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!
nikcub 6 minutes ago [-]
> What we've found is that giving LLM security agents access to good tools (Semgrep, CodeQL, etc.) makes them significantly better
100% agree - I spun out an internal tool I've been using to close the loop with website audits (more focus on website sec + perf + seo etc. rather than appsec) in agents and the results so far have been remarkable:
Human written rules with an agent step that dynamically updates config to squash false positives (with human verification) and find new issues in a loop.
upghost 2 hours ago [-]
Anakin: I'm going to save the world with my AI vulnerability scanner, Padme.
Padme: You're scanning for vulnerabilities so you can fix them, Anakin?
Anakin: ...
Padme: You're scanning for vulnerabilities so you can FIX THEM, right, Annie?
nikcub 44 seconds ago [-]
I assume that's why this is gated behind a request for access from teams / enterprise users rather than being GA
czbond 2 hours ago [-]
Definitely will be a fight against bad actors pulling bulk open source software projects, npm packages, etc and running this for their own 0 days.
I hope Anthropic can place alerts for their team to look for accounts with abnormal usage pre-emptively.
3 minutes ago [-]
tptacek 2 hours ago [-]
You want frontier models to actively prevent people from using them to do vulnerability research because you're worried bad people will do vulnerability research?
czbond 1 hours ago [-]
Not at all. I was suggesting if an account is performing source code level request scanning of "numerous" codebases - that it could be an account of interest. A sign of mis-use.
This is different than someones "npm audit" suggesting issues with packages in a build and updating to new revisions. Also different than iterating deeply on source code for a project (eg: nginx web server).
tptacek 2 hours ago [-]
I don't understand the joke here.
ukuina 10 minutes ago [-]
A vuln scanner is dual-use.
john_strinlai 58 minutes ago [-]
[dead]
nadis 1 hours ago [-]
> "Rather than scanning for known patterns, Claude Code Security reads and reasons about your code the way a human security researcher would: understanding how components interact, tracing how data moves through your application, and catching complex vulnerabilities that rule-based tools miss."
Fascinating! Our team has been blending static code analysis and AI for a while and think it's a clever approach for the security use case the Anthropic team's targeting here.
bink 1 hours ago [-]
I hope this is better than their competitors products. So far I've been underwhelmed. They basically just find stuff that's already identified by static analysis tooling and toss in a bunch of false positives from the AI scans.
1 hours ago [-]
david_shaw 1 hours ago [-]
There's a lot of skepticism in the security world about whether AI agents can "think outside the box" enough to replicate or augment senior-level security engineers.
I don't yet have access to Claude Code Security, but I think that line of reasoning misses the point. Maybe even the real benefit.
Just like architectural thinking is still important when developing software with AI, creative security assessments will probably always be a key component of security evaluation.
But you don't need highly paid security engineers to tell you that you forgot to sanitize input, or you're using a vulnerable component, or to identify any of the myriad issues we currently use "dumb" scanners for.
My hope is that tools like this can help automate away the "busywork" of security. We'll see how well it really works.
samuelknight 2 minutes ago [-]
LLMs and particularly Claude are very capable security engineers. My startup builds offensive pentesting agents (so more like red teaming), and if you give it a few hours to churn on an endpoint it will find all sorts of wacky things a human won't bother to check.
tptacek 1 hours ago [-]
I am seeing something closer to the opposite of skepticism among vulnerability researchers. It's not my place to name names, but for every Halvar Flake talking publicly about this stuff, there are 4 more people of similar stature talking privately about it.
awestroke 1 hours ago [-]
Claude Opus 4.6 has been amazing at identifying security vulnerabilities for us. Less than 50% falae positives.
john_strinlai 1 hours ago [-]
[dead]
41 minutes ago [-]
29 minutes ago [-]
drcongo 2 hours ago [-]
I thought they'd noticed how many of my Claude tokens I've been burning trying to build defences against the AI bot swarms. Sadly not.
reconnecting 36 minutes ago [-]
Is it only crawlers or bots that abuse your product?
We have been developing our own system (1) for several years, and it's built by engineers, not Claude. Take a look — maybe it could be helpful for your case.
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!
100% agree - I spun out an internal tool I've been using to close the loop with website audits (more focus on website sec + perf + seo etc. rather than appsec) in agents and the results so far have been remarkable:
https://squirrelscan.com/
Human written rules with an agent step that dynamically updates config to squash false positives (with human verification) and find new issues in a loop.
Padme: You're scanning for vulnerabilities so you can fix them, Anakin?
Anakin: ...
Padme: You're scanning for vulnerabilities so you can FIX THEM, right, Annie?
I hope Anthropic can place alerts for their team to look for accounts with abnormal usage pre-emptively.
This is different than someones "npm audit" suggesting issues with packages in a build and updating to new revisions. Also different than iterating deeply on source code for a project (eg: nginx web server).
Fascinating! Our team has been blending static code analysis and AI for a while and think it's a clever approach for the security use case the Anthropic team's targeting here.
I don't yet have access to Claude Code Security, but I think that line of reasoning misses the point. Maybe even the real benefit.
Just like architectural thinking is still important when developing software with AI, creative security assessments will probably always be a key component of security evaluation.
But you don't need highly paid security engineers to tell you that you forgot to sanitize input, or you're using a vulnerable component, or to identify any of the myriad issues we currently use "dumb" scanners for.
My hope is that tools like this can help automate away the "busywork" of security. We'll see how well it really works.
We have been developing our own system (1) for several years, and it's built by engineers, not Claude. Take a look — maybe it could be helpful for your case.
1. https://github.com/tirrenotechnologies/tirreno
No one knows you also caused that problem.