It's interesting to look at what was being attempted when the vulnerability was introduced[0]
> Workflows like jira_close.yml use deprecated atlassian JIRA actions and have a dependency on the gh-actions repo. This is not ideal and unecessarily complex. PR updates jira_close workflow to use direct API calls via curl. It preserves custom fields used too.
I won't speak to this projects' management and how they prioritize things, but from my own experience, pre-AI, this type of change would have been firmly in the "this is a minor annoyance, put it in the Tech Debt Backlog alongside the 50000 other tickets" and never actually done. The cost of a human investing the time understanding how to fix the problem, doing code changes, testing them, and deploying them is just way too high for what actual value this change brings, which is close to nothing.
Now with AI, it's as simple as firing up an agent and telling them to make a change; as much effort as writing that backlog Jira ticket in the first place.
Similar to the problem open source is having with low-value PRs, companies are going to have to start realizing that code is not free to review or maintain, even when it's generated for ~free, in their internal processes. Just because an agent can fix a minor tech debt annoyance with a few lines of instructions doesn't mean it should.
In a similar vein, JSON's lack of comments makes me marvel at how consistently JavaScript seems to choose the worse option. I'm oh so glad it found its way into config files
The first linked PR (#1218) has only one commit co-authored by Copilot and it's not related to the vulnerability, and neither are the other suggestions in the PR. Am I missing something?
> However, on issues events, github.event.pull_request is always null.
This is extra dumb because even if you thought this condition was correctly testing the user's identity, it shouldn't have "appeared protective" upon even a moment's thought. If it worked correctly, it would obviously just exclude one bot user while allowing all other users, so it wouldn't provide any protection at all.
But more likely, this condition was never intended to be "protective" at all, and it's only being described that way because the writeup is LLM slop.
No, Snowflake allowing autofixes compromised their Jira. If you tell someone to shoot you in the foot, and they shoot you in the foot, you shot yourself in the foot, just with more steps. If someone else finds the memo that says you've set up foot shooting as a service, and then they trigger that service, you still shot yourself in the foot.
Help me understand. Snowflake configured their Github repo to allow auto fixes by Copilot. It got merged automatically without anyone's review? And introduced essentially script-injection vulnerability through the title field?
If this is the case, I would say Snowflake should shut down its repo and get off Github asap.
I'm all for using a council of LLMs, I wrote a tool for it https://github.com/joelio/owl - but you still need to read through PRs yourself, at the very least.
It’s clear that they want this to be true so bad that they’re just not going to do it, and will spend a ton of money on quality gates and mitigation strategies instead of just reading some code.
I have been talking to people who want to autoreview and approve "minor" AI prs. For security especially, I think if the models weren't enough to prevent the issues, they aren't enough to judge what is minor.
> Workflows like jira_close.yml use deprecated atlassian JIRA actions and have a dependency on the gh-actions repo. This is not ideal and unecessarily complex. PR updates jira_close workflow to use direct API calls via curl. It preserves custom fields used too.
I won't speak to this projects' management and how they prioritize things, but from my own experience, pre-AI, this type of change would have been firmly in the "this is a minor annoyance, put it in the Tech Debt Backlog alongside the 50000 other tickets" and never actually done. The cost of a human investing the time understanding how to fix the problem, doing code changes, testing them, and deploying them is just way too high for what actual value this change brings, which is close to nothing.
Now with AI, it's as simple as firing up an agent and telling them to make a change; as much effort as writing that backlog Jira ticket in the first place.
Similar to the problem open source is having with low-value PRs, companies are going to have to start realizing that code is not free to review or maintain, even when it's generated for ~free, in their internal processes. Just because an agent can fix a minor tech debt annoyance with a few lines of instructions doesn't mean it should.
[0] https://github.com/snowflakedb/snowflake-connector-net/pull/...
In its quest to make markup "human readable", it has created countless footguns.
I honestly prefer XML at this point.
Better move as much of that as possible into your own scripts. And your scripts can be portable between forges, and even run locally!
> if: (github.event_name == 'issues' && github.event.pull_request.user.login != 'whitesource-for-github-com[bot]')
> However, on issues events, github.event.pull_request is always null.
This is extra dumb because even if you thought this condition was correctly testing the user's identity, it shouldn't have "appeared protective" upon even a moment's thought. If it worked correctly, it would obviously just exclude one bot user while allowing all other users, so it wouldn't provide any protection at all.
But more likely, this condition was never intended to be "protective" at all, and it's only being described that way because the writeup is LLM slop.
Quote injection still alive and well in 2026. Gawd.
If this is the case, I would say Snowflake should shut down its repo and get off Github asap.
Humans need to review this stuff yall there's no way around that, apparently to some, very inconvenient reality.
Absolutely.
Nothing in the PR jumps out as a red flag. Unless you know how the internals work, I suppose.
Made by AI?