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README.md
Nagini is an automatic verifier for statically typed Python programs, based on the Viper <http://viper.ethz.ch>_ verification infrastructure. Nagini is being developed at the Programming Methodology Group <https://www.pm.inf.ethz.ch/research/nagini.html>_ at ETH Zurich.
Our CAV 2018 tool paper describing Nagini can be found here <http://pm.inf.ethz.ch/publications/getpdf.php?bibname=Own&id=EilersMueller18.pdf>, and a more detailed description of its encoding can be found in Marco Eilers' thesis <https://pm.inf.ethz.ch/publications/Eilers2022.pdf>. Also see the Wiki <https://github.com/marcoeilers/nagini/wiki>_ for the documentation of Nagini's specification language. See the changelog <CHANGELOG.md>_ for the version history.
Visual Studio Code Plugin
Nagini can be used via a Vistual Studio code plugin available here <https://marketplace.visualstudio.com/items?itemName=viper-admin.nagini-ide>_. The plugin requires Java and Python to be installed (see dependencies below).
Dependencies (Ubuntu Linux)
Install Java 11 or newer (64 bit) and a Python version between Python 3.12 and 3.14 (64 bit).
Install the the required libraries, in particular, python3.x-dev.
For usage with Viper's verification condition generation backend Carbon, you will also need to install Boogie (version 2.15.9).
Dependencies (Windows)
Install Java 11 or newer (64 bit) and a Python version between Python 3.12 and 3.14 (64 bit).
Install the required version of either Visual C++ Build Tools or Visual Studio.
For usage with Viper's verification condition generation backend Carbon, you will also need to install Boogie (version 2.15.9).
Getting Started
Execute the following commands (on Windows, you may have to use cmd and not PowerShell):
Create a virtual environment::
virtualenv --python=python3.14 <env>
Activate it::
source env/bin/activate
on Linux, or::
env\Scripts\activate
on Windows.
Install Nagini from PyPI::
pip install nagini
# or with optional dependencies for server mode and testing:
pip install "nagini[server,test]"
Alternatively, to get the most up-to-date version, install from source::
git clone https://github.com/marcoeilers/nagini.git
cd nagini
pip install .
# or with optional dependencies for server mode and testing:
pip install ".[server,test]"
A pre-built Docker container with Python 3.12, Java 17, Z3, Boogie, and Nagini is maintained at docker-nagini <https://github.com/bigtalk-org/docker-nagini>_ (published to GitHub Container Registry).
To verify a file without installing local dependencies, run::
docker run --rm -v $(pwd):/code ghcr.io/bigtalk-org/docker-nagini path/to/file.py
Images for both Silicon (ghcr.io/bigtalk-org/docker-nagini:silicon) and Carbon (ghcr.io/bigtalk-org/docker-nagini:carbon) backends are available.
Command Line Usage
To verify a specific file from the nagini directory, run::
nagini [OPTIONS] path-to-file.py
You may have to explicitly supply a path to a Z3 executable (use version 4.8.7, other versions may offer significantly worse performance) using the command line parameter --z3=path/to/z3.
Additionally, you may have to set the environment variable JAVA_HOME to point to your Java installation.
See the wiki <https://github.com/marcoeilers/nagini/wiki>_ for information on how to write specifications in Nagini.
The following command line options are available::
--verifier
Selects the Viper backend to use for verification.
Possible options are 'silicon' (for Symbolic Execution) and 'carbon'
(for Verification Condition Generation based on Boogie).
Default: 'silicon'.
--select
Select which functions/methods/classes to verify. Expects a comma-
separated list of names.
--counterexample
Enable outputting counterexamples for verification errors (experimental).
--sif=v
Enable verification of secure information flow. v can be 'true' for ordinary
non-interference (for sequential programs only), 'poss' for possiblistic
non-intererence (for concurrent programs) or 'prob' for probabilistic non-
interference (for concurrent programs).
--float-encoding
Selects a different encoding of floating point values. The default is to model floats
as abstract values and all float operations as uninterpreted functions, so that essentially
nothing can be proved about them. Legal values for this option are 'real' to model floats
as real numbers (i.e., not modeling floating point imprecision), or 'ieee32' to model them
as proper IEEE 32 bit floats. The latter option unfortunately usually leads to very long
verification times or non-termination.
--int-bitops-size
Bitwise operations on integers (e.g. 12 ^ -5) are supported only for integers which can
be proven to be in a specific range, namely the range of n-bit signed integers.
This parameter sets the value of n.
Default: 8.
