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you could probably buy it as part of BeyondCorp https://cloud.google.com/beyondcorp
Tell me where I can buy it then. Because it’s not listed there. And the approach the paper describes requires tight integration between applications and a security provider, which I don’t think exists yet.
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not sure if you made the app or not - I like it a lot, only feedback is it should be a bit more intuitive on how to start the slides, I couldn't figure it out and old ppl like me don't always know
Press the arrow key.
""" Beyond Zero shifts the trust boundary from the application to the action being performed on a piece of data in realtime—and from after-the-fact investigation to in-the-moment evaluation and containment. It augments BeyondCorp’s foundational identity with a “brain” capable of reasoning about the context and intent of a specific request in realtime. """ Doesn't this simply shift the attack vector? Compromising this…
zero trust helped a lot because it forced vendors to stop relying on people magically doing the right thing ina centralized system. it decentralized boundaries.
this paper just says you still need deterministic boundaries and access control, not just have an llm say safe or unsafe. cool thanks google haha.
ps: hi guys, i know yall reading. sometimes its not the concept, its the implementation. else active shield or whatever would have worked too. not everyone can be the T7-9 thinker if implementing is seen as "for peasants"
Am I undertanding this correctly? The idea is to have ultimately an AI decide if I can have access to a resource based on dynamic inference, identity , intent and service signals that can easily be manipulated? Unless I gravely misunderstood the text, this seems like a terrible idea (fancy non-scifi, but still terrible)
This would be paired with deterministic controls. So you have, for example, "engineers can only read from the database, and only after they've perform a 2FA" but then there's context like "why is this engineer reading from the payments table when their IP is in a weird location and they're supposed to be on PTO?" and perhaps that's something a model decides. It's possible to turn that second thing into a sort of "ris…
This reads to me to be more for continuous behavioral monitoring once the access is gained via the deterministic controls. You wouldn't leave "Can person X access resource Y" up to the AI model, that's already decided based on the existing rules. Where the model comes in is "Is person X behaving in an expected way while using resource Y." Like, downloading a bunch of data when they've never done that before, might get flagged for either a session revocation, or a human review, or prompt for additional authentication, etc.
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Just to make my point: can I really trust humans to keep up with the required identity data that will give me enough "credibility" so the AI will give me access? Let's say I had a promotion, who changes my title in the system, who changes my responsibilities and my place in the org chart, more importantly, will they do it or is on leave and forgot? those are data points required by the agent to determine if I'm "good…
I think the dynamic risk signals is already an assumed part of the system. The proposal here seems to be shrinking the trust boundary from "can Alice use Google Drive?" to "should this specific read/write/export API call on this specific resource be allowed right now?" So yeah you're right in that it does add more probabilistic randomness just by virtue of changing the boundary of when the permission gate kicks in
In Entra where I work we already check things like "Is this person on a managed device? Is it compliant? Where are they? What MFA methods do they have registered/did they use?" on top of existing RBAC, etc. and its continuously evaluated. Entra watches for leaked passwords, assigns risk scores, etc. and you can make access decisions based on user risk or sign in risk, force password changes, require different MFA methods depending on the resource and the risk level, etc.
"Should this API call on this resource be allowed right now?" is mostly already determined by the above.
Where I see adding AI into the evaluation is to watch for unusual behavior that's not picked up by the deterministic signals. "Alice is trying to download gigs worth of data from the company file share, however she has never done that in the past, and there hasn't been any recent role/job changes" and so the LLM flags it or denies the request, or pushes it for a human approver, etc.
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Non of it really matters if the end product is just going to be ignored because there's zero people who want to be the guard in the panopticon and therefore, it'll still be given to an AI to watch and make it's dumb decisions about how trust worthy you are to do X, Y and Z. Even if the middle is deterministic, if one end is just going to be lazily hooked up to an AI, it's the shitty dystopian future.
That just gave me shivers down my spine of people eventually becoming so lazy that the AI will decide who to fire based on a massive amount of circumstantial data that very likely has tiny cumulative errors that will lead to classifying your best personnel as a bums and liabilities.
What will really happen: You can’t really perform your work, so you are slower than others, so they fire you based on bad performance.
Horrible startup idea: Discrimination as a service, by means of IA without pretending it’s IA.
Am I undertanding this correctly? The idea is to have ultimately an AI decide if I can have access to a resource based on dynamic inference, identity , intent and service signals that can easily be manipulated? Unless I gravely misunderstood the text, this seems like a terrible idea (fancy non-scifi, but still terrible)
This would be paired with deterministic controls. So you have, for example, "engineers can only read from the database, and only after they've perform a 2FA" but then there's context like "why is this engineer reading from the payments table when their IP is in a weird location and they're supposed to be on PTO?" and perhaps that's something a model decides. It's possible to turn that second thing into a sort of "ris…
I can't wait to fill out a form describing why I want to do something I have permission to do but the AutoBureaucrat5000 says no anyway.
Zero trust is deterministic. AI is non-deterministic Non-deterministic access controls is Terrible idea
Deterministic executes fast and you know what it will do. You want to evolve your ground truth, not hope for the best.
That said, there is a role for probabilistic elements in the security model...as bait and signal.
Zero trust is deterministic. AI is non-deterministic Non-deterministic access controls is Terrible idea
I completely agree. I think LLMs may have a role in security posture, specifically flagging/identifying potential threats for human review . But a Zero Trust/Access Controls should be a HARD boundary, not an inconsistent one. The problem we have right now is that there are some legitimately interesting ideas out there for things we could be using LLMs for, but we also have a ton of "I have a hammer, and everything lo…
Sounds like adding the LLM in would be on top of the existing deterministic controls.
Existing controls handle the "Should you be able to access this resource right now?" the LLM handles "Is this user behaving as we expect them to while accessing this resource?"
Oh yeah, a company whose business model is taking everyone’s data and selling it is going to help me secure my data. I guess there’s one born every minute…
This trope is so tiring. There is a massive difference between Google for enterprise customers and Google for consumers. The consumer offering is massively subsidized by ads and will use your data for ad placement, although they still never sell your data because that would hurt their business. The Enterprise offering guarantees you contractually that they never touch your data.