So you've finished your NFT collection and are ready to sell it. Except you can't figure out how to mint them! Not sure about smart contracts or want to avoid rising gas prices. You've tried and failed with apps like Mini mouse macro, and you're not familiar with Selenium/Python. Worry no more, NodeJS and Puppeteer have arrived!

Learn how to automatically post and sell all 1000 of my AI-generated word NFTs (Nakahana) on OpenSea for FREE!

My NFT project — Nakahana |

NOTE: Only NFTs on the Polygon blockchain can be sold for free; Ethereum requires an initiation charge. NFTs can still be bought with (wrapped) ETH.

If you want to go right into the code, here's the GitHub link: https://github.com/Yusu-f/nftuploader

Let's start with the knowledge and tools you'll need.

What you should know

You must be able to write and run simple NodeJS programs. You must also know how to utilize a Metamask wallet.

Tools needed

• NodeJS. You'll need NodeJs to run the script and NPM to install the dependencies.
• Puppeteer – Use Puppeteer to automate your browser and go to sleep while your computer works.
• Metamask – Create a crypto wallet and sign transactions using Metamask (free). You may learn how to utilize Metamask here.
• Chrome – Puppeteer supports Chrome.

Let's get started now!

Starting Out

Clone Github Repo to your local machine. Make sure that NodeJS, Chrome, and Metamask are all installed and working. Navigate to the project folder and execute npm install. This installs all requirements.

Replace the “extension path” variable with the Metamask chrome extension path. Read this tutorial to find the path.

Substitute an array containing your NFT names and metadata for the “arr” variable and the “collection_name” variable with your collection’s name.

Run the script.

After that, run node nftuploader.js.

Open a new chrome instance (not chromium) and Metamask in it. Import your Opensea wallet using your Secret Recovery Phrase or create a new one and link it. The script will be unable to continue after this but don’t worry, it’s all part of the plan.

Next steps

Open your terminal again and copy the route that starts with “ws”, e.g. “ws:/localhost:53634/devtools/browser/c07cb303-c84d-430d-af06-dd599cf2a94f”. Replace the path in the connect function of the nftuploader.js script.

Rerun node nftuploader.js. A second tab should open in THE SAME chrome instance, navigating to your Opensea collection. Your NFTs should now start uploading one after the other! If any errors occur, the NFTs and errors are logged in an errors.log file.

Error Handling

The errors.log file should show the name of the NFTs and the error type. The script has been changed to allow you to simply check if an NFT has already been posted. Simply set the “searchBeforeUpload” setting to true.

We're done!

If you liked it, you can buy one of my NFTs! If you have any concerns or would need a feature added, please let me know.

Thank you to everyone who has read and liked. I never expected it to be so popular.

You can make a proof for the statement "I know a secret number such that if you take the word ‘cow', add the number to the end, and SHA256 hash it 100 million times, the output starts with 0x57d00485aa". The verifier can verify the proof far more quickly than it would take for them to run 100 million hashes themselves, and the proof would also not reveal what the secret number is.

In the context of blockchains, this has 2 very powerful applications: Perhaps the most powerful cryptographic technology to come out of the last decade is general-purpose succinct zero knowledge proofs, usually called zk-SNARKs ("zero knowledge succinct arguments of knowledge"). A zk-SNARK allows you to generate a proof that some computation has some particular output, in such a way that the proof can be verified extremely quickly even if the underlying computation takes a very long time to run. The "ZK" part adds an additional feature: the proof can keep some of the inputs to the computation hidden.

You can make a proof for the statement "I know a secret number such that if you take the word ‘cow', add the number to the end, and SHA256 hash it 100 million times, the output starts with 0x57d00485aa". The verifier can verify the proof far more quickly than it would take for them to run 100 million hashes themselves, and the proof would also not reveal what the secret number is.

In the context of blockchains, this has two very powerful applications:

1. Scalability: if a block takes a long time to verify, one person can verify it and generate a proof, and everyone else can just quickly verify the proof instead
2. Privacy: you can prove that you have the right to transfer some asset (you received it, and you didn't already transfer it) without revealing the link to which asset you received. This ensures security without unduly leaking information about who is transacting with whom to the public.

But zk-SNARKs are quite complex; indeed, as recently as in 2014-17 they were still frequently called "moon math". The good news is that since then, the protocols have become simpler and our understanding of them has become much better. This post will try to explain how ZK-SNARKs work, in a way that should be understandable to someone with a medium level of understanding of mathematics.

Why ZK-SNARKs "should" be hard

Let us take the example that we started with: we have a number (we can encode "cow" followed by the secret input as an integer), we take the SHA256 hash of that number, then we do that again another 99,999,999 times, we get the output, and we check what its starting digits are. This is a huge computation.

A "succinct" proof is one where both the size of the proof and the time required to verify it grow much more slowly than the computation to be verified. If we want a "succinct" proof, we cannot require the verifier to do some work per round of hashing (because then the verification time would be proportional to the computation). Instead, the verifier must somehow check the whole computation without peeking into each individual piece of the computation.

One natural technique is random sampling: how about we just have the verifier peek into the computation in 500 different places, check that those parts are correct, and if all 500 checks pass then assume that the rest of the computation must with high probability be fine, too?

Such a procedure could even be turned into a non-interactive proof using the Fiat-Shamir heuristic: the prover computes a Merkle root of the computation, uses the Merkle root to pseudorandomly choose 500 indices, and provides the 500 corresponding Merkle branches of the data. The key idea is that the prover does not know which branches they will need to reveal until they have already "committed to" the data. If a malicious prover tries to fudge the data after learning which indices are going to be checked, that would change the Merkle root, which would result in a new set of random indices, which would require fudging the data again... trapping the malicious prover in an endless cycle.

