fix core.md

Signed-off-by: degrigis <[email protected]>

docs/docs/core.md

@@ -2,7 +2,7 @@
 # 🔥 Core Concepts
 
 ## Overview 
-greed relies on analyses provided by [Gigahorse](https://github.com/nevillegrech/gigahorse-toolchain) – a fantastic analysis framework for EVM-based smart contracts developed by [Dedaub](https://dedaub.com/). While Gigahorse offers precise CFG reconstruction and various out-of-the-box data-flow analyses (such as storage layout partial reconstruction, tainted calls, etc.), it lacks the capability to perform classic symbolic execution of a contract's code. For example, it cannot automatically discover the value of CALLDATA needed to reach a specific instruction. Additionally, we found using Datalog rules (or via the produced artifacts) to be sometimes impractical for creating more complex analyses. This led to the creation of greed!
+greed relies on analyses provided by [Gigahorse](https://github.com/nevillegrech/gigahorse-toolchain) – a fantastic analysis framework for EVM-based smart contracts developed by [Dedaub](https://dedaub.com/). While Gigahorse offers precise CFG reconstruction and various out-of-the-box data-flow analyses (such as storage layout partial reconstruction, tainted calls, etc.), it lacks the capability to perform classic symbolic execution of a contract's code. For example, it cannot automatically discover the value of CALLDATA needed to reach a specific instruction. Additionally, we found using Datalog rules (or via the produced artifacts) to be less user-friendly when trying to quickly prototype research ideas. This led to the creation of greed!
 
 When designing greed, we wanted to provide both a convenient Python wrapper for Gigahorse's analyses and symbolic execution capabilities similar to the popular tool [Mythril](https://github.com/Consensys/mythril). Unlike Mythril, we don't offer a one-click solution to discover smart contract vulnerabilities; instead, we provide a powerful and user-friendly smart contract binary analysis platform (those familiar with [angr](https://github.com/angr/angr) will find many similarities). That being said, one can implement all the analyses offered by Mythril on top of greed.