Analyzing Risk for IAM PassRole

Tue, 12 May 2026 12:00:00 +0000

The AWS iam:PassRole permission is one of the most foundational permissions in all IAM. It grants a principal the ability to assign roles to services. Unlike other privileged IAM permissions, which tend to allow for direct escalation paths, PassRole abuse is more nuanced and therefore it’s harder to assess the impact of PassRole assignments for principals. In this post, we will explore different methods of assessing risks associated with PassRole.

Overview

PassRole is an IAM permission only, not an action. You can assign it to a principal, but there is no corresponding API call. Instead, each service implements an action that in some way passes a role to the service/resource. For example, if you create a new Lambda Function, you are required to set an execution role. The CreateFunction call will check that the calling principal has the PassRole permission (also applies to similar actions like UpdateFunctionConfiguration).

Abuse

The risk of PassRole is hard to evaluate due to the complexity of an attack. The requirements for abuse are:

The compromised principal must have both the PassRole permission and the service-specific permission (ex: CreateFunction for Lambda).
- Also note: there is no official AWS documentation on which API actions also require PassRole. Developers must determine this on their own. The closest official resource is the list of services that integrate with IAM found here. Tenable also has a great post describing this issue here.
The attacker must be able to influence the service/resource that receives the role. This is the biggest difference as compared to direct privilege escalation permissions and is highly service specific.

As an example, we will use Lambda Function creation. The attacker will be operating from Role A, which has PassRole and CreateFunction permissions. The role they intend to pass is Role B and has administrator permissions (unconditional * on *). The attack steps are:

Attacker prepares the Lambda Function code in a way that allows them to achieve their desired goal. For example, by having the code assign them an administrator policy or by creating a new administrator role they can assume.
Attacker calls CreateFunction from Role A and specifies Role B as the new Function’s execution role
Attacker invokes the newly created Function
Lambda invokes the Attacker’s code and performs AWS actions using Role B, the administrator role

Defense

There are two primary ways to restrict PassRole in an IAM policy. The first is by using a Resource key to restrict the roles that can be passed.

JSON Restricting PassRole via a Resource


{
	"Version": "2012-10-17",
	"Statement": [
		{
			"Sid": "1",
			"Effect": "Allow",
			"Action": "iam:PassRole",
			"Resource": "arn:aws:iam::123456789000:role/RoleA"
		}
	]
}

The second is by using one or more PassRole-specific IAM conditions, namely iam:PassedToService and iam:AssociatedResourceARN.

JSON Restricting PassRole via iam:PassedToService


{
	"Version": "2012-10-17",
	"Statement": [
		{
			"Sid": "1",
			"Effect": "Allow",
			"Action": "iam:PassRole",
			"Resource": "arn:aws:iam::123456789000:role/RoleA",
			"Condition": {
				"StringEquals": {
					"iam:PassedToService": "lambda.amazonaws.com"
				}
			}
		}
	]
}

JSON Restricting PassRole via iam:AssociatedResourceARN


{
	"Version": "2012-10-17",
	"Statement": [
		{
			"Sid": "1",
			"Effect": "Allow",
			"Action": "iam:PassRole",
			"Resource": "arn:aws:iam::123456789000:role/RoleA",
			"Condition": {
				"StringEquals": {
					"iam:AssociatedResourceARN": "arn:aws:lambda:us-east-1:123456789000:function:FunctionA"
				}
			}
		}
	]
}

The iam:PassedToService condition specifies which services can receive the role(s) whereas iam:AssociatedResourceARN specifies which resource can receive the role(s).

Evaluating Risk

To evaluate the risks associated with principals assigned PassRole, we need to understand both the outbound access that principal has as well as inbound access to that principal (e.g., a role that is assumable and has PassRole permissions). For this analysis, we will describe it schematically then demonstrate how to perform it using Neph.

