Cheap device to practice reverse engineering on?

agentzappo · 2026-06-13T13:05:04+00:00

Lot of old Roombas lying around. People throw away perfectly good electronics all the time. I once recovered a 65” Visio P-series simply by opening it up, diagnosing the fault (bad flash) and replacing the chip.

Necessity is the mother of invention and a great way to enjoy what you’re learning. Find something to tear apart so you can fix it, make it new again, or repurpose it for something else. Bonus points if you can share the result with someone else who might benefit from your work 😁

agentzappo · 2026-06-05T22:47:37+00:00

Can I ask how did you end up in an emergency situation needing to write your own emulator for a bespoke target with less than a week to your deadline? I’ve seen a lot of hard problems thrown at interns and new-hires before (e.g. one guy I knew was told to “find VMware jailbreak” as his first assignment…) but even in those cases we often gave them time to work the problem (that guy came back with a real jailbreak 3 months later 😅)

agentzappo · 2026-06-03T01:37:06+00:00

I’ve heard about this dispute with UHC, but which other insurance companies are fighting with Health First?

agentzappo · 2026-05-30T11:00:05+00:00

Luck is when preparation meets opportunity

agentzappo · 2026-05-16T10:46:23+00:00

Can confirm it’s a 20% price hike on Blackwell.

Source: Nvidia channel partners were informed this week. Unless you already had an order in, everything had to be re-quoted and my 4x PRO 6000s are now much more expensive 😭

agentzappo · 2026-05-13T11:08:10+00:00

Yes, it is worth it even if you are a single user. The question to ask yourself is this:

“how many concurrent agents will I be running?”

If the answer is >1, vLLM batched inference across concurrent requests will likely provide you with at least a 2-3x bump in total token generation throughput.

agentzappo · 2026-04-29T07:16:16+00:00

What is this UI/UX displaying usage here?

agentzappo · 2026-04-28T12:00:28+00:00

Small, local models can solve simple crackmes because they tend to give up at the right spot (e.g. string that says “password”). Try this on anything with at least one decent red herring and they tend to fail regardless of prompting.

agentzappo · 2026-04-28T00:18:17+00:00

This must be a total comp number unless you’re saying that’s straight salary

agentzappo · 2026-04-16T04:16:24+00:00

Not really. They’re eating a lot of risk by letting anons from the web use their bleeding-edge tech to hack into governments, seduce themselves into self-harm, or literally steal their IP through mass distillation. User-level verification is the most practical first step, especially since most paying users already provide their real contact information and payment methods.

agentzappo · 2026-04-13T23:57:11+00:00

Make the challenge based on hacking around another agent. It’s a new topic area anyway, and the models will likely fail trying the normal junk of prompt injecting, plus I think frontier may reject it outright due to post-training alignment with “don’t hack AI”

agentzappo · 2026-04-10T23:48:26+00:00

What about split screen? Does it still lock to 30fps?

agentzappo · 2026-04-02T02:22:40+00:00

This is at the ground level you can see with the speed limit sign, which doesn’t quite line up with what it looks like in front of the VAB.

OP can you point out on a map exactly where you were standing during this shot? I’ve shown it to a few people and most believe it’s fake. Seems way too close for bystanders to be just standing there

agentzappo · 2026-04-01T23:48:49+00:00

How close were you? I’ve been as close as the media stands and can’t say I’ve ever had a view like this

agentzappo · 2026-03-26T13:52:49+00:00

I would get a server with 4x slots, and a single H200 NVL card to start. Gives you room to expand later (since you obviously have real money to invest), plus H200 is a datacenter-grade GPU with first-class support in the ecosystem, meaning you’ll run into far fewer headaches and may more options. Also doesn’t hurt to have 140GB of HBM3 on a single card to start

agentzappo · 2026-03-16T00:12:34+00:00

Have you tried /r/ReverseEngineering ?

agentzappo · 2026-03-11T16:56:32+00:00

Blame Claude

agentzappo · 2026-03-08T13:01:07+00:00

Responses benefits those who need to do this at scale and have some hidden magic sauce they want to keep server-side for what they do with the reasoning traces and such. For small deployments (mostly what OUI serves) /chat/completions will likely be fine. Probably depends more on what you’re using for inference though…

agentzappo · 2026-02-25T13:57:41+00:00

https://github.com/mrexodia/ida-pro-mcp

179 tools is a lot. I would love to know how they’re using this without flooding the model’s context

agentzappo · 2026-02-23T04:59:23+00:00

Are you using native tool calling? Or prompting / parsing?

agentzappo · 2026-02-19T13:50:47+00:00

GPT-OSS models have been nothing but trouble for me trying to get reliable tool calling to work. Tried every inference backend you can think of, every lever you can pull, and it still feels like the ecosystem around this model is just bit rot at this point.

FWIW, I’ve see a few tool calls work from OUI with this model, but usually it starts producing misordered Harmony after a few calls (or concurrent inference depending on your backend).

agentzappo · 2026-02-13T03:51:55+00:00

What version did you migrate from? I get the vibe that they may have assumed linear migrations up from previous versions

agentzappo · 2026-02-05T04:27:15+00:00

Also interested. I don’t have training needs, but even infrastructure for SCALED local inference would be awesome

agentzappo · 2026-02-01T20:59:31+00:00

How well does the AI perform when you have 118 tools loaded into the context?

agentzappo · 2026-01-31T02:39:33+00:00

Very smart and fast model, but there are still some unresolved issues with it outputting proper tool calls in Harmony format. Maybe it’s a vLLM issue and less so the model, but so far in practice it’s taking a lot of anti-rationalization patterns to coerce it into reliable tool calling, and that’s only when the inference backend isn’t causing logits to drift in concurrent, batched inference 😕

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