Mastering Wildcards in IAM Policy: A Practical Guide to AWS IAM Policy Wildcards

Wildcards are a powerful feature in IAM policies, enabling flexible permission patterns across resources and actions. However, with great power comes great responsibility. A single wildcard in the wrong place can open doors you never intended to open, or lock out legitimate users when misapplied. This article dives into the concept of an IAM policy wildcard, how it works in practice, and how to apply it safely to achieve the balance between usability and security in AWS IAM policy design.

Understanding the concept of an IAM policy wildcard

An IAM policy wildcard is a character or pattern that matches multiple strings, actions, or ARNs (Amazon Resource Names) in policy statements. In the AWS IAM language, wildcards are most commonly represented by the asterisk character (*) and are used to denote “all” or a broad set of matches. For example, an action such as s3:* matches every S3 action, while an ARN like arn:aws:s3:::my-bucket/* matches all objects within that bucket.

It is essential to distinguish between the wildcard usage inside the Action, Resource, and Condition sections of a policy. Each field has its own implications and safety considerations. The presence of a wildcard in an Action can grant broad capability across a service, whereas a wildcard in a Resource often broadens access to multiple resources. The combination of both yields the most powerful (and potentially dangerous) access patterns in an IAM policy wildcard scenario.

Where wildcards are typically used

In practice, the most common uses of a wildcard in an IAM policy include the following:

• Action-level wildcards: Granting broad permissions for a service by using patterns like ec2:* or s3:List*. This should be avoided in production unless there is a compelling, narrow-bound use case.
• Resource-level wildcards: Allowing access to all resources within a scope, such as arn:aws:s3:::my-bucket/* to address all objects in a bucket. When possible, you should replace this with more specific ARNs or resource-based boundaries to minimize risk.
• Combination wildcards: Using symbols in both Action and Resource to craft concise, readable policies. However, you must ensure that the resulting permissions do not grant excessive access beyond the intended scope.

Understanding these patterns helps you design an AWS IAM policy that remains secure while providing the necessary functionality for applications and teams.

Best practices for using an IAM policy wildcard

To minimize risk, approach the IAM policy wildcard with a principle of least privilege and a clear testing strategy. Here are practical guidelines that work well in most environments:

• Avoid broad action wildcards: Refrain from granting * actions. Instead, enumerate specific actions needed. If multiple actions are required, consider grouping them under a narrow prefix (for example, s3:GetObject and s3:PutObject) rather than s3:*.
• Limit resource wildcards: Prefer explicit ARNs or narrow resource patterns. If you must use a wildcard, apply it to object-level resources (e.g., arn:aws:s3:::my-bucket/*) instead of broad service-wide resources.
• Use conditions to refine access: StringEquals, StringLike, and other condition operators can help constrain access further even when wildcards exist in actions or resources. Example conditions can enforce MFA, time-based constraints, or IP address ranges.
• Employ explicit denies for dangerous cases: If a user or role should be blocked from certain operations, explicit Deny statements can help counteract any implicit Allow that arises from wildcards.
• Split policies for clarity: Rather than one massive policy with multiple wildcards, divide permissions into smaller policies tied to job roles. This makes auditing, debugging, and updates easier.
• Test with policy simulators: Before deploying, use the IAM Policy Simulator and Access Analyzer to verify that the wildcarded policies grant exactly what you expect, and nothing more.

Examples: safely using wildcards in IAM policy

Here are representative examples illustrating how to apply an IAM policy wildcard responsibly. These samples show common patterns and how to avoid overly permissive access.

Scoped action and resource example

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Action": [
        "s3:GetObject",
        "s3:PutObject"
      ],
      "Resource": [
        "arn:aws:s3:::my-secure-bucket/*"
      ],
      "Condition": {
        "Bool": {
          "aws:SecureTransport": "true"
        }
      }
    }
  ]
}

In this example, wildcards are not used for actions or resources; instead, the policy explicitly lists a couple of necessary actions and applies a resource bound to a specific bucket. The condition enforces secure transport, which is a practical safeguard against unencrypted access. This pattern demonstrates how the right use of an IAM policy wildcard is not always required to achieve effective security; explicit permissions with minimal scope often provide clearer security guarantees.

Controlled wildcard in resources

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Action": [
        "s3:GetObject"
      ],
      "Resource": [
        "arn:aws:s3:::my-bucket-logs/*"
      ]
    }
  ]
}

Here, the wildcard appears within the resource ARN to cover all objects in a designated logs bucket, while keeping the action narrow. This approach illustrates how a targeted wildcard in an IAM policy can be acceptable when the resource scope aligns with a known dataset or a controlled folder structure.

Testing, auditing, and governance

Testing is crucial when working with an IAM policy wildcard. The IAM Policy Simulator lets you validate whether a given user, group, or role has the intended permissions. Regularly auditing policies with AWS IAM Access Analyzer helps identify over-permissive statements and potential risks introduced by wildcards. Governance processes, including change management and peer reviews, also reduce the chance of inadvertently broadening access during policy updates.

For teams managing multiple accounts or complex environments, a centralized policy library with templated wildcard patterns can simplify compliance. It’s helpful to document the rationale for any wildcard usage, including the exact business need and the risk assessment justification. This transparency supports ongoing security reviews and audits.

Common pitfalls and how to avoid them

• Overusing wildcards in Action: Avoid blanket permissions like s3:* unless every action in that service is truly required for the role.
• Broad Resource wildcards: Refrain from granting access to all resources across a service (e.g., arn:aws:s3:::*) unless the use case is extremely narrow and well-justified.
• Assuming implicit denials are in effect: If a policy contains wildcards, verify that there are no conflicting denies that could override Allow statements in unexpected ways.
• Neglecting conditions: A wildcard without constraints can be dangerous. Always consider adding conditions to add precision.

Putting it all together

Mastering the use of an IAM policy wildcard requires a balance between operational agility and robust security. By reserving broad wildcards for well-justified, auditable cases and leaning on explicit actions and resources with strategic conditions, you can design policy language that remains readable, maintainable, and secure. The goal is to preserve the least privilege principle while enabling legitimate automation and collaboration across teams. In practice, this means reviewing every wildcarded entry, testing thoroughly, and documenting decisions for future audits.

Conclusion

Wildcards in IAM policy are a double-edged sword. They can simplify permission management but also expand risk if misapplied. A thoughtful approach to the IAM policy wildcard—prioritizing explicit actions and narrowly scoped resources, complemented by conditions and robust testing—helps you achieve a secure, scalable permission model. By following best practices, leveraging policy simulators, and maintaining clear governance, you can harness the flexibility of an IAM policy wildcard without compromising security or compliance.