> We employ Large Language Models (currently OpenAI GPT-4)
For IAM, this seems like a disaster waiting to happen. Combining hallucination problems with security settings is not a path I would consider
> We employ Large Language Models (currently OpenAI GPT-4)
For IAM, this seems like a disaster waiting to happen. Combining hallucination problems with security settings is not a path I would consider
My concern is for those who blindly trust LLMs. Security posturing is not the place to be an early adopter of AI tools. You have to understand both IAM and system architecture to know if what the LLM is saying is correct, so where does that leave us?
I think they can be an extra pair of eyes, but not the driver. Still, there is a signal to noise problem that remains, due to the inherent hallucinations.
my policies are definitely too broad, but feels like I should be able to tighten them up without changing code. (just potentially breaking things if I get it wrong and go too tight).
1. The application has to start using credentials for the first time, or consume them a different way. For example, stop consuming an environment variable and rely on a service account.
2. You have to change ops to support new workflows. Often you have to put approval workflows in place because fewer people can do things and you want only the machines touching production
3. You have to change human behaviors and habits (this is the real hard one). I've had to revert changes because the increased security blocked developers and they don't have time to adapt for the next deadline.
4. Getting parity in local development workflows is also challenging. How and where do you match vs except from IAM parity?
5. Should I give the current server access to a particular cloud service/resource or break out that particular function into a lambda and minimize the permissions there? You have to think through the implications of a breach and how/where you want to limit the blast radius.
6. This is probably obvious, but implementing application level controls, like API endpoint permissioning. IAM is not limited to cloud infra
ask questions to deepen your understanding
> ...ping-pong...
It was a scheduling problem rather than a decision problem. The impact radius is always more than you anticipate
I'm not saying don't use them, just use them as an extra pair of eyes, mostly to catch errors rather than to drive and architect
> get it that there is a lot of skepticism because of people hyping LLM's
The skepticism is not from the hype, it's from experiencing LLM output personally. They are fine if the output can be fuzzy, like a blog post or a function signature, not so much if there is a specific and fragile target.
I can justify to management that we have limited time for IAM and something was missed that we can fix / create tests / scans for after an incident. It's harder to explain that we chose a vendor that uses a non deterministic tool that can hallucinate for one of the most core security pieces of the puzzle.
Similarly, LLMs used for SQL generation meant for business analytics is also a critical area where if numbers are wrong, it might lead to a business going bankrupt.
For Prototype, fun exercise, sure go all in.
It'd potentially cost millions more to recover from a GPT-4 disaster.
These would be the "s3:*" and "Resources: *" scoped permissions I assume? I can't imagine users are explicitly typing out permissions, 95% of which are not relevant for the task.
> which creates huge problems
Such as? What is the material impact of a workflow or a user having too many permissions?
> and is a reason for spending millions in security tools
Are you claiming that overscoped IAM permissions alone are responsible for 1M+ security tooling bills in companies? Would you be willing to share information on which tools these are?
Security obviously https://en.wikipedia.org/wiki/Principle_of_least_privilege
How many times have excess permissions "actually" been the problem... versus something like correct permissions with compromised credentials?
By the way, I have no affiliation with slauth.io (just found them today as well). I just think that https://en.wikipedia.org/wiki/Principle_of_least_privilege is something good to follow in critical systems.
A few examples I've seen repeatedly:
* An AWS-hosted container/artifact/CI/CD application has an SSRF vulnerability that can be used to retrieve IAM instance credentials. Because micromanaging permissions is hard, and the application needs to access so much content in S3, spin up/down instances, etc. it has ec2:* and s3:. Unless the organization has created a separate AWS account for this platform specifically, it's probably game over at that point.
An internet-facing MDM solution has a code execution vulnerability. Because the vendor didn't want to document all of the individual permissions it needs, the installation instructions specify that it should run as an account with Domain Admin permissions in AD. That is definitely game over for most organizations, because even systems that don't authenticate against AD are almost always accessed from systems that do.
Micromanaging permissions is hard in a big organization. I saw it done well, years ago, in Active Directory, but it took several FTEs who were personally interested in the topic to set up and manage, and that was a traditional big business IT environment. In a startup-style free-for-all, good luck. I don't have an opinion either way on Slauth specifically, but something that generates IAM policies procedurally seems like a step in the right direction.
If you want to hear about stories of privilege escalation there should be easy to find. I also have some on my own which I might describe in another post but essentially it was the classic - CI/CD pipeline that "thinks" it has access only to QA does a "destroy all servers" in both QA and Production because it also had access to production without knowing anything about it.
"Accidentally destroyed production database on first day of a job"
At my job for example we don't have a separate support team for the ETL work we do so I have a lot of access I don't use unless things are breaking and then I can't wait for the access approval process to get added to database XXX or bucket YYY to diagnose what data has broken our processes.
I wrote some code once to fetch all those preconfigured role permissions and then present them in a more digestible way
My general approach is to spend more time up-front, so when you are in the heat of a problem, you don't have to learn under pressure. I think my beard is graying
Anecdotally I've used copilot to help write a lot of IAM polities in Terraform and the accuracy is basically 100% already.
With an API that has a hidden / predefined prompt, you'll run into hallucinations that are harder or impossible to handle