Clarifying the Confused Deputy Problem in Cybersecurity Discussions

The classic deputy trap and why it still matters

Ever wonder why a perfectly secure system suddenly lets a hacker walk through the front door? It’s usually not a broken lock, but a "confused deputy" who has the keys and gets tricked into using them for the wrong person.

This whole thing started back in the day with a simple compiler on a timesharing service. (Time-sharing - Wikipedia) As explained in the Confused deputy problem - Wikipedia entry, a compiler was given access to a billing file called (SYSX)BILL so it could log system stats. But when a regular user—who had zero rights to that billing file—asked the compiler to save "debug info" into that exact same filename, the compiler just did it.

The system didn't check if the user had permission; it only saw that the compiler (the deputy) did. Boom, billing data deleted.

You might think we moved past this, but honestly? It’s arguably worse now with microservices and cloud apis. (Microservices, Where Did It All Go Wrong • Ian Cooper - Reddit) Modern systems are full of these deputies. For example, a payment service might call a database service. If the db service trusts the payment service implicitly, a clever dev might trick the payment api into hitting a db record they shouldn't see.

• Retail & CSRF: This is also why Cross-Site Request Forgery is so dangerous; your browser is the deputy, using your session cookies to "authorize" a buy order you never actually clicked.
• The AI Agent trap: If you give an ai agent access to your email and slack, it becomes a high-level deputy. An attacker could send you an email that "confuses" the agent into forwarding your private slack messages to an external api.

"The "Confused Deputy" is not a history lesson; it's the silent killer in modern microservices... this manifests whenever a privileged service accepts an unvalidated input and acts on it." — Krati Gaur, via LinkedIn.

It’s all about ambient authority. When permissions are just "floating" around a service rather than tied to the specific request, you’re asking for trouble. Next, we'll look at how this plays out with the new kids on the block: ai agents.

How ai agents change the deputy landscape

If you think a compiler overwriting a billing file was bad, wait until you see what happens when we give ai agents the keys to the kingdom. These agents aren't just tools anymore; they're autonomous deputies that can browse the web, talk to your api, and move data between apps without you even clicking a button.

The problem is that we’re basically handing a loaded gun to a deputy who doesn't always know who's pulling the trigger. When we set up these agents, the temptation is to give them broad permissions so they don't get stuck. But that’s exactly how you end up with a massive security hole.

• The Lifecycle Mess: Most teams forget about agent lifecycle management. You create an agent for a project, give it an iam role, and then it just sits there with those permissions forever. This is where SCIM (System for Cross-domain Identity Management) comes in. It's a protocol for automating identity management. You should use scim to "de-provision" or kill off agent access automatically when a project ends, just like you would for an employee who quits.
• The prompt injection Trap: This is the big one. An attacker doesn't need to hack your server; they just need to send a "prompt" that tricks the ai into using its privileged access.
• Identity Boundaries: We need to define exactly what an agent can and cannot do from day one. If it doesn't need to delete records, that permission shouldn't exist in its profile.

Most ai agents today run with their own high-level permissions. When a user asks an agent to "summarize my last three emails," the agent uses its own credentials to hit the email api. It doesn't always check if the user actually has the right to see those specific emails.

As Dileep Pandiya pointed out on LinkedIn, this is a classic confused deputy risk in modern systems where a service handles requests for multiple users but fails to isolate their privileges.

The fundamental reason these ai agents are so vulnerable is because our current security relies on identity-based checks (ACLs) rather than capability-based security. The agent has the "identity" of a trusted worker, so the system just says yes.

Access control lists vs capability based security

So, we’ve been talking about how these deputies get confused, but the real fight is usually between two ways of handling the "keys" to your data: access control lists (acls) and capability-based security. Honestly, most of us grew up on acls because they’re easy to understand—it’s just a list of who is allowed to touch what—but in a world of ai agents and complex apis, they’re starting to fall apart.

The problem with an acl is that it only checks "who" you are, but it's totally blind to the "how" or "why" of a request. It’s like a bouncer at a club who only checks your ID but doesn't care if you're carrying a suitcase full of stolen goods.

• Identity vs. Authority: In traditional enterprise software, your identity (from okta or azure entra) is often siloed away from the actual authority. A service might know you’re "Bob from Accounting," but it doesn't know Bob was tricked into clicking a malicious link.
• Ambient Authority: This is the big one. acls rely on authority that just "hangs around" a process. If a service has access to a billing file, any request it handles might accidentally use that power.