--boogie
Sets the path of the Boogie executable. Required if the Carbon backend
is selected. Alternatively, the 'BOOGIE_EXE' environment variable can be
set.
--viper-jar-path
Sets the path to the required Viper binary ('viperserver.jar').
A single jar bundles both the Silicon and Carbon backends, so it
is used regardless of the selected backend. You can either use the
provided binary packages installed by default or compile your own
from source (see below).
Expects either a single path or a colon- (Unix) or semicolon-
(Windows) separated list of paths. Alternatively, the environment
variable 'VIPERSERVERJAR' can be set, or 'VIPERJAVAPATH' for a
full explicit classpath.
To see all possible command line options, invoke nagini without arguments.
Server Mode / Faster Verification Mode
Nagini has to do a significant amount of work on startup, and has to start a JVM to run Viper.
To avoid some of that startup work and speed up Viper's runtime, Nagini has a server mode.
To use it,
Install pyzmq::
pip install "nagini[server]"
Start a Nagini server::
nagini --server <otherArgs> dummyFile.py
Note that all required arguments, including JAVA_HOME and other potentially required
environment variables, have to be set here. The dummy file does not need to exist, it is
never read, but some file name has to be supplied.
Wait a few seconds to allow the server to start up. It prints a message like Server started successfully on <address> when it is ready.
While the server is running, run a client to instruct the server to verify a specific file::
nagini_client path/to/file.py
Model Context Protocol (MCP) Server
Nagini ships an MCP server that exposes verification to AI agents and MCP-capable
editors (e.g. Claude Code, Claude Desktop, Cursor) over stdio. Through it, an agent
can verify entire files, individual methods, or inline snippets and receive
structured diagnostics (error positions, messages, and optional counterexamples).
Install Nagini with the MCP dependencies::
pip install "nagini[mcp]"
As with normal command-line use, a Java installation is required. The Z3 and
Viper JAR binaries needed for verification are bundled with Nagini, so you do
not need to supply them separately. If Java is not found automatically, set the
JAVA_HOME environment variable to point to your Java installation.
The server is launched via the nagini_mcp entry point and communicates over
stdio, so it is normally started by the MCP client rather than by hand. Configure
your client to run it, passing JAVA_HOME through the environment if needed.
For example::
Use the absolute path to the nagini_mcp executable (e.g. the one inside your
virtual environment) if it is not on the client's PATH. The server uses the
faster in-process ViperServer backend by default and accepts the same
configuration options as the command line (e.g. --verifier); run
nagini_mcp --help to see them.
The server exposes the following tools: verify_file, verify_method,
verify_snippet, configure (change verification options at runtime),
cancel, and flush_cache. The verification tools also accept per-request
options: extra Viper backend arguments (viper_args, e.g. a --timeout)
and returning the translated Viper program (include_viper). See the
wiki <https://github.com/marcoeilers/nagini/wiki>_ for information on how to write
specifications in Nagini.
Alternative Viper Versions
To use a more recent or custom version of the Viper infrastructure, follow the
instructions here <https://github.com/viperproject/documentation/wiki>_. Look for
sbt assembly to find instructions for packaging the required JAR files. Use the
parameters mentioned above to instruct Nagini to use your custom Viper version.
Troubleshooting
On Windows: During the setup, you get an error like Microsoft Visual C++ 14.0 is required. or Unable to fnd vcvarsall.bat:
Python cannot find the required Visual Studio C++ installation, make sure you have either installed the Build Tools or checked the "Common Tools" option in your regular Visual Studio installation (see above).
While verifying a file, you get a stack trace ending with something like No matching overloads found:
The version of Viper you're using does not match your version of Nagini. Try updating both to the newest version.
Nagini cannot prove trivial properties about the return values of functions:
This is likely due to a lack of specifications, see the discussion in the General Contracts section of the wiki <https://github.com/marcoeilers/nagini/wiki>_.
Publications on Nagini
The following papers describe verification techniques implemented in Nagini:
Nagini: A Static Verifier for Python <http://pm.inf.ethz.ch/publications/getpdf.php?bibname=Own&id=EilersMueller18.pdf>_ — Marco Eilers and Peter Müller, CAV 2018. The original tool paper presenting Nagini's design and specification language.
Modular Specification and Verification of Security Properties for Mainstream Languages <https://pm.inf.ethz.ch/publications/Eilers2022.pdf>_ — Marco Eilers, PhD Thesis, ETH Zurich (2022). A detailed description of Nagini's encoding and verification approach.
