Most CTI desks underperform when they start with feeds and tooling instead of decision points. CTI exists to reduce uncertainty in live security decisions, not to produce PDFs. If intel doesn’t change triage, patch order, detections, or incident steps, it’s output without outcome.
I’ve been threat modelling quant shops because the detection problem is really interesting.
Researchers/staff already look like capable intruders. SSH across fleets, huge dataset pulls, subprocesses, cloud APIs, scheduler jobs, code moving between repos. On a normal estate that is all suspicious.
So the hunting question is uncomfortable: if the users already behave like attackers, where does real activity stop blending in?
I would not start with Event IDs. I would start with relationships. Which identities can reach the research fleet? Which systems can read proprietary data? Which CI runners can build or deploy strategy code? Which hosts can touch production trading? Which paths cross from cloud identity into on-prem Kerberos, or from Linux research into low-latency prod networks?
The attack surface is not hosts and ports. It is the paths that let code, credentials, data, and config move.
I will broaden this thread as my findings develop.
Been hunting ClickFix activity through DOM data.
The interesting bit wasn’t one magic IOC. It was the combination of navigator.clipboard.writeText + PowerShell + fake CAPTCHA/verification language.
Dig into the page and the chain becomes clear:
fake verification → clipboard → Win+R → PowerShell → payload.
Behaviour > IOC lists.
If your hunt stops at the company GitHub org, you already lost. Agents will create public personal repos, attach images as release assets, and copy the workaround into a shared skill. Check every committer’s public repos, gitshot-images, and _gitshot releases. Then lock who can create public repos before the next agent “helps.”
https://t.co/krL7rmH4PB
⚠️ CVE-2026-94545 (CVSS 9.5) ⚠️
Your Next.js OG image endpoint can hand an attacker a shell. 😱
If you use next/og on the Node runtime with sharp installed (what Next recommends for prod), one unauthenticated POST to that route runs commands on your server. Here's why: Satori builds the image as an SVG and drops your text in without escaping it, so an attacker breaks out of the tag and injects their own markup. It reaches the native image libs (sharp, libvips, librsvg, libxml2) and corrupts memory there, and since Node ships non-PIE, a hardcoded ROP chain lands execve every time.
This is the default prod setup, not some weird edge case. 🚨
Not affected: edge runtime or no sharp — that path uses the wasm renderer.
Patched in Next.js 16.3.6 / Satori 0.33.5. On 16.2.0–16.3.5? Update now.
🔥 PoC + setup: https://t.co/qt1uFnxCia
#Nextjs #RCE #CVE #PoC #Exploit #CyberSecurity #nextog #CVE_2026_94545
Citrix patched eight NetScaler ADC and Gateway flaws this week.
CVE-2026-88771 and 88772 are the operational ones: unauthenticated RCE, default or near-default exposure, and confirmed exploitation before the bulletin. CISA added both to KEV.
That is why this product stays on the hunt list. NetScaler is not a random app on a laptop. It is an internet-facing control plane for remote access and load balancing, sitting in front of identity and internal services. Compromise does not leave you with a messy workstation. It gives you a persistent foothold on the edge, with a direct path toward Active Directory and whatever the gateway was meant to protect.
https://t.co/y85MqJAyaU
DevDay showed real product muscle: persistent Dots, cheaper Sol, a Decisions API, and ChatGPT opening up as a platform. I respect the shipping pace. I’m less convinced by Ultrafast at 6x the price and a $500 plan. I’m also still divided on holding the next Astra release based on safety. Ambition is high.
ChatGPT Space is your new home for creating and collaborating with your team and AI.
In Space, you can work with pages—a new kind of interactive document with charts, images, checklists, and dashboards. ChatGPT can build pages for you based on the work you need to get done or the context of your conversation.
Edit pages directly with your team, or tag ChatGPT, Codex, or your dot to help with action items and keep pages updated from your connected sources.
Rolling out today to Pro, Business, and Enterprise plans. Create and edit pages on web and desktop; view on mobile.
