Session LogsSession #53
live · 2026-06-20 19:18
info — happy-starses_1626d0c17ffe1HoK…
Provider
openai
Model
gpt-5.5
Messages
5
Tools
2
Tool Calls
13
LLM Calls
7
tools2 unique
bash read
conversation5 messages
U
User
hey
A
Assistant
gpt-5.5 | agent=build | finish=stop
Hey. What would you like to work on?
U
User
what is running on this machine
A
Assistant
gpt-5.5 | agent=build | finish=tool-calls
I’ll inspect running processes and listening services so you can see what is active on the machine.
bashcompletedLists currently running processes▶
bashcompletedLists listening network services▶
A
Assistant
gpt-5.5 | agent=build | finish=stop
Key things running: - `caddy` reverse proxy on public ports `80`, `443`, `9996`, plus admin on `127.0.0.1:2019` - `sshd` on port `22` - Docker stack: `dockerd` and `containerd` - `opencode serve` on `127.0.0.1:4096` - `ghostty-web-server` on public port `8080` - `glances` monitoring server on `127.0.0.1:61209` - Node app `/srv/drive.gulasch.site/server.js` on `127.0.0.1:8097` - Python app `conversation_app.py` on `127.0.0.1:8096` - Python app `richard_app.py` on `127.0.0.1:8095` - Multiple `baresip` SIP clients listening on ports like `4444`, `4445`, and several dynamic TCP/UDP ports - Normal system services: `systemd`, `cron`, `rsyslogd`, `chronyd`, `systemd-resolved`, `systemd-networkd`, `qemu-ga`, `snapd` Highest CPU process right now appears to be: - `opencode serve`, PID `62381`, about `8.6% CPU`, running since Jun 05.
U
User
more detailed
A
Assistant
gpt-5.5 | agent=build | finish=tool-calls
▶ Reasoning
**Considering system details**

I think I need to provide more details about running some system commands like `docker ps`, `systemctl`, and checking the `caddy` configuration. It feels like I might need to gather more information for clarity. There are tools that could help, but I’ll have to think about which ones are necessary for a better understanding of the system status. Let’s figure out the best approach!
I’ll collect a fuller service inventory: containers, systemd units, process tree, ports with owning commands, and basic resource usage.
bashcompletedLists running Docker containers▶
bashcompletedLists running systemd services▶
bashcompletedShows process tree with arguments▶
bashcompletedLists processes sorted by CPU▶
bashcompletedLists processes sorted by memory▶
A
Assistant
gpt-5.5 | agent=build | finish=tool-calls
▶ Reasoning
**Exploring Caddy routes**

I need to gather detailed information about Caddy routes, possibly looking into service files. First, I should read the Caddyfile located at /etc/caddy/. I also want to check the outputs using systemctl to see details from relevant units and look at the existing ss output. I’m considering whether I actually need to involve containers in this process. Let's get to it and figure out the best way to approach these tasks!
Docker is installed and running, but there are currently no running containers. The interesting workload is all systemd-managed processes plus a few SIP helper processes.
bashcompletedShows key service unit definitions▶
bashcompletedLists listening ports and owners▶
bashcompletedShows uptime and load averages▶
bashcompletedShows current memory usage▶
bashcompletedShows filesystem disk usage▶
A
Assistant
gpt-5.5 | agent=build | finish=tool-calls
▶ Reasoning
**Considering password sensitivity**

I’m thinking I need to bring up the importance of password sensitivity because it seems like there's a risk of exposure here. I should avoid repeating the password in the output, especially since the user has the same machine. It’s crucial not to expose any secrets in the final output. I might want to note that it includes a plaintext password in the service, and maybe I should look into reading the caddyfile as needed.
I found the Ghostty service has a plaintext password set in its systemd unit environment; I won’t repeat it here, but it’s visible to root via `systemctl cat ghostty-web-server`.
readcompletedetc/caddy/Caddyfile▶
A
Assistant
gpt-5.5 | agent=build | finish=stop
▶ Reasoning
**Refining for detail**

