mythril
infer
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mythril | infer | |
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12 | 42 | |
3,717 | 14,708 | |
1.2% | 0.6% | |
8.1 | 9.9 | |
4 days ago | 2 days ago | |
Python | OCaml | |
MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
mythril
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Fuzzing Around: Better Smart Contract Testing through the Power of Random Inputs
Fuzzing has been around for a while in traditional full-stack development, but a new class of tools is here that can apply fuzzing to smart contract testing in web3. Some of the fuzzing tools include the open source Echidna and MythX.
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Mythril an easy way to audit your smart contracts.
Mythril is part of the core tools of Consensys Mythx one of the biggest Smart Contract security services for Ethereum, which main goal is to ensure development teams avoid costly errors and make Ethereum more secure and trustworthy… or at least that is what their page says.
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How do you guarantee the security of your smart contracts?
Other than audits and testing, there's automated security checking: https://github.com/ConsenSys/mythril I'm yet to try this in one of my projects
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Launching your Ethereum dApp on Avalanche
Mythril
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A Comprehensive Guide on Web3 Programming Languages and Tools
MythX, Mythril, Manticore, and Echidna are other tools for security audits.
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Tools to verify solidity code
Smart Contract Weakness Classification and Test Cases: https://swcregistry.io/ OKO Contract Explorer: https://oko.palkeo.com/txview Slither: https://github.com/crytic/slither MythX: https://mythx.io/ Tenderly: https://tenderly.dev/ Spot check program: https://docs.google.com/document/d/16...
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Static analysis of smartcontracts?
There are some paid tools and some free ones. A few that come to mind are ConsenSys MythX (based in part on the open-source Mythril), ShiftLeft, Oyente, Octopus… maybe best to just check out ETHSecurity’s list.
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Formal Verification Methods in industry
When you say "formal verification methods", what kind of techniques are you interested in? While using interactive theorem provers will most likely not become very widespread, there are plenty of tools that use formal techniques to give more correctness guarantees. These tools might give some guarantees, but do not guarantee complete functional correctness. WireGuard (VPN tunnel) is I think a very interesting application where they verified the protocol. There are also some tools in use, e.g. Mythril and CrossHair, that focus on detecting bugs using symbolic execution. There's also INFER from Facebook/Meta which tries to verify memory safety automatically. The following GitHub repo might also interest you, it lists some companies that use formal methods: practical-fm
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Please check this if you are looking for a good tokenomics project.
- Audited by MythX.io
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What kind of Ethereum node/API/setup do I need for these use cases?
ability to run security analysis on contracts using for .e.g. https://github.com/ConsenSys/mythril
infer
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An Introduction to Temporal Logic (With Applications to Concurrency Problems)
I think most development occurs on problems that can't be formally modeled anyway. Most developers work on things like, "can you add this feature to the e-commerce site? And can the pop-up be blue?" which isn't really model-able.
But that's not to say that formal methods are useless! We can still prove some interesting aspects of programs -- for example, that every lock that gets acquired later gets released. I think tools like Infer[0] could become common in the coming years.
[0]: https://fbinfer.com/
- Should I Rust or should I Go
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Enforcing Memory Safety?
Using infer, someone else exploited null-dereference checks to introduce simple affine types in C++. Cppcheck also checks for null-dereferences. Unfortunately, that approach means that borrow-counting references have a larger sizeof than non-borrow counting references, so optimizing the count away potentially changes the semantics of a program which introduces a whole new way of writing subtly wrong code.
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Interesting ocaml mention in buck2 by fb
Meta/Facebook are long time OCaml users, their logo is on the OCaml website. Their static analysis tool and its predecessor are both written in OCaml.
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CISA Director Easterly's comments about cyber security. Agree or disagree?
Then this idea that the US government will tell tech companies how to write secure software. Let's get this straight, the private sector, especially big tech is miles ahead of US government in this regard. Microsoft literally invented threat modelling and modern exploit mitigations. Facebook has the best appsec processes pretty much in the whole world, including their own cutting edge code analyzer. AWS uses formal verification everywhere. Meanwhile the US government itself runs mission-critical systems that's almost literally held together by bubble gum and toothpicks. Maybe they could dial down the arrogance a tad, get their own shit together, learn how this cyber stuff is actually done and only then try lecturing everyone else.
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A plan for cybersecurity and grid safety
Efforts: Dependabot, CodeQL, Coverity, facebook's Infer tool, etc
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A quick look at free C++ static analysis tools
I notice there isn't fbinfer. It's pretty cool, and is used for this library.
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silly guy
"Move fast, break stuff" is a great approach when you aren't pushing the broken bits to production. Fuck, even Facebook, the big "move fast, break stuff" company, uses tools to detect errors in its continuous integration toolchain. https://fbinfer.com/
- OCaml 5.0 Multicore is out
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Beyond Functional Programming: The Verse Programming Language (Epic Games' new language with Simon Peyton Jones)
TBH, there's a non-zero amount of non-"ivory tower" tools you may have used that are written in functional languages. Say, Pandoc or Shellcheck are written in Haskell; Infer and Flow are written in OCaml. RabbitMQ and Whatsapp are implemented in Erlang (FB Messenger was too, originally; they switched to the C++ servers later). Twitter backend is (or was, at least) written in Scala.
What are some alternatives?
manticore - Symbolic execution tool
SonarQube - Continuous Inspection
truffle - :warning: The Truffle Suite is being sunset. For information on ongoing support, migration options and FAQs, visit the Consensys blog. Thank you for all the support over the years.
Spotbugs - SpotBugs is FindBugs' successor. A tool for static analysis to look for bugs in Java code.
slither - Static Analyzer for Solidity and Vyper
Error Prone - Catch common Java mistakes as compile-time errors
smart-contract-best-practices - A guide to smart contract security best practices
FindBugs - The new home of the FindBugs project
solc-select - Manage and switch between Solidity compiler versions
PMD - An extensible multilanguage static code analyzer.
pyteal - Algorand Smart Contracts in Python
Checkstyle - Checkstyle is a development tool to help programmers write Java code that adheres to a coding standard. By default it supports the Google Java Style Guide and Sun Code Conventions, but is highly configurable. It can be invoked with an ANT task and a command line program.