ANTITREE

/dev/loop3 ro squashfs ---------------------------------------------------------~inode 0x4e21c8

uts:ns 4026532198 ----------------------------------------------------------#cap_sys_admin -eff

seccomp filt 0x1f ---------------------------------------------------------#rtt 12.4ms mtu 1500

::fe80::4a2c/64 ::::::::::::::::::::::::::::::::::::::::::::::::::::::::[vmalloc 0xffffc90000]

antiTree

Containers, kubernetes, AI, sandboxes, security, Linux isolation

and whatever else looks interesting enough to take apart.

[SANDBOXES]
[RUNTIME]GVISORID: RTM-49GVISOR / SYSCALL 0x2A / 11:16:45
Syscalls & sandboxes
[CONTAINERS]
[CLUSTER]CONTAINERDNODE: K8S-17CGROUP V2 / CAP_SYS_ADMIN / 04:22:09
Containers
[AI AGENTS]
[INFERENCE]TOOL-CALLCTX: 128KMCP / TOKENS 4096 / 19:41:02
AI & agents

· community

New Project: DRWND.com

I don’t remember the exact conversation, but Jason Ross inspired me to buy DRWND.com, as in Drone + PWND = DRWND. I’ve owned it for a bit waiting for some specific data so that I could use it as an informational site about DRWN attacks. As IANA web developer, this has been interesting and terrible but simple enough to share.

www.drwnd.com

I won’t assume the site makes any sense right now so I can summarize it like this:

  • It takes a data feed of all known locations of drone strikes and plots them
  • Circle size reflects the number of people killed
  • Circle color reflect the percentage of the deaths that were civilians and/or children in an RGB manner
    • Red – civilians
    • Green – expected targets or unknowns
    • Blue – children
  • <li style="text-align: left;">
      For example the done strike in Pakistan that is purple reflects that people were mostly civilians and children
    </li>
    

All this being said, the data comes from Dronestre.am which attempts to be honest but there’s no way that it can be complete nor totally accurate.