I need to finalize a concise summary that includes public mappings. I should definitely avoid mentioning any docker containers, as that's not relevant here. Instead, I want to focus on using data effectively in my response. It's important to make sure everything is clear and straightforward for the user while ensuring they have all the necessary information. I'll aim for a neat and professional presentation that meets their needs.
**Summary** This machine is a public-facing server with Caddy in front of several local apps, SIP bots, SSH, Docker installed but idle, and a browser terminal service. **Public Services** - `80/tcp`, `443/tcp`, `443/udp`: `caddy` - `22/tcp`: `sshd` - `8080/tcp`: `ghostty-web-server` - `9996/tcp`: `caddy`, plain HTTP reverse proxy to OpenCode - `4444/tcp`, `4445/tcp`: `baresip` SIP-related listeners - Several dynamic public TCP/UDP ports owned by `baresip` **Caddy Routes** From `/etc/caddy/Caddyfile`: - `gulasch.site` -> `127.0.0.1:4096` -> OpenCode - `richard.gulasch.site` -> `127.0.0.1:8095` -> `richard_app.py` - `conversation.gulasch.site` -> `127.0.0.1:8096` -> `conversation_app.py` - `drive.gulasch.site` -> `127.0.0.1:8097` -> Node app - `terminal.gulasch.site` -> `127.0.0.1:8080` -> Ghostty web terminal - `chat.gulasch.site` -> static files in `/var/www/chat.gulasch.site` - `:9996` -> `127.0.0.1:4096` -> OpenCode over unencrypted HTTP **Main App Processes** - `opencode.service` - PID `62381` - Command: `/root/.opencode/bin/opencode serve --hostname 127.0.0.1 --port 4096` - Resource use: about `8.6% CPU`, `~616 MB RSS` - Publicly reachable through `gulasch.site` and `:9996` - `ghostty-web-server.service` - PID `78564` - Command: `/opt/ghostty-web-server/dist/ghostty-web-server-linux-x64` - Port: `8080` - Publicly reachable directly on `:8080` and through `terminal.gulasch.site` - Has a plaintext password in the systemd unit environment - `gulasch-drive.service` - PID `80414` - Command: `/usr/bin/node /srv/drive.gulasch.site/server.js` - Local port: `127.0.0.1:8097` - Public via `drive.gulasch.site` - `conversation-sip.service` - PID `84437` - Command: `python3 conversation_app.py` - Local port: `127.0.0.1:8096` - Child process: `baresip -4 -f /opt/conversation-sip/baresip-runtime -v` - Public via `conversation.gulasch.site` - `rickroll-sip.service` - PID `61966` - Command: `python3 richard_app.py` - Local port: `127.0.0.1:8095` - Child process: `baresip -4 -f /opt/rickroll-sip/baresip-runtime -v` - Public via `richard.gulasch.site` **Monitoring / Admin** - `glances.service` - PID `33676` - Command: `/usr/bin/glances -s -B 127.0.0.1` - Local port: `127.0.0.1:61209` - `caddy` admin API - Local port: `127.0.0.1:2019` **Docker** - `docker.service` and `containerd.service` are running. - `docker ps` shows no running containers. **System State** - Uptime: `2 days, 2:54` - Load average: `0.38, 0.23, 0.20` - Memory: `15 GiB total`, `1.8 GiB used`, `13 GiB available` - Disk `/`: `301G total`, `9.9G used`, `278G available`, `4% used` - Swap: none configured **Notable Risk** - `:9996` exposes OpenCode over plain HTTP to all interfaces. - `ghostty-web-server` listens publicly on `:8080`. - The Ghostty service stores its password directly in the unit environment.
timeline27 events
service=session.prompt session.id=ses_1626d0c17ffe1HoKukxQ967w8v step=0 loop
service=session.processor session.id=ses_1626d0c17ffe1HoKukxQ967w8v messageID=msg_e9d92f47400136Z71nMftjNwM4 process
service=llm providerID=openai modelID=gpt-5.5 session.id=ses_1626d0c17ffe1HoKukxQ967w8v small=false agent=build mode=primary stream
service=session.prompt session.id=ses_1626d0c17ffe1HoKukxQ967w8v step=1 loop
service=session.prompt session.id=ses_1626d0c17ffe1HoKukxQ967w8v exiting loop
service=session.prompt session.id=ses_1626d0c17ffe1HoKukxQ967w8v step=0 loop
service=session.processor session.id=ses_1626d0c17ffe1HoKukxQ967w8v messageID=msg_e9d9335e7001nQOK0YyXnEC3dR process
service=llm providerID=openai modelID=gpt-5.5 session.id=ses_1626d0c17ffe1HoKukxQ967w8v small=false agent=build mode=primary stream
service=session.prompt session.id=ses_1626d0c17ffe1HoKukxQ967w8v step=1 loop
service=session.processor session.id=ses_1626d0c17ffe1HoKukxQ967w8v messageID=msg_e9d934339001rI0Bcz351fotk6 process
service=llm providerID=openai modelID=gpt-5.5 session.id=ses_1626d0c17ffe1HoKukxQ967w8v small=false agent=build mode=primary stream
service=session.prompt session.id=ses_1626d0c17ffe1HoKukxQ967w8v step=2 loop
service=session.prompt session.id=ses_1626d0c17ffe1HoKukxQ967w8v exiting loop
service=session.prompt session.id=ses_1626d0c17ffe1HoKukxQ967w8v step=0 loop
service=session.processor session.id=ses_1626d0c17ffe1HoKukxQ967w8v messageID=msg_e9d949c92001x2SuLth98A4trG process
service=llm providerID=openai modelID=gpt-5.5 session.id=ses_1626d0c17ffe1HoKukxQ967w8v small=false agent=build mode=primary stream
service=session.prompt session.id=ses_1626d0c17ffe1HoKukxQ967w8v step=1 loop
service=session.processor session.id=ses_1626d0c17ffe1HoKukxQ967w8v messageID=msg_e9d94b9ae0019wAY33iSnAjkX5 process
service=llm providerID=openai modelID=gpt-5.5 session.id=ses_1626d0c17ffe1HoKukxQ967w8v small=false agent=build mode=primary stream
service=session.prompt session.id=ses_1626d0c17ffe1HoKukxQ967w8v step=2 loop
service=session.processor session.id=ses_1626d0c17ffe1HoKukxQ967w8v messageID=msg_e9d94d5f7001yKFBkbWKBaDuPJ process
service=llm providerID=openai modelID=gpt-5.5 session.id=ses_1626d0c17ffe1HoKukxQ967w8v small=false agent=build mode=primary stream
service=session.prompt session.id=ses_1626d0c17ffe1HoKukxQ967w8v step=3 loop
service=session.processor session.id=ses_1626d0c17ffe1HoKukxQ967w8v messageID=msg_e9d94ebf7001eSSU7iR8UHO63F process
service=llm providerID=openai modelID=gpt-5.5 session.id=ses_1626d0c17ffe1HoKukxQ967w8v small=false agent=build mode=primary stream
service=session.prompt session.id=ses_1626d0c17ffe1HoKukxQ967w8v step=4 loop
service=session.prompt session.id=ses_1626d0c17ffe1HoKukxQ967w8v exiting loop
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openai gpt-5.5
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