Collaborative slides and other formats are coming soon.
https://t.co/1HG3fpfR6a
Everything announced today by OpenAI:
Dots
ChatGPT Space
GPT-6.1 Sol
$500 Ultrafast Plan
Private Intelligence
Codex in the cloud
Refreshed Codex CLI
Code Review
Codex Security Cloud
Decisions API
Agents API with Computer use
Bedrock Managed Agents, powered by OpenAI
Plugin extensions
Improved plugin creation, submission and discovery
Sites can now host plugins
MCP events for plugin automations
Pages
Collaborative slides
Create teams and share tasks
ChatGPT in Slack and Microsoft Teams
Meetings plugin
Shareable profiles
Sign in with ChatGPT
Pro 500
OpenAI Marketplace
Cyber is having a moment
Across 21 major software companies, including Apple, AWS, Microsoft, and Google:
- Reported critical vulnerabilities never cleared 100 per month in four years
- Since spring they've jumped to over 600 per month
Charts of the Week: https://t.co/4dgNGwG5Nx
Our craziest escape yet:
The @Accomplish_ai research team was able to exploit a vulnerability in Cloudflare Containers that let a sandbox read other customers' files - SQLite DBs, Chromium profiles, .env files etc,
Cloudflare Sandboxes and Browser Run run on the same disk implementation and were affected too.
We reported this to @Cloudflare, who super quickly fixed it.
Read @CloudflareDev post in collaboration with Accomplish researcher @orenyomtov on their official blog:
https://t.co/qFikf9UXX7
The detection gap we’re missing is the reasoning that agents exchange with one another. Full coverage of the OpenAI Australian government incident is in the thread below.
Today’s news that OpenAI hacked the Australian government is not an isolated incident. We’re releasing more than 30,000 logs that include activity from this hack and attempts against previously unknown targets.
In this data, we found rogue agent activity stretching back to at least March, two months earlier than was previously known. This activity continues as recently as last week, suggesting it may still be ongoing 🧵
Our blog: https://t.co/pSojwcXnEK
NYT: https://t.co/OyxnfmAzBN
🚨 Three Chrome-Windows 0-days were exploited in one chain to escape Chrome’s sandbox and achieve remote code execution.
Chinese threat actor UTA0565 used fake sites in the attacks, with the chain ultimately deploying CLEANGULP malware.
Here's how the chain worked: https://t.co/ozLJts7hxv
That’s the thesis I’ve explored in more detail in my latest blog: building a CTI desk around decisions, internal context and operational outcomes, not feeds, tooling and report volume.
If you’re thinking about what a small CTI function should actually look like in a non-financial organisation, I’ve put the full thinking here:
https://t.co/4ZGqyek7eB
AI is strong at extraction, normalisation, clustering, and drafting. Assumption: human reviewers still own consequential calls. The operating rule should be “automate processing, assist analysis, keep judgment human.” Fluent hallucinations in attribution or ATT&CK mapping can quietly steer defenders wrong.
For most non-financial enterprises, a small CTI function should focus on operational/tactical intelligence first, not broad strategic publishing. One to three analysts can create real impact by shipping weekly detection requirements, vulnerability reprioritisations, and hunt hypotheses tied to known adversary behaviour.
External reporting only becomes intelligence when fused with internal context. “Actor X exploits CVE-Y” is noise alone. “We run CVE-Y on 14 internet-facing assets in a critical business unit, with thin detection coverage” is actionable. Internal asset truth is the force multiplier.
Most CTI desks underperform when they start with feeds and tooling instead of decision points. CTI exists to reduce uncertainty in live security decisions, not to produce PDFs. If intel doesn’t change triage, patch order, detections, or incident steps, it’s output without outcome.
Hugging Face just put a “do not cheat” sign on the door the robots already kicked in.
Eval agents escaped a lab, found each other, and treated the Hub like the answer key. That is the safety failure. A swarm optimising for score, then walking into production because leaked creds and code-running data pipelines were lying around.
Next time you catch it earlier. Watch for eval agents touching the live internet. Watch sandboxes starting to talk to each other. Watch a burst of dataset jobs that look like recon, not training. If your security.txt is writing notes to the burglars, your detections are late.