kjok

I should have been clearer and specific: state management is done on the backend, but collecting behavioral biometrics and device fingerprint is done using JavaScript, which can be manipulated.

Adversaries do not have to wait for LLM models to evolve to mimic human process, they can simply evade the detection JavaScript that evaluates similarity. JavaScript is visible, can easily be reverse-engineered.

Please also collect responses from people, you'd find a pattern: a new attack is launched, people make noise, and later go back to installing packages the same way. Enterprises already use private registries to combat such attacks, vulnerable folks include individual devs and small teams.

Compare this to Android where you can run malware and it cannot do anything except for annoying you with notifications.

Are you sure it cannot do anything? Looking through various past malware/exploits, this doesn't seem to be the case.

Why should they be open source?

Cooldown sounds like a good idea ONLY IF these so called security companies can catch these malicious dependencies during the cooldown period. Are they doing this bit or individual researchers find a malware and these companies make headlines?

How difficult is it to build a second startup on the side?

Are you a bot?

Building automated analysis tool that help identify the use of GPL-licensed SDKs in mobile apps, promoting license compliance and supporting sustainable open-source development.

How do you know that they were LLM scrapers? The reason I ask is because user agents could easily be spoofed?

For those who have deployed Cloudflare in front, what are pros and cons? How's the user experience? Do they offer free bot protection?

How are you measuring this? Does your solution rely on user agent or device fingerprinting? Curious to know what tools are available today and how accurate they are.

Thanks for sharing your approach!

It is nothing special. We keep X number of machines in a warm pool.

I'd love to better understand the unit economics here. Specifically, whether cost is a meaningful factor.

The reason I ask is that many startups we've seen focus heavily on optimizing their technology to reduce cold/boot startup times. As you pointed out, perceived latency can also be improved by maintaining a warm pool of VMs.

Given that, I'm trying to determine whether it's more effective to invest in deeper technical optimizations, or to address the cold start problem by keeping a warm pool.

The problem is that those underlying frameworks can very easily be misconfigured.

Agreed. I'm sure a number of these sandboxing solutions are vibe-coded, which makes your concerns regarding misconfigurations even more relevant.

There are dozens of projects like this emerging right now. They all share the same challenge: establishing credibility.

Care to elaborate on the kind of "credibility" to be established here? All these bazillion sandboxing tools use the same underlying frameworks for isolation (e.g., ebpf, landlock, VMs, cgroups, namespaces) that are already credible.

And this is exactly why we see noise on HN/Reddit when a supply-chain cyberattack breaks out, but no breach is ever reported. Enterprises are protected by internal mirroring.

I mean that agents can scan the code to find anything "suspicious". After all, security vendors that claim to "detect" malware in packages are relying on LLMs for detection.

Curious to know why are coding agents not detecting such risks before importing dependencies?

I actually just published a paper...

This gives me an impression that the paper has already been published and is available publicly for us to read.

Maybe humans can focus on cybersecurity and fraud? That’s not going away with AI

Block based on cookies (i.e., set a cookie on the browser and check on the server whether it exists).

I understand the need, but I don't understand why a VM or Docker is not enough. Why are people creating custom wrappers around VMs/containers?

Genuine question: why is everyone rolling out their own sandbox wrappers around VMs/Docker for agents?

when they incorrectly fake devices

And how often does this happen? Do you have any proof? Most YC companies building browser agents have built-in captcha solvers.

If not today, models will get better at solving captchas in the near future. IMHO, the real concern, however, is cheap captcha solving services.

What is so fundamentally different for AI agents?

Ah ha.

You're right that registries are under-resourced. But, if automated malware scanning actually worked, we'd already see big tech partnering with package registries to run continuous, ecosystem-wide scanning and detection pipelines. However, that isn't happening. Instead, we see piecemeal efforts from Google with assurance artifacts (SLSA provenance, SBOMs, verifiable builds), Microsoft sponsoring OSS maintainers, Facebook donating to package registries. Google's initiatives stop short of claiming they can automatically detect malware.

This distinction matters. Malware detection is, in the general case, an undecidable problem (think halting problem and Rice theorem). No amount of static or dynamic scanning can guarantee catching malicious logic in arbitrary code. At best, scanners detect known signatures, patterns, or anomalies. They can't prove absence of malicious behavior.

So the reality is: if Google's assurance artifacts stop short of claiming automated malware detection is feasible, it's a stretch for anyone else to suggest registries could achieve it "if they just had more resources." The problem space itself is the blocker, not just lack of infra or resources.

automated scanners seem to do a good job already of finding malicious packages.

That's not true. This latest incident was detected by an individual researcher, just like many similar attacks in the past. Time and again, it's been people who flagged these issues, later reported to security startups, not automated tools. Don't fall for the PR spin.

If automated scanning were truly effective, we'd see deployments across all major package registries. The reality is, these systems still miss what vigilant humans catch.

on the other hand, the previous supply chain attack was found by automated tech.

Are you sure about this? Would love to see which ones.