For outbound access, we will focus on unconditional PassRole permissions as these represent the riskiest scenarios. Unconditional here means that there are no restrictions on the roles that can be passed nor on the services that can receive the roles. Schematically:

Identify all principals in an account
Retrieve their inline and attached policies
Expand policy wildcards then look for statements that allow PassRole
Filter those statements for ones without the IAM restrictions noted above
Validate that the effective permission set for the principal actually allows PassRole (e.g., there may be both an allow and a deny for PassRole across identity policies, permission boundaries, SCPs, etc).
(Optionally) Validate that the effective permission set allows the service-specific action

For inbound access, we will analyze trust policies for roles that have PassRole permissions to identify principals that can access those roles from both within the same account as well as from external accounts. Schematically:

For any role that has PassRole, analyze the trust policy for references to allowed principals, both explicit and wildcards
For each identified principal, validate that that principal can call AssumeRole against the target role with PassRole permissions

Note: you can also look for alternative mechanisms to access roles with PassRole permissions, such as if another abusable permission would allow for access to that role. For example, if you have a role that can call UpdateAssumeRolePolicy on the target role, you can update its trust policy to allow your role access.

Practical Analysis

For this analysis we will use Neph (release blog here), our open-source graph-based AWS security tool. For the more involved parts of the analysis, we will use the Jupyter Lab server included in the default Docker Compose deployment.

Neph relates both inline and attached policies to principals via an ATTACHED path:

ATTACHED path between two nodes

Policy nodes are enriched to include details about abusable permissions. This data is exposed via the iam_privesc and iam_privesc_permission node properties.

Since Neph considers PassRole an abusable permission, it will be included in these properties, making principal identification straightforward.

Privilege escalation node attributes on a policy node (also applies to inline policy nodes)

To filter these results for unconditional results, you can use a small code snippet to walk the policy statements and check for Resource and condition restrictions. The below snippet is a minimal example:

python Statement walking


import json
import copy
from neph.nodes import record_to_stub
from neph.aws.policies import get_allowed_actions_from_policy

results = session.run("""<QUERY>""").values()
for result in results:
    policy = record_to_stub(result[0], include_fakes=True)
    policy_dict = json.loads(policy.policy)
    statements = policy_dict.get("Statement", []) 
    
    for statement in statements:
        dummy_policy = copy.copy(policy_dict)
        dummy_policy["Statement"] = [statement]
        if "iam:PassRole" in get_allowed_actions_from_policy(dummy_policy):            
            if "Condition" not in statement:
                # logic here

Given a query returning policy nodes, this will load the results into a Neph node object then deserialize the policy data.
For each statement in the policy, create a full policy containing only that statement (the “dummy”). This is to isolate the positive results by statement.
The permissions in the statement are expanded then checked to see if iam:PassRole is present.

Example output using complete version of above code snippet.
AWSControlTowerExecution is an administrator role with full wildcard permissions.

Then validate that the effective set of policies for the principal does not disallow PassRole by using the Simulator. Note: PassRole is only an IAM permission, not an API call. However, the Neph Simulator will still work in this case.

Simulating PassRole using the Neph Simulator

This is equivalent to the following CLI command:

neph sim --principal "<ROLE ARN>" --action "iam:PassRole" --resource "*"

If you are interested in service-specific role passing actions, such as CreateFunction, you can then also simulate that action in addition to PassRole.

This piece of the analysis provides the set of principals with PassRole. For any roles within that list, it makes sense to also evaluate inbound access by analyzing the trust policies. If you’ve generated leads within Neph, you will already have inbound paths to the roles based on their trust policies. For example, if the trust policies allow assumption using an account-level trust, there will be a path to the role from that account.

