Cloud IAM Policies: Spotting Wildcards That Grant Too Much

Cloud systems do not run on trust; they run on policies. An identity and access management policy, usually called an IAM policy, is a document that states which identities, such as users, roles or services, are allowed to perform which actions on which resources, and under which conditions. When a service tries to do something, the cloud checks the applicable policies and allows the action only if a policy permits it. A policy that is too broad therefore does not merely look untidy; it actively permits actions that nobody intended, and an attacker or a mistake that gains access to that identity inherits the full breadth of the policy. The Cloud IAM Policy Analyzer reads a policy that you paste in and flags risky wildcards, which are the most common source of excessive breadth.

How it works

A policy is built from statements, and each statement has an effect, usually Allow or Deny, a list of actions, a list of resources, and optionally conditions. Actions name operations, such as reading a storage object or starting a server, and resources name the things those operations apply to, such as a particular storage bucket or a particular database. A wildcard, written as an asterisk, stands for many values at once: an action wildcard such as service:* permits every action in that service, and a resource wildcard of * permits the action on every resource of that type. A wildcard is not always wrong; a read-only policy that lists every object in one specific bucket may legitimately use a wildcard for the objects inside that bucket. The risk depends on how much the wildcard expands, and on what the rest of the statement already permits.

Where it goes wrong

The most dangerous combinations are easy to name. An action wildcard combined with a resource wildcard permits everything on everything, which is effectively administrative access regardless of the policy's title. An action wildcard on a sensitive service, such as identity management itself, permits creating users, changing policies or granting access, which can turn a small compromise into a total one. A resource wildcard on a sensitive resource type, such as secrets or encryption keys, permits reading material that should be restricted to a handful of identities. Conditions can narrow a statement, for example by requiring a request to come from a particular network, but a condition does not rescue a statement whose actions and resources are already far too broad, because conditions are only checked when they are present and correctly written.

Worked example

Worked example with sample values. Suppose you paste a sample policy containing 5 statements. The analyzer flags 2 of them: one uses an action wildcard on a sensitive service, and one uses a resource wildcard of * on a broad resource type. The flagged rate is 2 divided by 5, which equals 0.40, or 40 percent of the statements. The unflagged statements number 5 minus 2, which equals 3. If the first flagged statement is narrowed from service:* to the 2 specific actions the task actually needs, and the second is narrowed from * to 1 named resource, the flagged count falls from 2 to 0, a reduction of 2, which is a complete clearance of the flagged items in this sample. The sample policy here is illustrative, and the analyzer's findings are pattern-based flags, not a proof that a policy is secure or insecure.

Mistakes to avoid

The principle that guides fixing is least privilege: grant only the permissions a task actually needs, and no more. In practice that means listing specific actions rather than wildcards, naming specific resources rather than all resources, and adding conditions only as a supplement to narrow scoping, not as a substitute for it. Least privilege is harder to write than a wildcard, because it requires knowing what a task actually does, which sometimes means observing a service's real behaviour before finalising its policy. That effort is worth it, because a narrow policy limits the damage from a compromised credential, a buggy deployment or a mistaken command, while a broad policy amplifies all three.

Putting it into practice

Use the analyzer as a review step, not as a final verdict. Paste the policy, read each flagged wildcard, and ask whether the breadth is deliberate and justified or merely convenient. Narrow what can be narrowed, document any wildcard that must remain and why, and re-analyse after changes. Remember that the analyzer reads pasted text: it cannot see policies attached elsewhere, inherited permissions, or the actual behaviour of a service, so a clean report means no risky wildcards were found in that text, not that the identity is safe. Pair the analysis with a review of who holds the identity and what could happen if it were misused, and the policy becomes a real control rather than a document.

Related tools and reading: the Password Generator and the JSON Studio cover neighbouring checks that pair naturally with this one, and the guide at [/blog/security-check-before-handover-client-site/] extends the same topic with further background and examples for readers who want to go deeper.

Key points

• Actions listed specifically instead of service-wide wildcards
• Resources named specifically instead of a bare asterisk
• Sensitive services and secrets given the narrowest scope
• Remaining wildcards documented with a reason
• Policy re-analysed after every narrowing change

In short: An IAM policy states who may do what, to which resources. The analyzer flags risky wildcards in a pasted policy. A wildcard on actions or resources widens access greatly. Least privilege means granting only what a task needs.

One habit ties all of this together: re-check after every change. A result from the Cloud IAM Policy Analyzer is only as current as the text it was run on, so a fix, a redesign, or a new version of the underlying material deserves a fresh run rather than reliance on an old report. Keep the previous result alongside the new one, note what changed between them, and treat any new finding as a question to investigate rather than a verdict to accept or dismiss. That loop of checking, fixing, re-checking and recording is what turns a one-off test into a reliable routine, and it costs far less time than debugging a problem that a second check would have caught early.