Hello, hackers!
I’m starting a new community focused on Agentic Testing, Workflow Building, SOAR Integrations, and Agentic Bug Bounty.
We’ll explore how AI agents can be used to build smarter security workflows, automate security operations, and rethink bug bounty research.
Want to join us? Say “Hello” and I’ll add you to our Discord channel.
Let’s build, break, automate, and learn together.
Hashtags:
#CyberSecurity #AgenticAI #AIsecurity #BugBounty #SOAR #SecurityAutomation #AppSec
Dear yahoo boys and other cyber criminals,
The FBI has launched "Operation Blackout" and they are coming for you.
The big fishes are who they're looking for, and their network of apprentices.
So you sef wey be small yahoo boy fit be collateral damage.
You content creators or skit makers or musicians wey dey help dem front fit enter gbege too ooo.
Efcc is more lenient than FBI ooo.
I say make I warn una.
You can run, but you cannot hide forever ooo.
Every day for the thief, one day for the owner.
End.
ANTHROPIC SHOWS HOW TO RUN A WHOLE COMPANY WITH AI AGENTS FOR FREE
they split the work, collaborate, and run processes on their own with no humans in the loop
Bug Bounty Playbook 2 is great for learning post-recon exploitation techniques 🙌
It shows how to approach apps by analyzing their tech stack & you'll learn to create impactful POCs for bugs beyond OWASP's top 10!
Check it out here:https://t.co/dtWZwu7tXv #sponsored(but loved)
𝗠𝗖𝗣 𝘃𝘀 𝗔𝗣𝗜.
An 𝗔𝗣𝗜 defines how software systems communicate through specific endpoints, requests, and responses. It gives applications a structured way to access data or trigger functionality in another system.
𝗠𝗖𝗣 gives AI applications a standardized way to discover and use external tools, data, and resources. Instead of building custom integrations for every AI client, an MCP server exposes capabilities through a common protocol.
APIs expose functionality to software. MCP standardizes how AI applications discover and interact with that functionality.
But once AI sits behind an API, the request-response model gets harder.
Inference might take longer than the request can stay open. It might fail halfway through. It might need to be retried.
That changes how the API itself should be designed.
Oracle’s guide breaks down how to design for that with asynchronous jobs, workers, durable state, and predictable API contracts.
𝗥𝗲𝗮𝗱 𝘁𝗵𝗲 𝗴𝘂𝗶𝗱𝗲 → https://t.co/YIJ4uDSgRA
What else would you add?
——
🙏 Thanks to @OracleDevs for sponsoring this post.
➕ Follow me ( Nikki Siapno ) to improve at AI and system design.