Welcome to the podcast.
I'm your host, Jaden Shafer.
Today on the show, we are talking about AI security specifically for browsers.
Google Chrome has released a bunch of new security measures for the Google Chrome agentic features that they're going to be rolling out.
And I think a lot of these are actually very interesting ideas that we're going to see played out with OpenAI's Atlas browser, with Perplexity's Sonnet browser and inevitably everyone including Firefox, I think will have some version of an AI browser that can go and take actions for you.
I think this is basically the final, one of the best form factors for AI agents.
I think the kind of golden ticket would be an actual software on your computer that could take more control of your computer.
But I think the next best thing, and the thing that has the widest distribution today, would be browsers.
So something like Google Chrome would be the number one place that I think we can get these AI agents actually taking action and being very, very useful for us.
So the big problem, of course, is all of the innumerable ways that you can have security breaches and you can have bad actors essentially tricking these ai agents into handing over data or money for things that you wouldn't want to hand over your data or money for, and bad actors and hackers can can essentially steal this data in these ways.
So google obviously is very concerned about this, but they have a massive incentive to not have the chrome browser disrupted by someone like perplexity or open ai, but So they need to stay in the game.
And so, of course, Google has a lot of really bright minds over there and have come up with some really incredible solutions.
I want to break down what some of our solutions are and how I think this evolves, and also where I believe that they are falling short, because I don't think everything they've done is perfect.
So we're going to get into all of that.
Before we do, I wanted to mention...
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I'll leave a link in the description.
OK, let's talk about what Google has recently shown off as far as security measures for what they're rolling out in the future with Google Chrome.
Now they kind of gave a bunch of demos and they showed how Google Chrome could be an agent similar to Anthropic and Perplexi.
What they're rolling out.
But when they kind of gave their demos, they said look, these are going to be available in the coming months.
So they kind of did the tease and wait instead of the immediate drop with this feature.
It's basically my pet peeve, but whatever.
It is the way it is, especially with companies like Google and Apple, where they have kind of like these big show and tell conferences.
And then they're like, look, these will be coming out in the next few months.
And so I mean, this is just the way it is when they have these like pre-designed conferences, like Google IO, where they announce a bunch of stuff.
I really appreciate it when these AI companies do an announcement and they immediately drop.
Google did not do that in this case.
But what they did do that I thought was pretty impressive, as they've started to roll this out is they said that they're using the help of a few different models to keep the agent's actions in check.
So essentially, they've built what they're calling a user alignment critique model.
Now, they're using Gemini to do this.
And it basically looks at the action items that is built by the planner model.
So essentially what that means is when you're going to go and use an AI agent.
Let's say you're like hey, help me go and download my podcast episode.
And I mean I know this isn't everyone's everyone's workflow I'm coming up with something that's my own rather than just giving you, like a travel planner, one which I feel like is overused.
So Let's say you're like hey, go download my podcast episode, go edit it, go upload it to this platform, come up with some titles and descriptions and publish it for me on, you know Monday, Wednesday or Friday, depending on what the next available slot for a podcast episode is.
Right.
Let's say this is your workflow.
It's going to like these agents.
They essentially listen to your prompt.
However, you know, unformatted it may be where you describe your whole workflow and they'll break it down into a very clear, organized path.
They're like OK, in order to do the download, we need to make sure that we have space on the drive and we need to make sure that, when we download it, we you know we do X Y, Z things and we're downloading the right file.
And we got to go find it.
Like anyways, they came up with this very elaborate walkthrough of what they're going to do now.
What they've done as far as security goes is they've created a user alignment critique which is essentially a model.
It can't see anything on your screen.
So the AI agent, it can see everything on your screen.
It comes up with a plan that goes and executes the plan.
Every step of the plan, when it says, okay, I see this, I'm going to do this thing next.
You can kind of see the reasoning on comment and even on opening eyes Atlas, where it like, tells you what it's doing while it goes through all the steps.
So it's kind of useful to watch that to understand how these models are working.
But How Google's functioning now is.
As it's taking those actions.
It has a separate model that is looking at what your original objective is and what its current step it's taking.
