Zope3 Security

Introduction

The Security framework provides a generic mechanism to implement security policies on Python objects. This introduction provides a tutorial of the framework explaining concepts, design, and going through sample usage from the perspective of a Python programmer using the framework outside of Zope.

Definitions

Principal

A generalization of a concept of a user.

Permission

A kind of access, i.e. permission to READ vs. permission to WRITE. Fundamentally the whole security framework is organized around checking permissions on objects.

Purpose

The security framework's primary purpose is to guard and check access to Python objects. It does this by providing mechanisms for explicit and implicit security checks on attribute access for objects. Attribute names are mapped onto permission names when checking access and the implementation of the security check is defined by the security policy, which receives the object, the permission name, and an interaction.

Interactions are objects that represent the use of the system by one or more principals. An interaction contains a list of participations, which represents the way a single principal participates in the interaction. An HTTP request is one example of a participation.

Its important to keep in mind that the policy provided is just a default, and it can be substituted with one which doesn't care about principals or interactions at all.

Framework Components

Low Level Components

These components provide the infrastructure for guarding attribute access and providing hooks into the higher level security framework.

Checkers

A checker is associated with an object kind, and provides the hooks that map attribute checks onto permissions deferring to the security manager (which in turn defers to the policy) to perform the check.

Additionally, checkers provide for creating proxies of objects associated with the checker.

There are several implementation variants of checkers, such as checkers that grant access based on attribute names.

Proxies

Wrappers around Python objects that implicitly guard access to their wrapped contents by delegating to their associated checker. Proxies are also viral in nature, in that values returned by proxies are also proxied.

High Level Components

Security Management

Provides accessors for setting up interactions and the global security policy.

Interaction

Stores transient information on the list of participations.

Participation

Stores information about a principal participating in the interaction.

Security Policy

Provides a single method that accepts the object, the permission, and the interaction of the access being checked and is used to implement the application logic for the security framework.

Narrative (agent sandbox)

As an example we take a look at constructing a multi-agent distributed system, and then adding a security layer using the Zope security model onto it.

Scenario

Our agent simulation consists of autonomous agents that live in various agent homes/sandboxes and perform actions that access services available at their current home. Agents carry around authentication tokens which signify their level of access within any given home. Additionally agents attempt to migrate from home to home randomly.

The agent simulation was constructed separately from any security aspects. Now we want to define and integrate a security model into the simulation. The full code for the simulation and the security model is available separately; we present only relevant code snippets here for illustration as we go through the implementation process.

For the agent simulation we want to add a security model such that we group agents into two authentication groups, "norse legends", including the principals thor, odin, and loki, and "greek men", including prometheus, archimedes, and thucydides.

We associate permissions with access to services and homes. We differentiate the homes such that certain authentication groups only have access to services or the home itself based on the local settings of the home in which they reside.

We define the homes/sandboxes

  • origin - all agents start here, and have access to all services here.
  • valhalla - only agents in the authentication group 'norse legend' can reside here.
  • jail - all agents can come here, but only 'norse legend's can leave or access services.

Process

Loosely we define a process for implementing this security model

  • mapping permissions onto actions
  • mapping authentication tokens onto permissions
  • implementing checkers and security policies that use our authentication tokens and permissions.
  • binding checkers to our simulation classes
  • inserting the hooks into the original simulation code to add proxy wrappers to automatically check security.
  • inserting hooks into the original simulation to register the agents as the active principal in an interaction.

Defining a Permission Model

We define the following permissions:

NotAllowed = 'Not Allowed'
Public = Checker.CheckerPublic
TransportAgent = 'Transport Agent'
AccessServices = 'Access Services'
AccessAgents = 'Access Agents'
AccessTimeService = 'Access Time Services'
AccessAgentService = 'Access Agent Service'
AccessHomeService = 'Access Home Service'

and create a dictionary database mapping homes to authentication groups which are linked to associated permissions.

