This Python package is a collection of modules to allow easier interactive use of angr for learning and prototyping angr.

All features are designed for the use of angr in an interactive environment like an IPython shell or a Jupyter environment (both CLI and Notebook), but some will still work in a simple Python shell or script.

Using a font that supports Ligatures like JetBrains Mono is recommended to make the output more pleasant to read.

A stable version is available on PyPi.

pip install angrcli

In case you want a development install of this, run this in a folder of your choice (e.g. your angr-dev repo) after activating your angr virtual environment

git clone https://github.com/fmagin/angr-cli.git
cd angr-cli
pip install -e ./

To import and setup all features:

import angrcli.full

This will take care of importing and registering the plugins.

The Context View plugin allows rendering of a state in a view similiar to that provided by GDB plugins like GEF or pwndbg.

import angr
# This line registers the plugin and makes it available on each state
import angrcli.plugins.ContextView
proj = angr.Project("/bin/ls", load_options={"auto_load_libs":False})
state = proj.factory.entry_state()
# Print the state
state.context_view.pprint()

The Interactive Exploration is a Python CMD wrapper around a Simulation Manager that provides shortcuts for various common operations, like stepping blocks, running until a symbolic branch or manually selecting successors.

This can either be used in a script, or inside an IPython shell. The latter allows rapid switching between the wrapper to access the shortcuts and the IPython shell for more complex operations.

import angr
import angrcli.plugins.ContextView
from angrcli.interaction.explore import ExploreInteractive
proj = angr.Project("/bin/ls", load_options={"auto_load_libs":False})
state = proj.factory.entry_state()
# For quick but less flexible access (state isn't modified)
state.explore()
# state.explore() basically just does the following on each call
e = ExploreInteractive(proj, state)
e.cmdloop()

angrcli.ast.rendering provides render_ast which uses graphviz to generate a SVG representation of an AST which can be displayed instead of the __repr__ method of the AST object.

import claripy
from angrcli.ast.rendering import render_ast
from claripy.ast.bv import BV
BV._repr_svg_ = lambda self: render_ast(self)._repr_svg_()
x = claripy.BVS('x', 32)
y = claripy.BVS('y', 32)