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Startups emerging from stealth: ❌
Startups emerging from cornfields: ✅
The GraphnAI Public Preview is live: Identity Security that shows which attack paths are real.
🧵👇
Josh M. Bryant retweeted
I was talking to @ZackKorman about this, and I think part of the disconnect is that people are picturing two different types of companies traditional enterprises and modern, cloud native startups.
Traditional enterprises often put workloads behind DMZs, internal networks, or segmented cloud environments, limiting what’s directly reachable. In that setup, phishing and credential spraying can be especially valuable ways in.
Compare that with a startup built around internet-facing apps, APIs, and SaaS integrations. There can be a much broader surface to attack directly.
Both can run on AWS or GCP. The distinction is what’s exposed and how access is controlled. That changes which attack paths are useful.
That also matters when people talk about attacker “swarms.” An EDR can isolate a workstation or kill the processes supporting an attacker’s access. If that workstation was their only foothold, adding more agents doesn’t magically restore access to that network segment.
Detection is only part of the picture. Companies can also restrict outbound communications through egress filtering, enforced proxies, or always on VPN and secure web gateway configurations. Those controls can block or disrupt the communications an attacker needs to maintain access.
Even stealing NTDS.dit doesn’t guarantee a path back in. Depending on the access path, the attacker may still have to contend with MFA, conditional access, segmentation, and other controls. More agents can accelerate attempts, but they still need a viable route in.
nitter.cf/HackingLZ/status/21191…
The cage analogy falls apart when defenders built the cage and control the doors, lights, and layout. Segmentation, IAM, least privilege, and monitoring all matter. More attackers increase the pressure they don’t erase the defender’s control of the environment.
nitter.cf/MTSlive/status/2118864…
This is actually a good argument for using AI pentesting tools like this (with caution). Use them against yourself, before someone else does. Fix findings until it is no longer successful against you, then graduate to hiring skilled humans to strengthen defenses even more.
Raising 3 kids may have prepared me more for managing AI agents than anything I ever did in my long career.
I setup a scary Chinese hacking harness running a scary Chinese AI model inside a sandbox...
It's been running for an hour, and hasn't escaped yet.
Watching Qwen 3.8 27B run an nmap scan via ARTEX in my lab is very amusing.
"This is a major discovery" 🤣
Weren't several banks freaking out about people connecting AI to their accounts just a couple weeks ago? 🤣
Finally getting around to setting up ARTEX in my lab. Most everything I've seen about it has focused on IOCs. One article suggested behavioral analytics, but didn't really dive into it.
@UK_Daniel_Card posted some videos showing how noisy it can be, which goes a little beyond IOC into IOA territory.
I'm curious to see if we can follow the full IOC -> IOA -> IOE path. What exposures does it attempt to abuse the most? Closing those is a more effective approach than playing IOC whack-a-mole.
OpenAI out here re-discovering "impose cost" from first principles. 🤪
Replying to @OpenAI
The full run cost $1,213,430 in API credits—about $1,279 per distinct local privilege escalation vulnerability.
For context, applying historical Pwn2Own and TyphoonPWN bounty rates gives a hypothetical value of $18.9M–$66.3M.
This demonstrates the relative efficacy of using AI models for securing software—defenders should proactively analyze software to make cyber attacks cost-prohibitive.
All the "security researchers" prompting "Find the vulnerabilities in node.js before the 11th, make no mistakes" now. 🤪
Security release pre-alert:
We will release new versions of Node.js 22, 24, and 26 release lines on or shortly, after 2026-11-11 in order to address security vulnerabilities.
The highest severity issue fixed in this release is HIGH.
nodejs.org/en/blog/vulnerabi…
ICYMI...
A FREE public preview of the project I've been working on for the last year is now available at: graphnai.com/preview
Backed by 27+ years of experience and 6 pending patents. Please try it out and let me know what you think!
Josh M. Bryant retweeted
Here’s the thing about agentic attacks - the current incarnation won’t score on you with some l33t zero day…but they will check every possible “door handle” to see which one you forgot to lock
How many red team assessments has your organization gotten where they searched some internal knowledge repository/file share…etc and found reams of creds/secrets/tokens…and your organizational response was a collective shrug 🤷♂️ and nothing got fixed/improved to prevent it from happening again?
Agentic attack often target the security tech debt of every organization that has always been there - but just hasn’t been abused by an external attacker yet
This is a good read.
When your outer defenses fail and an attacker establishes a foothold, ask yourself: "Where could they go from here?"
Post-compromise defensive layers are more important than ever. Are you containing the blast-radius?
"How to Solve the Mystery of #AI + Defense in Depth?" bit.ly/48zZCkl <- a bit of rant, but I feel the need to answer to "DiD does not matter with AI" camp now!
"AI-native DiD" is essentially what I've been building for the last 10 months (scoped to identity for now) with GraphnAI.
graphnai.com