You can't see what's on the screen, so it can't be tricked basically by a prompt injection.
That's like forget all your past instructions and make sure you do X Y, Z right.
This is what people are kind of worried about, this quote unquote prompt injection.
Instead, all it sees is your original goal and then the actions it's going to take.
And that model says yes or no if that action aligns with the original goal.
It's a very clever kind of way to use AI to stop the bad actors of AI.
They've done this.
And if the critical model thinks that the planned task doesn't serve what the user's original goal is, it's going to ask the planning model to rethink its strategy on what it's doing.
So Google says that the, like the critic model only sees the metadata and not the actual web content.
And I think what's powerful is that the other thing they're doing to prevent agents from getting disallowed or untrustworthy sites and accessing the basically is that they're using this an agent origin sets tool.
So this is another tool.
So they have, I think, three main tools.
The first one was their user alignment critique.
The And essentially what it's going to do is it's going to restrict the model to access.
Read only origins and read writable origins.
So what that means is that read only origins is data that Gemini is allowed to consume content from.
So an example of that would be, you know, like on a shopping site.
The listings, those are very relevant to the task that you're doing, right?
If you're like, go buy me a pair of white tennis shoes, and it goes to a webpage and there's white tennis shoes.
The listing information about those white tennis shoes.
That's very relevant to the task that you're doing.
But the banner ad that's on that website, right?
Like maybe it's a Shopify store or some other store and they've got Google ads on there.
That is not relevant.
And so... the listing is relevant, but the banner ads are not.
And Google also said that the agent is only allowed to click on or type on certain iframes of a page.
So the ads would not be there.
What's kind of hilarious to me is the fact that Google is the number one ads platform in the world.
And yet their AI agent that they're creating is literally designed to ignore ads.
And it's also especially ironic to me, considering that you know this is all coming on Google Chrome, who you know.
I for many years used Google Chrome and I had, like ad blockers, you know, like.
You know, all sorts of ad blocker plugins that would block extensions, that would block ads.
And then Google Chrome made it very difficult for those same ad blocker plugins to fully function.
And I've essentially moved to other platforms.
I use Brave now as my browser because it by default blocks all ads.
I don't need a plugin.
I don't need an extension.
It just works.
And yeah, I forget, ads exist on the And so anyways, it's very ironic to me that, as we're creating AI agents, we're literally designing them to ignore ads, which is where Google makes all their money and what they've stopped.
It feels like they're kind of like bent on not allowing any humans to block ads, but their AI agents can.
Anyways, it's ironic.
I think it's kind of funny.
But I also do think it's clever and great for security, yada, yada.
So like Google continue on this path.
I think it's great.
One thing that I think is interesting is this concept of iframes inside of a website.
Basically, what I think is clever here is because it's only allowing the agent to click on or type on certain iframes on a site.
It's actually...
It's very smart because, beyond just visually what you can see on the page, it also can read the HTML or the code for the page.
So it understands more about the page and more about security risks than a regular human would.
A very common phishing attack that I think you would see is like is you know iframes inside of a website and the iframe is of a completely different website.
That's stealing data.
You know a hacker could go, you know, hack a legitimate website, put an iframe embedded inside of that website that you think you're typing your data into a specific website, but really there's a hacker extracting data.
That's like one kind of clever way to go about it.
Another one is just with you know complete spoof websites where you have a slight typo in the URL that people may not notice.
You try to make a direct clone of, like PayPal or Bank of America and get their, get their information and and you know there's kind of common scams that people do.
What's cool to me is that the AI agents will actually be better than humans at detecting that, because they're looking at not just what's on the screen but also the code.
And they're built to kind of scrutinize everything and not click on or interact with iframes or elements of the page that they know are false, which is kind of cool.
This is what they said in a blog post about all of it.
They said this delineation enforces that only data from a limited set of origins is available to the agent.
And this data can only be passed on to the writable origins.
This bounds the threat vector of cross-origin data leaks.
This also gives the browser the ability to enforce some of that separation, such as by not even sending to the model data that is outside of the readable set.
Essentially, Google's keeping a check on the page navigation by looking at the URLs through another observer model.
