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Discussion (22 Comments)Read Original on HackerNews
Something like incorrect SELinux configurations?
Now should I mention all the screw up I have seen in several Saas 1b+ valuation, including DocuSign/ and more security oriented ones (PIM related etc?).
For any softwares, you need a minimum critical mindset and experiences that you don't usually see.
In other cases the content is at easily guessable path, and that is a whole different story
Syntax is solved.
But getting agents to write secure code currently seems beyond what can be trained into models even with synthetic data. Or maybe the big labs haven’t tried yet.
Regardless if you truly care about your AI’s output having some property, the only way is to codify how work that has that quality looks - then create deterministic hooks and checks that refuse to let the AI stop until it’s passed the bar.
Skills, MCPs, “you MUST do this” in your agent instructions.. it’s all just new ways to waste tokens trying to asymptotically approach what good work looks like.
You will never reliably get acceptable work unless you build deterministic checking, and enforcement of said checking in a way to model can’t bypass or ignore.
Look into Claude Code hooks - your hook can be a script, and if it exits with exit code 2, it’ll block the model and show it the script’s output. A stop hook can check the model’s work and block its attempt to stop if the work doesn’t meet your bar. The script output can describe what still needs to be fixed and for bonus points, where (line 567 uses untrusted input, paragraph 2 makes an uncited claim, clause 15 references superseded case law, etc.)
Security? At this stage, I'm a bit afraid that it's a joke more than anything else.
You could also use hooks to block running of scripts for some number of turns after an attempt to cheat.
Defense is a toally different game, and requires a complete new mindset than creativity. Security is something that you miss one then you lose all.
AIs are good at choosing a good candidate based on a reward model, but it sucks hard at enumerating mundane attack surfaces and make combinations to exploit through.
Someone else blindly operating an llm on a corpus you created with an llm is comical.
There is nothing wrong with asking for help or bouncing ideas of people with stronger skills.
I still have the responsibility to code XYZ well. But I don’t have to do it in a clean room.
You played yaself
Review your code, have integration tests, rollout feature incrementally with feature flags.
All the things we previously did for all the really bad human developers which AI is way better than
They defined vibecoding as non technical folk using llms to code, sound like you were a software house and have coding experience... Basically id trust coders with prod released ai code, but not an office full of Jackies
Are they actually different? I would guess they have roughly the same efficacy. 100% code coverage means nothing, and this is especially true with LLMs.
I mean, yes, but I suppose we live in such a nonsensically thoughtless time that stating the obvious has some value.
> To combat this we need to write a security context file to guide the AI
And you've already lost the plot. The problem is not that you're pulling the arm of the slot machine without wearing your lucky underwear, the problem is that you're delegating security to the slot machine to begin with. Pack it up, you're done.
Edit: To combat this we need to actually write and understand our code.
In our company we are just running agents inside isolated containers with isolated network access so it cannot even SSH or fuck up anything even if it gets access into it... That's the only and safest way... inconvenient, true, but the only safe option.
PS: At the same time I've observed this way actually people uses the agent in a more reasonable way, e.g. producing helper scripts to help them with their daily stuff, produce very specific things, create simple PoCs, but they don't commit to vibe-code all the functionality in their corresponding software products.