Neph represents explicit principal references in trust policies using a CAN_ASSUME lead relationship. A trust policy like:

JSON Trust policy


{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Action": "sts:AssumeRole",
            "Effect": "Allow",
            "Principal": {
                "AWS": "arn:aws:iam::123456789000:role/Role"
            }
        }
    ]
}

Will lead to the creation of a path like:

CAN_ASSUME LEAD path for explicit role trust

CAN_ASSUME LEAD path for account-level trusts

If roles trust entire accounts for assumption, Neph will use the CAN_ASSUME lead as well, but with the source node being an account instead of a role. You will need to expand that to the principals from that account by using the account_id attribute.

Role in account (bottom) that has CAN_ASSUME lead (top)

Additional analysis should then be performed to validate the source node can assume the role by using the Simulator to make an AssumeRole call from the source node to the target that has PassRole permissions.

Simulating AssumeRole using the Neph Simulator

Principals that can assume roles with PassRole represent additional risk as they effectively have the PassRole permission.

Extending Neph

You can leverage Neph’s extensibility to make initial PassRole target identification easier. As noted above, Neph enriches policy nodes that include abusable permissions with additional node attributes. The code responsible for this enrichment can be found here.

Source code for privilege escalation enrichment

The policy contents are checked to see if they contain any of the noted abusable permissions. Policies that do receive additional attributes. Neph also uses these abusable permissions for its privilege escalation fanout (code here).

Both checks can be repurposed to look for additional notable permissions, such as service-specific implementations of role passing operations like CreateFunction, either by looking for those specific permissions in isolation or by looking for them cooccurring with PassRole.

For this example, we will use the node enrichment as a basis for a new enrichment that looks for a combination of PassRole and one or more service-specific implementations, like CreateFunction

python PassRole Enrichment


SERVICE_SPECIFIC_PASSROLE = ["lambda:CreationFunction"]

class PassRoleCombinations(NodeEnrichment):
    nodes = [IamPolicy, IamInlinePolicy, IicInlinePolicy]

    @classmethod
    @add_session()
    def enrich(cls, stub, session: Session = None):
        if hasattr(stub, "policy") and (policy := getattr(stub, "policy")) is not None:
            policy_json = json.loads(policy)
            allowed_actions = get_allowed_actions_from_policy(policy_json)
            has_passrole = "iam:PassRole" in allowed_actions
            service_permissions = list(filter(lambda x: x in allowed_actions, SERVICE_SPECIFIC_PASSROLE))

            if has_passrole and len(service_permissions) > 0:
                parent = stub.get_parent()
                if parent == IamPolicy:
                    match = f"""MATCH (policy:{IamPolicy.label}{{arn: "{stub.arn}"}})"""
                elif parent in [IamInlinePolicy, IicInlinePolicy]:
                    match = f"""MATCH (policy:{IamInlinePolicy.label}|{IicInlinePolicy.label}{{principal_arn: "{stub.principal_arn}", name: "{stub.name}", policy: '{stub.policy}' }})"""
                else:
                    return

                permissions_str = json.dumps(service_permissions)
                query = f"""
                {match}
                SET policy.passrole_combination = "true"
                SET policy.passrole_combination_permissions = '{permissions_str}'
                """
                session.run(query)

This class is largely the same as the one linked above. The main difference is that it checks both for PassRole and the service permissions whereas the original only checks for abusable permissions, which includes PassRole
You can modify the SERVICE_SPECIFIC_PASSROLE list as needed to include additional permissions
This adds the passrole_combination and passrole_combination_permissions node attributes on matched nodes

After installing and running the enrichment (details here), you can query for matches based on the added attributes, passrole_combination and passrole_combination_permissions.

Policy node with new attributes from custom enrichment

Closing

PassRole is a highly privileged permission in AWS that requires a nuanced approach to understanding its risk. Using tools like Neph, you can better understand the inbound and outbound attack paths related to principals with PassRole permissions.

If you have any questions or concerns, feel free to reach out to @2xxeformyshirt. Neph source code can be found here.

Neph on SRA Labs | Cybersecurity Research & Innovation by Security Risk Advisors