Defining and Binding Checkers

Checkers are the foundational unit for the security framework. They define what attributes can be accessed or set on a given instance. They can be used implicitly via Proxy objects, to guard all attribute access automatically or explicitly to check a given access for an operation.

Checker construction expects two functions or dictionaries, one is used to map attribute names to permissions for attribute access and another to do the same for setting attributes.

We use the following checker factory function:

def PermissionMapChecker(permissions_map={},
                         setattr_permission_func=NoSetAttr):
    res = {}
    for k,v in permissions_map.items():
        for iv in v:
            res[iv]=k
    return checker.Checker(res.get, setattr_permission_func)

time_service_checker = PermissionMapChecker(
                               # permission : [methods]
                               {'AccessTimeService':['getTime']}
                               )

with the NoSetAttr function defined as a lambda which always return the permission NotAllowed.

To bind the checkers to the simulation classes we register our checkers with the security model's global checker registry:

import sandbox_simulation
from zope.security.checker import defineChecker
defineChecker(sandbox_simulation.TimeService, time_service_checker)

Defining a Security Policy

We implement our security policy such that it checks the current agent's authentication token against the given permission in the home of the object being accessed:

class SimulationSecurityPolicy:

    implements(ISecurityPolicy)

    createInteraction = staticmethod(simpleinteraction.createInteraction)

    def checkPermission(self, permission, object, interaction):

        home = object.getHome()
        db = getattr(SimulationSecurityDatabase, home.getId(), None)

        if db is None:
            return False

        allowed = db.get('any', ())
        if permission in allowed or ALL in allowed:
            return True

        if interaction is None:
            return False
        if not interaction.participations:
            return False
        for participation in interaction.participations:
            token = participation.principal.getAuthenticationToken()
            allowed = db.get(token, ())
            if permission not in allowed:
                return False

        return True

There are no specific requirements for the interaction class, so we can just use zope.security.simpleinteraction.Interaction.

Since an interaction can have more than one principal, we check that all of them are given the necessary permission. This is not really necessary since we only create interactions with a single active principal.

There is some additional code present to allow for shortcuts in defining the permission database when defining permissions for all auth groups and all permissions.

Integration

At this point we have implemented our security model, and we need to integrate it with our simulation model. We do so in three separate steps.

First we make it such that agents only access homes that are wrapped in a security proxy. By doing this all access to homes and services (proxies have proxied return values for their methods) is implicitly guarded by our security policy.

The second step is that we want to associate the active agent with the security context so the security policy will know which agent's authentication token to validate against.

The third step is to set our security policy as the default policy for the Zope security framework. It is possible to create custom security policies at a finer grained than global, but such is left as an exercise for the reader.

Interaction Access

The default implementation of the interaction management interfaces defines interactions on a per thread basis with a function for an accessor. This model is not appropriate for all systems, as it restricts one to a single active interaction per thread at any given moment. Reimplementing the interaction access methods though is easily doable and is noted here for completeness.

Perspectives

It's important to keep in mind that there is a lot more that is possible using the security framework than what's been presented here. All of the interactions are interface based, such that if you need to re-implement the semantics to suite your application a new implementation of the interface will be sufficient. Additional possibilities range from restricted interpreters and dynamic loading of untrusted code to non Zope web application security systems. Insert imagination here ;-).

Zope Perspective

A Zope3 programmer will never commonly need to interact with the low level security framework. Zope3 defines a second security package over top the low level framework and authentication sources and checkers are handled via zcml registration. Still those developing Zope3 will hopefully find this useful as an introduction into the underpinnings of the security framework.

Code

The complete code for this example is available.

  • sandbox.py - the agent framework
  • sandbox_security.py - the security implementation and binding to the agent framework.

Authors

  • Kapil Thangavelu <hazmat at objectrealms.net>
  • Guido Wesdorp <guido at infrae.com>
  • Marius Gedminas <marius at pov.lt>