Product Programs in the Wild: Retrofitting Program Verifiers to Check Information Flow Security <https://pm.inf.ethz.ch/publications/EilersMeierMueller21.pdf>_ — Marco Eilers, Severin Meier, and Peter Müller, CAV 2021. Describes Nagini's support for verifying information flow security (noninterference) via product programs constructed at the Viper intermediate language level.
Modular Reasoning about Object Relations <https://pm.inf.ethz.ch/publications/GreutmannEilersMueller26.pdf>_ — Micha Greutmann, Marco Eilers, and Peter Müller (2026). Presents a modular technique for verifying algebraic properties of object relations such as equality, implemented in Nagini.
Published Work Using Nagini
The following papers and theses have used Nagini to verify Python programs:
Self-Spec Verifiable Code Generation <https://arxiv.org/pdf/2609.39568>_ — Qian et al., Peking University (2026). Introduces VeriCodeBench, a benchmark of 400 problems across C, Java, Rust, and Python in which LLMs must generate both their own specifications and verified code; the Python track uses Nagini.
SWE-Proof: Can Language Models Resolve Real-World Issues with Machine-Checked Proofs? <https://arxiv.org/pdf/2609.21190>_ — Ma et al., UC Berkeley / Georgia Tech / UIUC / AWS AI Labs (2026). Turns the 500 real-world issues of SWE-bench Verified into formally verified coding tasks for LLM agents, using Nagini as one of three verification backends (alongside Velvet and Lean).
Formally Verified ASN.1 Python Encoders and Decoders <https://ethz.ch/content/dam/ethz/special-interest/infk/chair-program-method/pm/documents/Education/Theses/Luca_Schafroth_MS_Report.pdf>_ — Luca Schafroth, ETH Zurich Master's Thesis (2026). Formal verification of ASN.1/ACN-generated Python codecs using Nagini, proving round-trip correctness for several data types and fully verifying the BitStream runtime component.
A Verification-Aware Pipeline for Programmable Logic Controllers <https://www.es.mdu.se/pdf_publications/7311.pdf>_ — Salari et al., Mälardalen University (2025). Verifies Python models of industrial IEC 61131-3 Function Block Diagram programs (from an electropneumatic brake control subsystem) generated by the PyLC+ framework.
VeriGuard: Enhancing LLM Agent Safety via Verified Code Generation <https://arxiv.org/pdf/2510.05156>_ — Miculicich et al., Google (2025). Uses Nagini to formally verify behavioral policies for LLM-based AI agents, providing runtime safety guarantees for agent actions.
Can LLMs Enable Verification in Mainstream Programming? <https://arxiv.org/pdf/2503.14183>_ — Shefer et al., JetBrains Research (2025). Evaluates LLMs' ability to generate verified code across Dafny, Nagini, and Verus using benchmarks derived from HumanEval.
An LLM Benchmark Suite for Specification Inference <https://ethz.ch/content/dam/ethz/special-interest/infk/chair-program-method/pm/documents/Education/Theses/wiwest_Masters_Thesis.pdf>_ — William West, ETH Zurich Master's Thesis (2025). Develops a benchmark for evaluating LLMs on program verification inference tasks, including Nagini specification synthesis.
Large Language Models for Verified Programs <https://ethz.ch/content/dam/ethz/special-interest/infk/chair-program-method/pm/documents/Education/Theses/omkar_thesis-omkar-zade.pdf>_ — Omkar Zade, ETH Zurich Master's Thesis (2024). Uses LLMs to automatically infer Nagini memory-safety specifications for Python programs, contributing a dataset of verified programs as a benchmark.
Hierarchical Program-Triggered Reinforcement Learning Agents for Automated Driving <https://arxiv.org/pdf/2103.13861>_ — Gangopadhyay et al., IIT Kharagpur, IEEE Transactions on Intelligent Transportation Systems (2021). Uses Nagini to verify that the structured Python program controlling a hierarchy of RL driving agents satisfies safety specifications.
Igloo: Soundly Linking Compositional Refinement and Separation Logic for Distributed System Verification <https://arxiv.org/pdf/2010.04749>_ — Sprenger et al., ETH Zurich, OOPSLA 2020. Uses Nagini to verify that Python implementations of distributed protocols (leader election, replication, and a security protocol) satisfy I/O specifications derived from Isabelle/HOL models.
Static Verification of the SCION Router Implementation <https://ethz.ch/content/dam/ethz/special-interest/infk/chair-program-method/pm/documents/Education/Theses/Sascha_Forster_BA_report(3).pdf>_ — Sascha Forster, ETH Zurich Bachelor's Thesis (2018). Verifies memory safety, progress, and I/O behaviour of the SCION border router's Python implementation using Nagini.
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