But unfortunately there is a fatal flaw in naively applying random sampling to spot-check a computation in this way: computation is inherently fragile. If a malicious prover flips one bit somewhere in the middle of a computation, they can make it give a completely different result, and a random sampling verifier would almost never find out.

It only takes one deliberately inserted error, that a random check would almost never catch, to make a computation give a completely incorrect result.

If tasked with the problem of coming up with a zk-SNARK protocol, many people would make their way to this point and then get stuck and give up. How can a verifier possibly check every single piece of the computation, without looking at each piece of the computation individually? There is a clever solution.

StableGains lost millions of dollars in customer funds in Anchor Protocol without telling its users. The Anchor Protocol offered depositors 19-20% APY before its parent ecosystem, Terra LUNA, lost tens of billions of dollars in market capitalization as LUNA fell below $0.01 and its stablecoin (UST) collapsed.

A Terra Research Forum member raised the alarm. StableGains changed its homepage and Terms and Conditions to reflect how it mitigates risk, a tacit admission that it should have done so from the start.

StableGains raised $600,000 in YCombinator's W22 batch. Moonfire, Broom Ventures, and Goodwater Capital invested $3 million more.

StableGains' 15% yield product attracted $42 million in deposits. StableGains kept most of its deposits in Anchor's UST pool earning 19-20% APY, kept one-quarter of the interest as a management fee, and then gave customers their promised 15% APY. It lost almost all customer funds when UST melted down. It changed withdrawal times, hurting customers.

• StableGains said de-pegging was unlikely. According to its website, 1 UST can be bought and sold for $1 of LUNA. LUNA became worthless, and Terra shut down its blockchain.
• It promised to diversify assets across several stablecoins to reduce the risk of one losing its $1 peg, but instead kept almost all of them in one basket.
• StableGains promised withdrawals in three business days, even if a stablecoin needed time to regain its peg. StableGains uses Coinbase for deposits and withdrawals, and customers receive the exact amount of USDC requested.

StableGains scrubs its website squeaky clean

StableGains later edited its website to say it only uses the "most trusted and tested stablecoins" and extended withdrawal times from three days to indefinite time "in extreme cases."

Previously, USDC, TerraUST (UST), and Dai were used (DAI). StableGains changed UST-related website content after the meltdown. It also removed most references to DAI.

Customers noticed a new clause in the Terms and Conditions denying StableGains liability for withdrawal losses. This new clause would have required customers to agree not to sue before withdrawing funds, avoiding a class-action lawsuit.

Customers must sign a waiver to receive a refund.

Erickson Kramer & Osborne law firm has asked StableGains to preserve all internal documents on customer accounts, marketing, and TerraUSD communications. The firm has not yet filed a lawsuit.

Thousands of StableGains customers lost an estimated $42 million.

Celsius Network customers also affected

CEL used Terra LUNA's Anchor Protocol. Celsius users lost money in the crypto market crash and UST meltdown. Many held CEL and LUNA as yielding deposits.

CEO Alex Mashinsky accused "unknown malefactors" of targeting Celsius Network without evidence. Celsius has not publicly investigated this claim as of this article's publication.

CEL fell before UST de-pegged. On June 2, 2021, it reached $8.01. May 19's close: $0.82.

When some Celsius Network users threatened to leave over token losses, Mashinsky replied, "Leave if you don't think I'm sincere and working harder than you, seven days a week."

Celsius Network withdrew $500 million from Anchor Protocol, but smaller holders had trouble.

OpenSea, a non-fungible token (NFT) marketplace, is fighting plagiarism. A new “two-pronged” approach will aim to root out and remove copies of authentic NFTs and changes to its blue tick verified badge system will seek to enhance customer confidence.

According to a blog post, the anti-plagiarism system will use algorithmic detection of “copymints” with human reviewers to keep it in check.

Last year, NFT collectors were duped into buying flipped images of the popular BAYC collection, according to The Verge. The largest NFT marketplace had to remove its delay pay minting service due to an influx of copymints.

80% of NFTs removed by the platform were minted using its lazy minting service, which kept the digital asset off-chain until the first purchase.

NFTs copied from popular collections are opportunistic money-grabs. Right-click, save, and mint the jacked JPEGs that are then flogged as an authentic NFT.

The anti-plagiarism system will scour OpenSea's collections for flipped and rotated images, as well as other undescribed permutations. The lack of detail here may be a deterrent to scammers, or it may reflect the new system's current rudimentary nature.

Thus, human detectors will be needed to verify images flagged by the detection system and help train it to work independently.

“Our long-term goal with this system is two-fold: first, to eliminate all existing copymints on OpenSea, and second, to help prevent new copymints from appearing,” it said.

“We've already started delisting identified copymint collections, and we'll continue to do so over the coming weeks.”

It works for Twitter, why not OpenSea

OpenSea is also changing account verification. Early adopters will be invited to apply for verification if their NFT stack is worth $100 or more. OpenSea plans to give the blue checkmark to people who are active on Twitter and Discord.

This is just the beginning. We are committed to a future where authentic creators can be verified, keeping scammers out.

Also, collections with a lot of hype and sales will get a blue checkmark. For example, a new NFT collection sold by the verified BAYC account will have a blue badge to verify its legitimacy.

New requests will be responded to within seven days, according to OpenSea.

These programs and products help protect creators and collectors while ensuring our community can confidently navigate the world of NFTs.

By elevating authentic content and removing plagiarism, these changes improve trust in the NFT ecosystem, according to OpenSea.

OpenSea is indeed catching up with the digital art economy. Last August, DevianArt upgraded its AI image recognition system to find stolen tokenized art on marketplaces like OpenSea.

It scans all uploaded art and compares it to “public blockchain events” like Ethereum NFTs to detect stolen art.