Verifpal is new software for verifying the security of cryptographic protocols. Building upon contemporary research in symbolic formal verification, Verifpal’s main aim is to appeal more to real-world practitioners, students and engineers without sacrificing comprehensive formal verification features.
In order to achieve this, Verifpal introduces a new, intuitive language for modeling protocols that is much easier to write and understand than the languages employed by existing tools. At the same time, Verifpal is able to model protocols under an active attacker with unbounded sessions and fresh values, and supports queries for advanced security properties such as forward secrecy or key compromise impersonation.
Verifpal has already been used to verify security properties for Signal, Scuttlebutt, TLS 1.3, Telegram and other protocols. It is a community-focused project, and available under a GPLv3 license.
An Intuitive Protocol Modeling Language
The Verifpal language is meant to illustrate protocols close to how one may describe them in an informal conversation, while still being precise and expressive enough for formal modeling. Verifpal reasons about the protocol model with explicit principals: Alice and Bob exist and have independent states.
Modeling that Avoids User Error
Verifpal does not allow users to define their own cryptographic primitives. Instead, it comes with built-in cryptographic functions — this is meant to remove the potential for users to define fundamental cryptographic operations incorrectly.
Easy to Understand Analysis Output
When a contradiction is found for a query, the result is related in a readable format that ties the attack to a real-world scenario. This is done by using terminology to indicate how the attack could have been possible, such as through a man-in-the-middle on ephemeral keys.
Friendly and Integrated Software
Verifpal comes with a Visual Studio Code extension that offers syntax highlighting and, soon, live query verification within Visual Studio Code, allowing developers to obtain insights on their model as they are writing it.