Last year I thought that AI-generated code would be scanned the same way as human-generated code. What I realized from working on Guardian was that being in the agent loop is an unfair advantage: you can ask the agent to switch to a secure library (eg, defusedxml for python) and it will happily do it before code lands. If you asked a developer to do that in a CI code review, it's a lot more context switching and work.
That means there is an unprecedented opportunity to make both security and developer outcomes better by shaping agent behavior towards secure defaults. Even things like "don't add dependencies unless these conditions are met; we only want top1000 NPM dependencies, otherwise just write it yourself."
Capabilities like this will have a big impact on the OSS ecosystem (positive and negative) as they profilerate.
> This plan works by letting software supply chain companies find security issues in new releases. Many security companies have automated scanners for popular and less popular libraries, with manual triggers for those libraries which are not in the top N.
The impact question is really around scale; a few weeks ago Anthropic claimed 500 "high-severity" vulnerabilities discovered by Opus 4.6 (https://red.anthropic.com/2026/zero-days/). There's been some skepticism about whether they are truly high severity, but it's a much larger number than what BigSleep found (~20) and Aardvark hasn't released public numbers.
As someone who founded a company in the space (Semgrep), I really appreciated that the DARPA AIxCC competition required players using LLMs for vulnerability discovery to disclose $cost/vuln and the confusion matrix of false positives along with it. It's clear that LLMs are super valuable for vulnerability discovery, but without that information it's difficult to know which foundation model is really leading.
What we've found is that giving LLM security agents access to good tools (Semgrep, CodeQL, etc.) makes them significantly better esp. when it comes to false positives. We think the future is more "virtual security engineer" agents using tools with humans acting as the appsec manager. Would be very interested to hear from other people on HN who have been trying this approach!
"Staged publishing: A new publication model that gives maintainers a review period before packages go live, with MFA-verified approval from package owners. This empowers teams to catch unintended changes before they reach downstream users—a capability the community has been requesting for years."
This is explicitly not the conclusion Pascal drew with the wager, as described in the next section of the Wikipedia article: "Pascal's intent was not to provide an argument to convince atheists to believe, but (a) to show the fallacy of attempting to use logical reasoning to prove or disprove God..."
Looks like the `ets` readme has a direct comparison:
> The purpose of ets is similar to that of moreutils ts(1), but ets differentiates itself from similar offerings by running commands directly within ptys, hence solving thorny issues like pipe buffering and commands disabling color and interactive features when detecting a pipe as output. (ets does provide a reading-from-stdin mode if you insist.) ets also recognizes carriage return as a line seperator, so it doesn't choke if your command prints a progress bar. A more detailed comparison of ets and ts can be found below.
So the argument is because the vulnerability lifetime is exponentially distributed, focusing on secure defaults like memory safety in new code is disproportionately valuable, both theoretically and now evidentially seen over six years on the Android codebase.
Amazing, I've never seen this argument used to support shift/left secure guardrails but it's great. Especially for those with larger, legacy codebases who might otherwise say "why bother, we're never going to benefit from memory-safety on our 100M lines of C++."
I think it also implies any lightweight vulnerability detection has disproportionate benefit -- even if it was to only look at new code & dependencies vs the backlog.
Absolutely agreed, and copying from a comment I wrote last year: I think the fact that tree-sitter is dependency-free is worth highlighting. For context, some of my teammates maintain the OCaml tree-sitter bindings and often contribute to grammars as part of our work on Semgrep (Semgrep uses tree-sitter for searching code and parsing queries that are code snippets themselves into AST matchers).
Often when writing a linter, you need to bring along the runtime of the language you're targeting. E.g., in python if you're writing a parser using the builtin `ast` module, you need to match the language version & features. So you can't parse Python 3 code with Pylint running on Python 2.7, for instance. This ends up being more obnoxious than you'd think at first, especially if you're targeting multiple languages.
Before tree-sitter, using a language's built-in AST tooling was often the best approach because it is guaranteed to keep up with the latest syntax. IMO the genius of tree-sitter is that it's made it way easier than with traditional grammars to keep the language parsers updated. Highly recommend Max Brunsfield's strange loop talk if you want to learn more about the design choices behind tree-sitter: https://www.youtube.com/watch?v=Jes3bD6P0To
And this has resulted in a bunch of new tools built off on tree-sitter, off the top of my head in addition to difftastic: neovim, Zed, Semgrep, and Github code search!
That means there is an unprecedented opportunity to make both security and developer outcomes better by shaping agent behavior towards secure defaults. Even things like "don't add dependencies unless these conditions are met; we only want top1000 NPM dependencies, otherwise just write it yourself."
Capabilities like this will have a big impact on the OSS ecosystem (positive and negative) as they profilerate.