Research

What reading the field side by side showed us.

We reviewed 29 primary works on how AI agent access is controlled, read against fifty years of access-control theory. Each paper is solid on its own. Read together, they leave five problems that no single paper states.

In one sentence: current agent-authorization research protects whatever access an agent starts with, cannot express a dangerous combination with a single limit, and measures attacks far better than the cost of stopping them.

Method

How we read the field.

  1. 01
    Select29 primary works on how AI agent access is controlled.
  2. 02
    Verify50 references, each one checked against its source.
  3. 03
    CompareRead side by side, and against access-control theory, for the problems no single paper states.

Finding 01

Narrowing is not least privilege

The evidence

Every delegation scheme we reviewed guarantees that a sub-agent can never hold more than the agent that started it. That is valuable, and it is easy to mistake for least privilege. It is not. Narrowing protects whatever the first agent was given, including everything it never needed. One study measured agents exposed to about fifteen times the tools their task required (Sidik & Rokach). A chain that never widens still carries that excess at every step.

What it changed in StartiQOS

We derive what the task needs first, and make that the starting point narrowing then protects.

Sidik & Rokach arXiv:2604.11839

Finding 02

A single limit cannot express a combination

The evidence

The danger in agent access is often a pair: reading customer records is fine, sending data outside is fine, both in one session is how data leaves. The leading system that checks combinations does so from a list of forbidden pairs, and its safety guarantee holds only "under a complete restriction set" (Muruaga, Bounded Agents). We show that the obvious alternative, one ceiling on the combined effect, cannot work at all: anything that fits under a ceiling alone also fits together. It takes a bound with several corners.

What it changed in StartiQOS

The gateway checks the combined effect of what an agent holds against a bound with several generators, not a list and not a single ceiling.

Muruaga, Bounded Agents arXiv:2608.15888

Finding 03

The field disagrees on whether AI may shape its own permissions

The evidence

Three recent works take incompatible positions without citing each other. One forbids any policy derived from model output, to keep out poisoning (Capability Gates). One lets the model propose short-lived permissions that a fixed checker approves (IntentCap). Others learn policy from observed behaviour, one of them in what it calls a controlled staging phase (AgentGuardian). The third position is the exposed one: an attacker who influences what is observed only needs to be seen, not to succeed.

What it changed in StartiQOS

Learning needs evidence from many independent sessions before a permission enters a policy, and a person approves every policy.

Capability Gates arXiv:2606.28679IntentCap arXiv:2609.14631AgentGuardian arXiv:2601.10440

Finding 04

Attacks are measured far better than the cost of stopping them

The evidence

Defences report attack results in detail and the cost to legitimate work thinly. One widely cited result of zero false denials rests on ten benign cases (Capability Gates). With no failures in ten trials, the true rate could still be as high as 30.8% at 95% confidence. The same work's result on 48 attack attempts bounds its miss rate far more tightly, at 7.4%.

10

benign cases behind “zero false denials”

up to 30.8%

48

attack attempts behind the miss rate

up to 7.4%

Upper bound of the true rate at 95% confidence, with no failures observed.

What it changed in StartiQOS

Shadow mode exists: before anything is blocked, you see exactly what enforcement would have stopped in your own environment.

Capability Gates arXiv:2606.28679

Finding 05

Trust and sensitivity are two different questions

The evidence

Several systems put data on one scale. They are separate: how far to trust an instruction from an untrusted email is an integrity question; how far a customer record may travel is a confidentiality question. Information-flow work for agents keeps the two apart (FIDES), as access-control theory has since the 1970s.

What it changed in StartiQOS

The gateway tracks how much untrusted content a session has read separately from how sensitive its data is, and narrows authority as exposure grows.

FIDES arXiv:2505.23643

References

Works cited on this page.

  1. Sidik & RokacharXiv:2604.11839
  2. Muruaga, Bounded AgentsarXiv:2608.15888
  3. Capability GatesarXiv:2606.28679
  4. IntentCaparXiv:2609.14631
  5. AgentGuardianarXiv:2601.10440
  6. FIDESarXiv:2505.23643
About the review. Shashwat and Tejinder Pal, Department of AIT CSE, Chandigarh University. A systematic review of 29 primary works with 50 references, every one verified. Currently in submission; we will link the published version here. Every finding above is quoted from, or computed from, a cited source.

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