FlowPy

A static information flow control (IFC) checker - in Python, for Python.

Installation

1. Clone this repository: git clone git@github.com:zsabbagh/flowpy.git or git clone https://github.com/zsabbagh/flowpy.git.
2. Change directory to the project root: cd flowpy.
3. Install the package: pip install . (or pip install -e . for developers).

What

Information flow control is a way of monitoring and possibly restricting the flow of information within a system. It's different from many other security measures such as cryptography or access control, since it aims to show what information is being propagated to where even after it's been "lawfully" accessed. For example, controlling who can access a file can be a good security measure, but once it's been accessed this control can't really do much more. IFC, on the other hand, helps provide a proper overview regardless of what other procedures are in place, making it very interesting from a security standpoint.

Why

While taking a course in language-based security (LBS) at KTH Royal Institute of Technology, we found the concept of statically checking programs for insecure information flows interesting. Combine this with a fascination for abstract syntax trees (ASTs) and a general love for programming, and this project was born :)

Despite this ''just'' being our project for the course mentioned above, we try to keep the code reasonably clean and well-commented. Any questions or input is welcome!

How

We make heavy use of two main Python libraries: tokenize for parsing the comments used for telling FlowPy what functions to check, and ast to be able to properly analyse them.

Each time we find one or more comments asking FlowPy to check a function, we parse all the rules present in these comments while looking for the function name. The parsed rules are placed into a State object, which keeps track of the current security context and each variable's security labels, and when we find the function name we store it together with the State. Once the entire file has been parsed, we create a FunctionEvaluator for each function and start the evaluation. This traverses the AST in order, verifying each statement or expression using a set of predetermined rules. If any breaches of these rules are found, FlowPy will output a warning for each of these cases.

Usage

Rules are Python comments and follow the grammar # fp var: label_1, label_2, etc. var*: label_3.. This rule gives the variable var the labels label_1, label_2 and etc. All labels that match the wildcard pattern var*, i.e. anything starting with var to also have label_3. Note that this implies that var has label_3.

Completely empty label sets are always prioritised. These are denoted with the rule var: (). and cannot include any other label in rule. This is made available to be able to wipe rules in certain function definitions/scopes.

To run the programme, simply do:

• flowpy <file-to-test> (or -h for more info).
• Preferrably, see the demo programmes for files to test FlowPy on.

Testing

To test FlowPy, install pytest and run it from the project root directory.