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v1.1.2 (#85)
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* Added Secrets Manager support. Cleaned up resource-policy handling from command line.

* Adding minimum permissions policy doc.

* implemented edge checks related to SageMaker: CreateTrainingJob and CreateProcessingJob

* added codebuild support

* added ec2 auto scaling support

* update findings writing

Co-authored-by: Erik Steringer <[email protected]>
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ncc-erik-steringer and Erik Steringer authored May 28, 2021
1 parent f047d19 commit 6139b13
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2 changes: 1 addition & 1 deletion principalmapper/__init__.py
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Expand Up @@ -15,4 +15,4 @@
# You should have received a copy of the GNU Affero General Public License
# along with Principal Mapper. If not, see <https://www.gnu.org/licenses/>.

__version__ = '1.1.1'
__version__ = '1.1.2'
10 changes: 8 additions & 2 deletions principalmapper/analysis/find_risks.py
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@@ -1,5 +1,6 @@
"""Python code for identifying risks using a Graph generated by Principal Mapper. The findings are tracked using
dictionary objects with the format:
{
"title": <str>,
"severity": "Low|Medium|High",
Expand Down Expand Up @@ -94,6 +95,10 @@ def gen_privesc_findings(graph: Graph) -> List[Finding]:
description_preamble = 'In AWS, IAM Principals such as IAM Users or IAM Roles have their permissions defined ' \
'using IAM Policies. These policies describe different actions, resources, and ' \
'conditions where the principal can make a given API call to a service.\n\n' \
'Administrative principals can call any action with any resource, as in the ' \
'AdministratorAccess AWS-managed policy. However, some permissions may allow another ' \
'non-administrative principal to gain access to an administrative principal. ' \
'This represents a privilege escalation risk.\n\n' \
'The following principals could escalate privileges:\n\n'

description_body = ''
Expand All @@ -109,7 +114,7 @@ def gen_privesc_findings(graph: Graph) -> List[Finding]:
'IAM {} Can Escalate Privileges'.format('Principals' if len(node_path_list) > 1 else 'Principal'),
'High',
'A lower-privilege IAM User or Role is able to gain administrative privileges. This could lead to the '
'lower-privilege principal being used to compromise the account\'s resources.',
'lower-privilege principal being used to compromise the account and its resources.',
description_preamble + description_body,
'Review the IAM Policies that are applicable to the affected IAM User(s) or Role(s). Either reduce the '
'permissions of the administrative principal(s), or reduce the permissions of the principal(s) that can '
Expand Down Expand Up @@ -419,7 +424,8 @@ def gen_admin_users_without_mfa_finding(graph: Graph) -> List[Finding]:
'create IAM Policies that impose extra restrictions on the permissions of IAM Users ' \
'depending on whether or not they have authenticated with MFA when using the AWS API. ' \
'Any IAM User with administrative privileges should be configured to have an MFA ' \
'device. The following IAM Users with administrative privileges do not have an MFA ' \
'device. \n\n' \
'The following IAM Users with administrative privileges do not have an MFA ' \
'device configured:' \
'\n' \
'\n'
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213 changes: 213 additions & 0 deletions principalmapper/graphing/autoscaling_edges.py
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"""Code to identify if a principal in an AWS account can use access to EC2 Auto Scaling to access other principals."""


# Copyright (c) NCC Group and Erik Steringer 2019. This file is part of Principal Mapper.
#
# Principal Mapper is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# Principal Mapper is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
#
# You should have received a copy of the GNU Affero General Public License
# along with Principal Mapper. If not, see <https://www.gnu.org/licenses/>.

import logging
from typing import Dict, List, Optional

from botocore.exceptions import ClientError

from principalmapper.common import Edge, Node
from principalmapper.graphing.edge_checker import EdgeChecker
from principalmapper.querying import query_interface
from principalmapper.querying.local_policy_simulation import resource_policy_authorization, ResourcePolicyEvalResult
from principalmapper.util import arns, botocore_tools

logger = logging.getLogger(__name__)


class AutoScalingEdgeChecker(EdgeChecker):
"""Class for identifying if EC2 Auto Scaling can be used by IAM principals to gain access to other IAM principals."""

def return_edges(self, nodes: List[Node], region_allow_list: Optional[List[str]] = None,
region_deny_list: Optional[List[str]] = None, scps: Optional[List[List[dict]]] = None) -> List[Edge]:
"""Fulfills expected method return_edges."""

logger.info('Generating Edges based on EC2 Auto Scaling.')