Instead of relying on a list of names, we should look at what security experts call "Capabilities." As Mark Miller (a pioneer in this space) often argues, a capability is both a designation of an object and a shareable right to access that object. It’s like a physical key or a signed url. If you have the key, you have the power, and the key itself defines exactly what it can open.

• No Confusion: Since the permission and the object (like a file or api endpoint) are bundled together, the deputy doesn't have to guess whose authority it’s using. It just uses the token it was handed.
• Least Privilege by Design: Capability systems naturally enforce the principle of least privilege. You don't give the agent "Read All" access; you give it a token that only reads "report_v1.pdf."

A common real-world example is how S3 Pre-signed URLs work. Instead of giving a web server full access to a bucket, you generate a link that only works for one specific file for five minutes. It’s much harder to "confuse" a service when it only has the power you gave it for that one specific second.

Next, we’re gonna look at some classic web and cloud examples like CSRF and SSRF to see this in action.

Real world examples in the modern cloud stack

Ever wonder why your browser sometimes feels like it's working against you? It's because the modern web is basically built on a pile of "deputies" that are constantly being tricked into doing things they shouldn't.

The most common version of this today is Cross-Site Request Forgery (CSRF). Your browser is the ultimate deputy; it holds your session cookies for your bank. If you visit a sketchy site, it can use your browser's "ambient authority" to send a request to your bank—like "transfer $500 to attacker"—and since the browser attaches your cookies automatically, the bank thinks it’s really you.

It’s funny how old bugs keep coming back in new clothes. Take Server-Side Request Forgery (SSRF). An attacker tricks a cloud-based image resizer (the deputy) into fetching data from the internal metadata service (like 169.254.169.254). The cloud provider trusts the resizer, so it hands over the keys to the kingdom.

• Healthcare Scenarios: In a medical portal, a "doctor" deputy might have a broad permission to GetPatientRecord. If the portal doesn't validate that the specific doctor logged in is actually assigned to the patient ID in the request, the portal acts as a confused deputy. An attacker could swap the patient ID in the URL to scrape records they aren't supposed to see.
• Retail: Attackers use CSRF to add items to carts or change shipping addresses by exploiting the fact that the user is already logged in.

Cross-tenant cloud attacks: The ultimate confusion

This mess gets even weirder when we talk about "Cross-Tenant" attacks in the cloud. This is the "boss level" of the confused deputy problem. Imagine you are using a 3rd party cloud service to analyze your AWS logs. You give that service an iam role to read your S3 bucket.

The problem? That 3rd party service is also analyzing logs for 100 other companies. If the service doesn't use an External ID, an attacker (who is also a customer of that service) could give the service your ARN (Amazon Resource Name). The service—acting as the deputy—then uses its permission to access your data and shows it to the attacker.

AWS actually has a whole guide on this because it's such a common way for people to accidentally leak their entire cloud infrastructure. You have to force the deputy to prove which "tenant" it's working for at that exact moment.

Practical solutions for enterprise iam teams

So, you've seen how the deputy gets confused, but how do we actually stop it without breaking everything? In a world where ai agents are basically high-level deputies with keys to your cloud, we need more than just a simple checklist.

The best way to fix this is to stop trusting the deputy's identity blindly. You gotta teach the system to ask: "who actually told you to do this?" In aws, you can use condition keys like aws:SourceArn or aws:SourceAccount. This forces the resource to verify that the request isn't just coming from a privileged service, but from a specific, authorized trigger.

• Explicit Trust Policies: don't just give a service a broad iam role. Use conditions so it only acts when a specific resource—like a specific s3 bucket—is the target.
• Validation at the Edge: your api should check if the original user has the rights, not just the service account.

We also need to treat ai agents like employees. That means they need a lifecycle. As mentioned before, use SCIM to provision and de-provision agent identities. If an agent is only supposed to work on the "Omega Project," its identity should be deleted the second that project is marked finished in your system.

• Standardize Identity: make sure every ai agent has a unique identity in your idp. No shared "Agent_Role" accounts that everyone uses.
• Monitoring for Weirdness: as mentioned earlier by Dileep Pandiya on LinkedIn, you need logging to catch when a deputy acts outside its boundaries. If an agent suddenly starts touching billing files it never touched before, your soc should get a ping.

Honestly, there is no silver bullet here. But by moving away from "ambient authority" and toward a model where every bit of power is tied to a specific, validated context, you make it way harder for attackers to trick your deputies. It's about building a system that's smart enough to say "no" even when the person asking has a badge.