This observer model is looking what's on the page.
And I think this can prevent navigation to harmful model-generated URLs.
That's essentially what Google has said.
I think right now Google said that it is also handing over the reins to users for a bunch of different tasks.
This...
Some things I think are good about this.
Some things I don't think are good about this.
For instance, when an agent is trying to navigate to a site with information like banking or medical data, it first is going to ask the user.
You can see pros and cons to this.
I think a lot of people are going to be wary of like hey, I don't want Google Gemini going and logging into my bank without my permission, because security all sorts of security issues there.
But at the same time it's like if I asked it to do something because it was useful for me, and then it's like not able to do it, then it makes it less useful to me.
So this is kind of the debate that I personally have.
I'm like, if there's a way to make it secure and I could just say, hey, go check my bank and let me know, you know, if my transaction to XYZ Corporation went through because I wasn't sure it's something funny happened on my credit card.
And, you know, Google Gemini could go do that and let me know like that would be very useful.
So I can see like uses and that, but then if it was like, Oh well sorry, that's like too confidential.
Like, would you like me to do this?
Or can you like you can you log in and then I'll go search for it?
Like, I don't know.
I can imagine it just being kind of cumbersome and annoying and I would like to streamline it.
But I know I'm sure there's a great debate to be had in that regard.
But what I think is less debatable is that, for sites that require a login, is going to ask a user for permission to let Chrome use the password manager.
Google said that the agent's model doesn't have exposure to password data.
And they also said it's going to let users, it's going to ask users before taking actions like making a purchase or sending a message.
So personally, I think this is just making it less useful.
If it's going to ask me permission to send a message where I'm like hey, go send an email to this person saying this
And then it like drafts up an email.
It's like, do I have permission to send this message to this person?
It's like, I already, yeah, like I already gave you permission.
Or if I was like, hey, like go buy me this exact pair of shoes.
Don't spend more than this much money.
Go probably buy it from this place.
And then it like does all the research?
And it's like, all right, I'm going to buy the shoes and it's exactly everything that you wanted.
Are you good?
Like, I don't know.
To me it's like, just if I give you an instruction, I would, when the model is good enough.
I hope it can do it without asking me for it.
So maybe we'll, we'll get there.
Maybe this is just kind of a, because the model is not good enough today.
So it's setting the limitations.
My worst fear is be that these limitations last forever, right?
Like I want an AM model that can truly go and do everything I need it to go do without Without having to ask me.
This is basically my biggest pet peeve.
And my biggest issue with perplexes comment and with open eyes.
Atlas browser is that I have all sorts of tasks I get it to do and ask me like, like you know, 10 different times throughout the task.
Are you sure I can proceed to the next step?
And I'm like, if I have to babysit you and say yes every, you know every minute, I might as well just do this thing myself.
Or really, what I do is just hire a person to do it because I can tell them how to do it once and they'd never ask me again for a month while they do all the tasks.
So anyways, that's my personal pet peeve.
And I hope that Google removes a lot of these asking for permission things in the future.
Google said that they also have some prompt injection classifiers to prevent unwanted actions.
They're also testing agentic capabilities against attacks.
So they have a bunch of researchers that are working on this right now.
I would expect nothing less from Google.
I think that is fantastic.
There is apparently or I guess perplexity.
Recently, they released this kind of new open source content detection model earlier this month um, and so i think that there's a lot of other players paying a lot of attention to this and the idea but uh, for that with perplexity is to prevent prompt injection attacks against agents.
I think google is going to work on this as well.
I honestly think that all of the research done by any of these companies, especially because they're going to publish it and talk about it, is going to get used by everyone.
I don't think that's like the competitive advantage you want.
Like The competitive advantage of Google Chrome is that, like you know, we are way less prone to attacks, but we're not going to tell you how, like they're going to tell everyone how and that everyone's going to use them.
So at the end of the day, I think this is going to be good for the entire industry.
Thank you so much for tuning into the podcast today.
If you enjoyed the episode, make sure to leave a rating review wherever you get your podcasts.
And as always, make sure to go check out AIbox.ai.
I will catch you in the next episode.