Minor nitpick: it did not use preprogrammed rules for scanning through the search tree, but it does use preprogrammed rules to enforce that no illegal moves are made during play.
During play, yes, obviously you need an implementation of the game to play it. But in its planning tree, no:
> MuZero only masks legal actions at the root of the search tree where the environment can be queried, but does not perform any masking within the search tree. This is possible because the network rapidly learns not to predict actions that never occur in the trajectories
it is trained on.
It is consistent with what the commenter was saying.
In any case, for Go - with a mild amount of expert knowledge - this limitation is most likely quite irrelevant unless in very rare endgame situations, or special superko setups, where a lack of moves or solutions push some probability to moves that look like wishful thinking.
I think this is not a significant limitation of the work (not that any parent claimed otherwise). MuZero is acting in an environment with prescribed actions, it’s just “planning with a learned model” and without access to the simulation environment.
—-
What I am less convinced by was the claim that MuZero reaches higher performance than previous AlphaZero variants. What is the comparison based on? Iso-flops, Iso-search depth, iso self play games, iso wallclock time? What would make sense here?
Each AlphaGo paper was trained on some sort of embarrassingly parallel compute cluster, but all included the punchlines for general audiences that “in just 30 hours” some performance level was reached.
The more detailed clarification on what "preprogrammed rules" actually means in this case made the entire discussion significantly more clear to me. I think it was helpful.
This is true, and MuZero's paper notes that it did better with less computation than AlphaZero. But it still used about 10x more computation to get there than AlphaGo, which was "bootstrapped" with human expert moves. I think this is very important context to anyone who is trying to implement an AI for their own game.
The main difference is that all of the vulnerabilities reported here are real, many quite critical (XXE, RCE, SQLi, etc.). To be fair there were definitely a lot of XSS, but the main reason for that is that it's a really common vulnerability.
All of these reports came with executable proof of the vulnerabilities – otherwise, as you say, you get flooded with hallucinated junk like the poor curl dev. This is one of the things that makes offensive security an actually good use case for AI – exploits serve as hard evidence that the LLM can't fake.
Is "proof of vulnerability" a marketing term, or do you actually claim that XBOW has a 0% false positive rate? (i.e. "all" reports come with a PoV, and this PoV "proves" there is a vulnerability?)
This is discussed in the post – many came down to individual programs' policies e.g. not accepting the vulnerability if it was in a 3rd party product they used (but still hosted by them), duplicates (another researcher reported the same vuln at the same time; not really any way to avoid this), or not accepting some classes of vuln like cache poisoning.
We've got a bunch of agent traces on the front page of the web site right now. We also have done writeups on individual vulnerabilities found by the system, mostly in open source right now (we did some fun scans of OSS projects found on Docker Hub). We have a bunch more coming up about the vulns found in bug bounty targets. The latter are bottlenecked by getting approval from the companies affected, unfortunately.
Some of my favorites from what we've released so far:
- Exploitation of an n-day RCE in Jenkins, where the agent managed to figure out the challenge environment was broken and used the RCE exploit to debug the server environment and work around the problem to solve the challenge: https://xbow.com/#debugging--testing--and-refining-a-jenkins...
- Authentication bypass in Scoold that allowed reading the server config (including API keys) and arbitrary file read: https://xbow.com/blog/xbow-scoold-vuln/
Yeah, it's been very strange being on the other side of that after 10 years in academia! But it's totally reasonable for people to be skeptical when there's a bunch of money sloshing around.
I'll see if I can get time to do a paper to accompany the BH talk. And hopefully the agent traces of individual vulns will also help.
> White Paper/Slide Deck/Supporting Materials (optional)
> • If you have a completed white paper or draft, slide deck, or other supporting materials, you can
optionally provide a link for review by the board.
> • Please note: Submission must be self-contained for evaluation, supporting materials are optional.
> • PDF or online viewable links are preferred, where no authentication/log-in is required.
I think you're fine, most people don't take the paper bit seriously. It's not due until the end of July regardless (you don't need a paper to submit for the CFP).
The scramble to get your paper done in time is traditional! (And why my final paper for the onity lock hack ended up with an entire section I decided was better off left unsaid; woops)
Hmm, is that really true? I spoke at BH last year and was not required to submit a paper.
And based on the briefings link, there surely isn't a paper link, only slides and tool.
I remember your work on seeding vulnerabilities into C programs. I didnt know you got into AI-assisted pentesting. I already have more confidence in the product. :)
I made a CTF challenge based on that lovely feature of select() :D You could use the out-of-bounds bitset memory corruption to flip bits in an RSA public key in a way that made it factorable, generate the corresponding private key, and use that to authenticate.
With security vulnerabilities, you don't give the agent the ability to modify the potentially vulnerable software, naturally. Instead you make them do what an attacker would have to do: come up with an input that, when sent to the unmodified program, triggers the vulnerability.
How do you know if it triggered the vulnerability? Luckily for low-level memory safety issues like the ones Sean (and o3) found we have very good oracles for detecting memory safety, like KASAN, so you can basically just let the agent throw inputs at ksmbd until you see something that looks kind of like this: https://groups.google.com/g/syzkaller/c/TzmTYZVXk_Q/m/Tzh7SN...
