility, not chase hype.

From the prompt I used:

• It uses evidence-based skepticism, clearly separating no known incidents from proven trustworthiness.

• It shows why self-claimed audits, partnerships, and celebrity backing are not real verification.

• It highlights that lack of coverage from credible outlets (CoinDesk, Decrypt, etc.) is itself a warning sign.

• It presents risk as a spectrum, not a binary scam/not-scam judgment.

Tool 3: CustomGPT - “My scam filter” train one for yourself or check out the one I made down below

This is my favorite for beginners because it turns safety into a system, not a vibe.

What I use it for: Running the same scam checks every time:

• Contract/source verification steps

• Common scam patterns (rug pull signals, honeypot signals, phishing language)

• What I should verify next (instead of “should I buy?”)

How I set it up (simple):

• I give it my checklist rules (never share seed phrase, verify contract address, check liquidity lock, etc.)

• I instruct it: “Never encourage buying. Only evaluate risk and verification steps.”

Prompt example:

“Here’s the project description + tokenomics + links. Act as my scam filter. List red flags and the exact verification steps I should do before interacting.”

The answer from this CustomGPT is reliable because it teaches how beginners actually get scammed, how they should think instead, and will match with their own checklist.

• It teaches process, not opinions → you learn how to verify, not what to believe

• It breaks hype vs reality → shows that good storytelling ≠ safe investment

• It introduces real-world crypto risk thinking → taxes, liquidity locks, wallet control, governance

• It’s actionable → clear, step-by-step checks students can reuse on any project

• It reinforces the core lesson → “Trust code, locks, and on-chain proof - not words”

Key takeaway 🔑 

If you have to take one idea from this lesson, it’s this:

In crypto, you don’t need to be the smartest person in the room, you just need a process that stops you from acting fast when emotions are high.

Coins like BTC/ETH/BNB are usually safer basics. Tokens are where the wild opportunities are… and where most traps live. When you combine a simple verification habit (liquidity lock, contract checks, realistic claims) with AI tools that slow you down and summarize risk, you give yourself a huge advantage - especially as a beginner.

If you enjoy this lesson, please let me know and check out these amazing news, content, experiences and tutorials related to AI and Crypto from our team down below🔥✌️👇️:

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