The Kottage project (I don't have a large marketing budget for making up names, bear with me) is and attempt for creative application of NFTs other than pure digital art. The application allows for tokenizing short-time rental time slots, dividing longer slots into shorter ones and merging them back if there is a sequence of consecutive slots.
This approach allows for creating a secondary market of timeslots (e.g., on OpenSea) and hopefully create more liquid and frictionless market for short time rentals. Real estate owners can sell timeslots in bulk (e.g. for an entire year), participants of the market can break them down into smaller chunks and sell them to different customers depending on the properties of the slot (e.g., high season, low season).
Tech stack:
[ Ethereum ] [ solidity ] [ OpenZeppelin ] [ hardhat ] [ JavaScript ]
Project link:
AnxioCrew is a fun project utilising NFTs. Don't get me wrong, I think NFTs are very interesting instruments and are largely misunderstood. They can definitely be useful (see my KottageToken project - attempt to tokenize short-time rentals).
I created this particular NFT collection because I was running out of ideas for birthday presents for my friends. So I thought, why not a cute, mentally unstable AnxioBuddy? You could never not love them!
Tech stack:
[ Solidity ] [ JavaScript ] [ OpenZeppelin ] [ Hardhat] [ OpenSea ]
Project link:
The original idea for hunter-seeker (HS) framework was based on research into fuzzing, instrumentation, automation, binning crashes and taint analysis that was lead I belive by Charlie Miller and/ir Ben Nagy (can't remember exactly now, apologies). It involved qemu variant hacked for propagating taint (temu/bitblaze (?)).
Let's start from the end :). The goal of the bug hunting process is a weaponized exploit ready for submission in a vuln aquisition program. In order to produce a weaponized exploit, exploitable crash must be available and a toolset for engineering the shellcode and a payload. I belive the best tool for this should rely on taint analysis. In order to produce an exploitable crash, a number of ordinary crashes should be generated and binned In order to produce a number of crashes, analysis sunject needs to be instrumented for exception detection and repeated processing of a mutated sample should be performed In roder to produce mutated samples, core samples need to be chosen based on the code coverage (code of new features and code working on input data (processing files, serving protocol requests) has high potential)
Tech stack:
[ C/C++ ] [ Python ] [ Qemu ] [ Assembly ]
Project link: