Manticore: A Symbolic Execution Tool for Analysis Of Smart Contracts

Manticore 

Manticore is a symbolic execution tool for analysis of smart contracts and binaries.

Features

• Program Exploration: Manticore can execute a program with symbolic inputs and explore all the possible states it can reach
• Input Generation: Manticore can automatically produce concrete inputs that result in a given program state
• Error Discovery: Manticore can detect crashes and other failure cases in binaries and smart contracts
• Instrumentation: Manticore provides fine-grained control of state exploration via event callbacks and instruction hooks
• Programmatic Interface: Manticore exposes programmatic access to its analysis engine via a Python API

Manticore can analyze the following types of programs:

• Ethereum smart contracts (EVM bytecode)
• Linux ELF binaries (x86, x86_64, aarch64, and ARMv7)
• WASM Modules

Installation

Note: We recommend installing Manticore in a virtual environment to prevent conflicts with other projects or packages

Option 1: Installing from PyPI:

pip install manticore

Option 2: Installing from PyPI, with extra dependencies needed to execute native binaries:

pip install "manticore[native]"

Option 3: Installing a nightly development build:

pip install --pre "manticore[native]"

Option 4: Installing from the master branch:

git clone https://github.com/trailofbits/manticore.git
cd manticore
pip install -e ".[native]"

Option 5: Install via Docker:

docker pull trailofbits/manticore

Once installed, the manticore CLI tool and Python API will be available.

For a development installation, see our wiki.

Usage

CLI

Manticore has a command line interface which can perform a basic symbolic analysis of a binary or smart contract. Analysis results will be placed into a workspace directory beginning with mcore_. For information about the workspace, see the wiki.

EVM

Manticore CLI automatically detects you are trying to test a contract if (for ex.) the contract has a .sol or a .vy extension. See a demo.

Click to expand:

$ manticore examples/evm/umd_example.sol 
 [9921] m.main:INFO: Registered plugins: DetectUninitializedMemory, DetectReentrancySimple, DetectExternalCallAndLeak, ...
 [9921] m.e.manticore:INFO: Starting symbolic create contract
 [9921] m.e.manticore:INFO: Starting symbolic transaction: 0
 [9921] m.e.manticore:INFO: 4 alive states, 6 terminated states
 [9921] m.e.manticore:INFO: Starting symbolic transaction: 1
 [9921] m.e.manticore:INFO: 16 alive states, 22 terminated states
[13761] m.c.manticore:INFO: Generated testcase No. 0 - STOP(3 txs)
[13754] m.c.manticore:INFO: Generated testcase No. 1 - STOP(3 txs)
...
[13743] m.c.manticore:INFO: Generated testcase No. 36 - THROW(3 txs)
[13740] m.c.manticore:INFO: Generated testcase No. 37 - THROW(3 txs)
[9921] m.c.manticore:INFO: Results in ~/manticore/mcore_gsncmlgx

Manticore-verifier

An alternative CLI tool is provided that simplifys contract testing and allows writing properties methods in the same high-level language the contract uses. Checkout manticore-verifier documentation. See a demo

Native

Click to expand:

$ manticore examples/linux/basic
[9507] m.n.manticore:INFO: Loading program examples/linux/basic
[9507] m.c.manticore:INFO: Generated testcase No. 0 - Program finished with exit status: 0
[9507] m.c.manticore:INFO: Generated testcase No. 1 - Program finished with exit status: 0
[9507] m.c.manticore:INFO: Results in ~/manticore/mcore_7u7hgfay
[9507] m.n.manticore:INFO: Total time: 2.8029580116271973

API

Manticore provides a Python programming interface which can be used to implement powerful custom analyses.

EVM

For Ethereum smart contracts, the API can be used for detailed verification of arbitrary contract properties. Users can set the starting conditions, execute symbolic transactions, then review discovered states to ensure invariants for a contract hold.

Click to expand:

from manticore.ethereum import ManticoreEVM
contract_src="""
contract Adder {
    function incremented(uint value) public returns (uint){
        if (value == 1)
            revert();
        return value + 1;
    }
}
"""
m = ManticoreEVM()

user_account = m.create_account(balance=10000000)
contract_account = m.solidity_create_contract(contract_src,
                                              owner=user_account,
                                              balance=0)
value = m.make_symbolic_value()

contract_account.incremented(value)

for state in m.ready_states:
    print("can value be 1? {}".format(state.can_be_true(value == 1)))
    print("can value be 200? {}".format(state.can_be_true(value == 200)))

Native

It is also possible to use the API to create custom analysis tools for Linux binaries. Tailoring the initial state helps avoid state explosion problems that commonly occur when using the CLI.

Click to expand:

# example Manticore script
from manticore.native import Manticore

m = Manticore.linux('./example')

@m.hook(0x400ca0)
def hook(state):
  cpu = state.cpu
  print('eax', cpu.EAX)
  print(cpu.read_int(cpu.ESP))

  m.kill()  # tell Manticore to stop

m.run()

WASM

Manticore can also evaluate WebAssembly functions over symbolic inputs for property validation or general analysis.

Click to expand:

from manticore.wasm import ManticoreWASM

m = ManticoreWASM("collatz.wasm")

def arg_gen(state):
    # Generate a symbolic argument to pass to the collatz function.
    # Possible values: 4, 6, 8
    arg = state.new_symbolic_value(32, "collatz_arg")
    state.constrain(arg > 3)
    state.constrain(arg < 9)
    state.constrain(arg % 2 == 0)
    return [arg]


# Run the collatz function with the given argument generator.
m.collatz(arg_gen)

# Manually collect return values
# Prints 2, 3, 8
for idx, val_list in enumerate(m.collect_returns()):
    print("State", idx, "::", val_list[0])

Requirements

• Manticore requires Python 3.7 or greater
• Manticore officially supports the latest LTS version of Ubuntu provided by Github Actions
  • Manticore has experimental support for EVM and WASM (but not native Linux binaries) on MacOS
• We recommend running with increased stack size. This can be done by running ulimit -s 100000 or by passing --ulimit stack=100000000:100000000 to docker run

Compiling Smart Contracts

• Ethereum smart contract analysis requires the solc program in your $PATH.
• Manticore uses crytic-compile to build smart contracts. If you're having compilation issues, consider running crytic-compile on your code directly to make it easier to identify any issues.
• We're still in the process of implementing full support for the EVM Istanbul instruction semantics, so certain opcodes may not be supported. In a pinch, you can try compiling with Solidity 0.4.x to avoid generating those instructions.

Using a different solver (Yices, Z3, CVC4)

Manticore relies on an external solver supporting smtlib2. Currently Z3, Yices and CVC4 are supported and can be selected via commandline or configuration settings. If Yices is available, Manticore will use it by default. If not, it will fall back to Z3 or CVC4. If you want to manually choose which solver to use, you can do so like this: manticore --smt.solver Z3

Installing CVC4

For more details go to https://cvc4.github.io/. Otherwise just get the binary and use it.

    sudo wget -O /usr/bin/cvc4 https://github.com/CVC4/CVC4/releases/download/1.7/cvc4-1.7-x86_64-linux-opt
    sudo chmod +x /usr/bin/cvc4

Installing Yices

Yices is incredibly fast. More details here https://yices.csl.sri.com/

    sudo add-apt-repository ppa:sri-csl/formal-methods
    sudo apt-get update
    sudo apt-get install yices2

Getting Help

Feel free to stop by our #manticore slack channel in Empire Hacking for help using or extending Manticore.

Documentation is available in several places:

The wiki contains information about getting started with Manticore and contributing

The API reference has more thorough and in-depth documentation on our API

The examples directory has some small examples that showcase API features

The manticore-examples repository has some more involved examples, including some real CTF problems

If you'd like to file a bug report or feature request, please use our issues page.

For questions and clarifications, please visit the discussion page.

Download Details:
Author: trailofbits
Source Code: https://github.com/trailofbits/manticore
License: AGPL-3.0 License

#blockchain  #solidity  #ethereum  #smartcontract #python 

What is GEEK

Buddha Community

PySQL Tutorial: A Database Framework for Python

PySQL 

PySQL is database framework for Python (v3.x) Language, Which is based on Python module mysql.connector, this module can help you to make your code more short and more easier. Before using this framework you must have knowledge about list, tuple, set, dictionary because all codes are designed using it. It's totally free and open source.

Tutorial Video in English (Watch Now)

Installation

Before we said that this framework is based on mysql.connector so you have to install mysql.connector first on your system. Then you can import pysql and enjoy coding!

python -m pip install mysql-connector-python

After Install mysql.connector successfully create Python file download/install pysql on the same dir where you want to create program. You can clone is using git or npm command, and you can also downlaod manually from repository site.

PyPi Command

Go to https://pypi.org/project/pysql-framework/ or use command

pip install pysql-framework

Git Command

git clone https://github.com/rohit-chouhan/pysql

Npm Command

Go to https://www.npmjs.com/package/pysql or use command

$ npm i pysql

Snippet Extention for VS Code

Install From Here https://marketplace.visualstudio.com/items?itemName=rohit-chouhan.pysql

Table of contents

• Connecting a Server
• Create a Database in Server
• Drop Database
• Connecting a Database
• Creating Table in Database
• Drop Table in Database
• Selecting data from Table
• Add New Column to Table
• Modify Column to Table
• Drop Column from Table
• Manual Execute Query
• Inserting data
• Updating data
• Deleting data

Connecting a Server

---

To connect a database with localhost server or phpmyadmin, use connect method to establish your python with database server.

import pysql

db = pysql.connect(
    "host",
    "username",
    "password"
 )

Create a Database in Server

---

Creating database in server, to use this method

import pysql

db = pysql.connect(
    "host",
    "username",
    "password"
 )
 pysql.createDb(db,"demo")
 #execute: CREATE DATABASE demo

Drop Database

---

To drop database use this method .

Syntex Code -

pysql.dropDb([connect_obj,"table_name"])

Example Code -

pysql.dropDb([db,"demo"])
#execute:DROP DATABASE demo

Connecting a Database

---

To connect a database with localhost server or phpmyadmin, use connect method to establish your python with database server.

import pysql

db = pysql.connect(
    "host",
    "username",
    "password",
    "database"
 )

Creating Table in Database

---

To create table in database use this method to pass column name as key and data type as value.

Syntex Code -

pysql.createTable([db,"table_name_to_create"],{
    "column_name":"data_type", 
    "column_name":"data_type"
})

Example Code -

pysql.createTable([db,"details"],{
    "id":"int(11) primary", 
     "name":"text", 
    "email":"varchar(50)",
    "address":"varchar(500)"
})

2nd Example Code -

Use can use any Constraint with Data Value

pysql.createTable([db,"details"],{
    "id":"int NOT NULL PRIMARY KEY", 
     "name":"varchar(20) NOT NULL", 
    "email":"varchar(50)",
    "address":"varchar(500)"
})

Drop Table in Database

---

To drop table in database use this method .

Syntex Code -

pysql.dropTable([connect_obj,"table_name"])

Example Code -

pysql.dropTable([db,"users"])
#execute:DROP TABLE users

Selecting data from Table

---

For Select data from table, you have to mention the connector object with table name. pass column names in set.

Syntex For All Data (*)-

records = pysql.selectAll([db,"table_name"])
for x in records:
  print(x)

Example - -

records = pysql.selectAll([db,"details"])
for x in records:
  print(x)
#execute: SELECT * FROM details

Syntex For Specific Column-

records = pysql.select([db,"table_name"],{"column","column"})
for x in records:
  print(x)

Example - -

records = pysql.select([db,"details"],{"name","email"})
for x in records:
  print(x)
#execute: SELECT name, email FROM details

Syntex Where and Where Not-

#For Where Column=Data
records = pysql.selectWhere([db,"table_name"],{"column","column"},("column","data"))

#For Where Not Column=Data (use ! with column)
records = pysql.selectWhere([db,"table_name"],{"column","column"},("column!","data"))
for x in records:
  print(x)

Example - -

records = pysql.selectWhere([db,"details"],{"name","email"},("county","india"))
for x in records:
  print(x)
#execute: SELECT name, email FROM details WHERE country='india'

Add New Column to Table

---

To add column in table, use this method to pass column name as key and data type as value. Note: you can only add one column only one call

Syntex Code -

pysql.addColumn([db,"table_name"],{
    "column_name":"data_type"
})

Example Code -

pysql.addColumn([db,"details"],{
    "email":"varchar(50)"
})
#execute: ALTER TABLE details ADD email varchar(50);

Modify Column to Table

---

To modify data type of column table, use this method to pass column name as key and data type as value.

Syntex Code -

pysql.modifyColumn([db,"table_name"],{
    "column_name":"new_data_type"
})

Example Code -

pysql.modifyColumn([db,"details"],{
    "email":"text"
})
#execute: ALTER TABLE details MODIFY COLUMN email text;

Drop Column from Table

---

Note: you can only add one column only one call

Syntex Code -

pysql.dropColumn([db,"table_name"],"column_name")

Example Code -

pysql.dropColumn([db,"details"],"name")
#execute: ALTER TABLE details DROP COLUMN name

Manual Execute Query

---

To execute manual SQL Query to use this method.

Syntex Code -

pysql.query(connector_object,your_query)

Example Code -

pysql.query(db,"INSERT INTO users (name) VALUES ('Rohit')")

Inserting data

---

For Inserting data in database, you have to mention the connector object with table name, and data as sets.

Syntex -

data =     {
    "db_column":"Data for Insert",
    "db_column":"Data for Insert"
}
pysql.insert([db,"table_name"],data)

Example Code -

data =     {
    "name":"Komal Sharma",
    "contry":"India"
}
pysql.insert([db,"users"],data)

Updating data

---

For Update data in database, you have to mention the connector object with table name, and data as tuple.

Syntex For Updating All Data-

data = ("column","data to update")
pysql.updateAll([db,"users"],data)

Example - -

data = ("name","Rohit")
pysql.updateAll([db,"users"],data)
#execute: UPDATE users SET name='Rohit'

Syntex For Updating Data (Where and Where Not)-

data = ("column","data to update")
#For Where Column=Data
where = ("column","data")

#For Where Not Column=Data (use ! with column)
where = ("column!","data")
pysql.update([db,"users"],data,where)

Example -

data = ("name","Rohit")
where = ("id",1)
pysql.update([db,"users"],data,where)
#execute: UPDATE users SET name='Rohit' WHERE id=1

Deleting data

---

For Delete data in database, you have to mention the connector object with table name.

Syntex For Delete All Data-

pysql.deleteAll([db,"table_name"])

Example - -

pysql.deleteAll([db,"users"])
#execute: DELETE FROM users

Syntex For Deleting Data (Where and Where Not)-

where = ("column","data")

pysql.delete([db,"table_name"],where)

Example -

#For Where Column=Data
where = ("id",1)

#For Where Not Column=Data (use ! with column)
where = ("id!",1)
pysql.delete([db,"users"],where)
#execute: DELETE FROM users WHERE id=1

--- Finish ---

Change Logs

[19/06/2021]
 - ConnectSever() removed and merged to Connect()
 - deleteAll() [Fixed]
 - dropTable() [Added]
 - dropDb() [Added]
 
[20/06/2021]
 - Where Not Docs [Added]

The module is designed by Rohit Chouhan, contact us for any bug report, feature or business inquiry.

Author: rohit-chouhan
Source Code: https://github.com/rohit-chouhan/pysql
License: Apache-2.0 License

#python 

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