# Gather projects information for each region
autoscaling_clients = []
if self.session is not None:
as_regions = botocore_tools.get_regions_to_search(self.session, 'autoscaling', region_allow_list, region_deny_list)
for region in as_regions:
autoscaling_clients.append(self.session.create_client('autoscaling', region_name=region))

launch_configs = []
for as_client in autoscaling_clients:
logger.debug('Looking at region {}'.format(as_client.meta.region_name))
try:
lc_paginator = as_client.get_paginator('describe_launch_configurations')
for page in lc_paginator.paginate():
if 'LaunchConfigurations' in page:
for launch_config in page['LaunchConfigurations']:
if 'IamInstanceProfile' in launch_config and launch_config['IamInstanceProfile']:
launch_configs.append({
'lc_arn': launch_config['LaunchConfigurationARN'],
'lc_iip': launch_config['IamInstanceProfile']
})

except ClientError as ex:
logger.warning('Unable to search region {} for launch configs. The region may be disabled, or the error may '
'be caused by an authorization issue. Continuing.'.format(as_client.meta.region_name))
logger.debug('Exception details: {}'.format(ex))

result = generate_edges_locally(nodes, scps, launch_configs)

for edge in result:
logger.info("Found new edge: {}".format(edge.describe_edge()))

return result


def generate_edges_locally(nodes: List[Node], scps: Optional[List[List[dict]]] = None, launch_configs: Optional[List[dict]] = None) -> List[Edge]:
"""Generates and returns Edge objects related to EC2 AutoScaling.
It is possible to use this method if you are operating offline (infra-as-code). The `launch_configs` param
should be a list of dictionary objects with the following expected structure:
~~~
{
'lc_arn': <Launch Configurations ARN>,
'lc_iip': <IAM Instance Profile>
}
~~~
All elements are required, but if there is no instance profile then set the field to None.
"""

result = []

# iterate through nodes, setting up the map as well as identifying if the service role is available
role_lc_map = {}
service_role_available = False
for node in nodes:
# this should catch the normal service role + custom ones with the suffix
if ':role/aws-service-role/autoscaling.amazonaws.com/AWSServiceRoleForAutoScaling' in node.arn:
service_role_available = True

if node.instance_profile is not None:
for launch_config in launch_configs:
if launch_config['lc_iip'] in node.instance_profile:
if node in role_lc_map:
role_lc_map[node].append(launch_config['lc_arn'])
else:
role_lc_map[node] = [launch_config['lc_arn']]

for node_destination in nodes:
# check if destination is a user, skip if so
if ':role/' not in node_destination.arn:
continue

# check that the destination role can be assumed by EC2
sim_result = resource_policy_authorization(
'ec2.amazonaws.com',
arns.get_account_id(node_destination.arn),
node_destination.trust_policy,
'sts:AssumeRole',
node_destination.arn,
{},
)

if sim_result != ResourcePolicyEvalResult.SERVICE_MATCH:
continue # EC2 wasn't auth'd to assume the role

for node_source in nodes:
# skip self-access checks
if node_source == node_destination:
continue

# check if source is an admin: if so, it can access destination but this is not tracked via an Edge
if node_source.is_admin:
continue

csr_mfa = False # stash for later ref
if not service_role_available:
create_service_role_auth, csr_mfa = query_interface.local_check_authorization_handling_mfa(
node_source,
'iam:CreateServiceLinkedRole',
'*',
{
'iam:AWSServiceName': 'autoscaling.amazonaws.com'
},
service_control_policy_groups=scps
)
if not create_service_role_auth:
continue # service role can't be used if it doesn't exist or be created

create_auto_scaling_group_auth, casg_mfa = query_interface.local_check_authorization_handling_mfa(
node_source,
'autoscaling:CreateAutoScalingGroup',
'*',
{},
service_control_policy_groups=scps
)
if not create_auto_scaling_group_auth:
continue # can't create an auto-scaling group -> move along

if node_destination in role_lc_map:
if service_role_available:
reason = 'can use the EC2 Auto Scaling service role and an existing Launch Configuration to access'
else:
reason = 'can create the EC2 Auto Scaling service role and an existing Launch Configuration to access'

if csr_mfa or casg_mfa:
reason = '(MFA Required) ' + reason

result.append(Edge(
node_source,
node_destination,
reason,
'EC2 Auto Scaling'
))

create_launch_config_auth, clc_mfa = query_interface.local_check_authorization_handling_mfa(
node_source,
'autoscaling:CreateLaunchConfiguration',
'*',
{},
service_control_policy_groups=scps
)

if not create_launch_config_auth:
continue # we're done here

pass_role_auth, pr_mfa = query_interface.local_check_authorization_handling_mfa(
node_source,
'iam:PassRole',
node_destination.arn,
{
'iam:PassedToService': 'ec2.amazonaws.com'
},
service_control_policy_groups=scps
)

if pass_role_auth:
if service_role_available:
reason = 'can use the EC2 Auto Scaling service role and create a launch configuration to access'
else:
reason = 'can create the EC2 Auto Scaling service role and create a launch configuration to access'
if clc_mfa or pr_mfa:
reason = '(MFA Required) ' + reason

result.append(Edge(
node_source,
node_destination,
reason,
'EC2 Auto Scaling'
))

return result
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