Learning Linux in 2025!
Get your hands dirty with the Linux Command Line CTF Challenges on @learntocloud
It literally takes 15-20 second to deploy the provided lab environment in your choice of cloud.
More challenges coming soon.
Today we are in a security nightmare:
- Railway may have exposed customer environment variables and API keys
- SBI confirmed that customer records ended up on the dark web
- eMudhra's certificate keys were extremely weak (one was literally just the number 4)
- LiteLLM shipped a compromised version that steals credentials and includes a backdoor
- PHP released two critical remote code execution vulnerabilities (PHP2Shell)
- Node.js issued urgent security patches for a Brotli decoder remote code execution flaw, plus TLS and DNS issues and blocked the compromised eMudhra certificates
- Rajasthan gov systems were allegedly linked to the exposure of a large set of identity records
- OpenCode confirmed a breach that exposed AI provider API keys (OpenAI, Anthropic, Google) for a portion of Console users
- Plex Media Server vulnerabilities (Plex2Shell) are being actively exploited in the wild to install malware on unpatched servers
- GitLab fixed a critical CVSS 10.0 unauthenticated remote code execution flaw in its CI/CD regex compiler
AI-102 is retired. Its replacement, AI-103, is a very different exam.
I just passed the Microsoft AI-103 (Azure AI Apps and Agents Developer Associate), and made a video on how I prepared.
The biggest shift: it's no longer "which Cognitive Service do I pick?" It's agents, tools, RAG, and Microsoft Foundry.
A few things that helped me:
- Start with the official study guide. AI-103 is new, so a lot of third-party content is still recycled AI-102 material.
- Spend most of your time on 2 domains. Planning/securing Foundry + building gen AI apps and agents make up 55-65% of the exam.
- Know which agent tool fits which scenario: File Search vs Azure AI Search, Bing grounding, Code Interpreter, function calling, OpenAPI, MCP.
- Managed identity beats API keys. Every time.
- Go hands-on. Build one agent in Foundry and the whole object model clicks.
If you're coming from AWS like me, I also mapped the Azure services to their AWS equivalents in my notes.
Video - https://t.co/WJPCEI6CPq
Today we are rolling out Gemini 4 Argon globally in the Gemini API, to Pro + Ultra in Gemini App, and Ultra subs in Antigravity!
Argon is a huge step forward for Gemini, and a labor of love. This model has been battle tested by over 100,000 people at Google over the last month, with so much new innovation, ambition, and hard work baked into this release. The team has been heads down over the last 6 months working to make this possible across the stack (research, infra, safety, eng, etc).
We rolled the model out to cyber defenders as part of our fairwind program and early access customers over the last 2 weeks, it has been amazing to see and talk to folks who are now using this model daily. Seeing the models writing capability, raw knowledge and persistence for coding, paired with new features like 1M token output when the model needs to work more has gotten me even more excited about our path ahead.
This is just the start of the Gemini 4 era. As you saw with 3.5, 3.6, 3.7, and 3.8 Flash, our iteration speed with Gemini is fast : ) Now with Gemini 4 Argon to work from, I am cannot wait to see the progress continue, and most importantly see what this new model enables for the world.
This is such a special moment in the arc of technology, as millions of people everyday tackle problems they could never have thought possible before. Gemini 4 Argon was built to help you tackle the hardest problems. I have personally felt this spark with Argon and hope you do too. Onwards!!