r/linuxadmin 15m ago

tcp_mtu_probing, should I touch it or no?

Upvotes

Before anything, I really would appreciate answers from professionals without the interference of AI. I have been going back and forth the past few months with multiple AI models asking about this and every model gives a different answer. I really need a certain answer

I run a file storage server which faces the internet and serves customers, so high throughput is one of the goals I try to achieve on my servers

The past 6 months I've been studying the Linux kernel source code and sysctl docs to learn what each tunable parameter actually does instead of blindly pasting configurations from tuning guides and just hope that it makes things perfect

Now one of the points I'm stuck at is net.ipv4.tcp_mtu_probing

I see a lot of tuning guides suggest setting that to 1 or even 2 instead of the default 0

But if that's really recommended, why doesn't Linux set it to 1 by default instead of 0? I mean 1 seems like a better moderate value to set instead of disabling it completely

Although the below points kinda hold me back from altering tcp_mtu_probing but I might be wrong and that's why I opened this topic to ask for advice:

  1. Packet-layer path MTU discovery (TCP MTU probing, QUIC MTU probing, etc) just mask a real underlying MTU problem which should be fixed from its root instead of hiding it
  2. TCP MTU probing relies on packet loss and this can falsely make congestion control algorithms work worse and reduce the congestion window even if there's no real congestion
  3. Certain quirky firewalls may hate the fact that my server is sending data in variable packet sizes because of the MTU probing and hence they may drop the packets completely or block the connection entirely

Do my above points make sense or am I mistaken?


r/linuxadmin 3h ago

Investigating Unexpected Outbound Connections on Linux Servers

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0 Upvotes

r/linuxadmin 1h ago

AWS Kiro MCP prompt injection → unapproved RCE (no CVE, joint Intezer/Kodem research)

Upvotes

Based on the technical breakdown Intezer and Kodem Security published July 19, here's the architectural impact for anyone running Kiro or evaluating agentic IDEs.

Root cause: ~/.kiro/settings/mcp.json wasn't in Kiro's protected-paths list. The agent's fsWrite tool could modify it without a real approval gate, and the file auto-reloads on change, starting whatever MCP server it describes.

Attack: hidden color:#fff;font-size:1px text on a normal-looking doc page instructs Kiro to add an MCP server whose launch command is an inline Node.js exfil script. Developer only approved fetching the URL. Everything downstream — file write, server creation, code exec — happened silently.

Fixed in 0.11.130. No CVE issued. Worth noting this is the second time this exact file-write primitive has surfaced in Kiro since its 2025 launch — the first fix only covered Supervised mode, leaving default Autopilot exposed, which is what got hit this time.

Full writeup w/ attack-chain diagram and remediation list: [background link, footnote]

Anyone running agentic IDEs in Autopilot-equivalent modes in production — what's your actual control for file writes to tool/MCP config paths? Approval dialogs clearly aren't sufficient on their own.

https://www.techgines.com/post/aws-kiro-mcp-prompt-injection-vulnerability


r/linuxadmin 2h ago

Alright, time to give it a stab ....Sashiko ...https://github.com/sashiko-dev/sashiko ......Agentic review of Linux Kernel code changes

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0 Upvotes

r/linuxadmin 18h ago

How we reclaimed 120GB of disk space choked by local LLM caches

0 Upvotes

If you are running local LLMs, your hard drive is likely bleeding gigabytes without you realizing it. Between default model weights, duplicate quantization formats, and forgotten vector embeddings, local AI setups are silent storage hogs.

Here is how you can systematically track down and clean up the clutter directly from your terminal:

  • Locate hidden Hugging Face and Ollama model weights: By default, Hugging Face caches everything in ~/.cache/huggingface/hub and Ollama stores models under ~/.ollama/models. Run du -sh ~/.cache/huggingface/ to see how much space is currently locked up.
  • Prune redundant quantization formats and unused embedding databases: Review your downloaded models and delete redundant variations (like keeping both Q4_K_M and Q8_0 when you only use one). Clear out stale Chroma, FAISS, or Pinecone local vector database caches residing in your project directories.
  • Automate routine garbage collection: Set up a lightweight shell script to periodically check cache growth and alert you before your drive hits capacity.

Fore More Information

I put together the complete, production-ready automated cleanup script along with an interactive storage calculator to help map out your directories.

Direct links to the complete article.

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