Simon Willison’s Weblog

httpjail (via) Here's a promising new (experimental) project in the sandboxing space from Ammar Bandukwala at Coder. httpjail provides a Rust CLI tool for running an individual process against a custom configured HTTP proxy.

The initial goal is to help run coding agents like Claude Code and Codex CLI with extra rules governing how they interact with outside services. From Ammar's blog post that introduces the new tool, Fine-grained HTTP filtering for Claude Code:

httpjail implements an HTTP(S) interceptor alongside process-level network isolation. Under default configuration, all DNS (udp:53) is permitted and all other non-HTTP(S) traffic is blocked.

httpjail rules are either JavaScript expressions or custom programs. This approach makes them far more flexible than traditional rule-oriented firewalls and avoids the learning curve of a DSL.

Block all HTTP requests other than the LLM API traffic itself:

$ httpjail --js "r.host === 'api.anthropic.com'" -- claude "build something great"

I tried it out using OpenAI's Codex CLI instead and found this recipe worked:

brew upgrade rust
cargo install httpjail # Drops it in `~/.cargo/bin`
httpjail --js "r.host === 'chatgpt.com'" -- codex

Within that Codex instance the model ran fine but any attempts to access other URLs (e.g. telling it "Use curl to fetch simonwillison.net)" failed at the proxy layer.

This is still at a really early stage but there's a lot I like about this project. Being able to use JavaScript to filter requests via the --js option is neat (it's using V8 under the hood), and there's also a --sh shellscript option which instead runs a shell program passing environment variables that can be used to determine if the request should be allowed.

At a basic level it works by running a proxy server and setting HTTP_PROXY and HTTPS_PROXY environment variables so well-behaving software knows how to route requests.

It can also add a bunch of other layers. On Linux it sets up nftables rules to explicitly deny additional network access. There's also a --docker-run option which can launch a Docker container with the specified image but first locks that container down to only have network access to the httpjail proxy server.

It can intercept, filter and log HTTPS requests too by generating its own certificate and making that available to the underlying process.

I'm always interested in new approaches to sandboxing, and fine-grained network access is a particularly tricky problem to solve. This looks like a very promising step in that direction - I'm looking forward to seeing how this project continues to evolve.

# 19th September 2025, 9:57 pm / http, javascript, proxies, sandboxing, security, v8, rust, claude-code, codex-cli

GPT‑5-Codex and upgrades to Codex. OpenAI half-released a new model today: GPT‑5-Codex, a fine-tuned GPT-5 variant explicitly designed for their various AI-assisted programming tools.

Update: OpenAI call it a "version of GPT-5", they don't explicitly describe it as a fine-tuned model. Calling it a fine-tune was my mistake here.

I say half-released because it's not yet available via their API, but they "plan to make GPT‑5-Codex available in the API soon".

I wrote about the confusing array of OpenAI products that share the name Codex a few months ago. This new model adds yet another, though at least "GPT-5-Codex" (using two hyphens) is unambiguous enough not to add to much more to the confusion.

At this point it's best to think of Codex as OpenAI's brand name for their coding family of models and tools.

The new model is already integrated into their VS Code extension, the Codex CLI and their Codex Cloud asynchronous coding agent. I'd been calling that last one "Codex Web" but I think Codex Cloud is a better name since it can also be accessed directly from their iPhone app.

Codex Cloud also has a new feature: you can configure it to automatically run code review against specific GitHub repositories (I found that option on chatgpt.com/codex/settings/code-review) and it will create a temporary container to use as part of those reviews. Here's the relevant documentation.

Some documented features of the new GPT-5-Codex model:

• Specifically trained for code review, which directly supports their new code review feature.
• "GPT‑5-Codex adapts how much time it spends thinking more dynamically based on the complexity of the task." Simple tasks (like "list files in this directory") should run faster. Large, complex tasks should use run for much longer - OpenAI report Codex crunching for seven hours in some cases!
• Increased score on their proprietary "code refactoring evaluation" from 33.9% for GPT-5 (high) to 51.3% for GPT-5-Codex (high). It's hard to evaluate this without seeing the details of the eval but it does at least illustrate that refactoring performance is something they've focused on here.
• "GPT‑5-Codex also shows significant improvements in human preference evaluations when creating mobile websites" - in the past I've habitually prompted models to "make it mobile-friendly", maybe I don't need to do that any more.
• "We find that comments by GPT‑5-Codex are less likely to be incorrect or unimportant" - I originally misinterpreted this as referring to comments in code but it's actually about comments left on code reviews.

The system prompt for GPT-5-Codex in Codex CLI is worth a read. It's notably shorter than the system prompt for other models - here's a diff.

Here's the section of the updated system prompt that talks about comments:

Add succinct code comments that explain what is going on if code is not self-explanatory. You should not add comments like "Assigns the value to the variable", but a brief comment might be useful ahead of a complex code block that the user would otherwise have to spend time parsing out. Usage of these comments should be rare.

Theo Browne has a video review of the model and accompanying features. He was generally impressed but noted that it was surprisingly bad at using the Codex CLI search tool to navigate code. Hopefully that's something that can fix with a system prompt update.

Finally, can it drew a pelican riding a bicycle? Without API access I instead got Codex Cloud to have a go by prompting:

Generate an SVG of a pelican riding a bicycle, save as pelican.svg

Here's the result:

# 15th September 2025, 6:55 pm / ai, openai, generative-ai, llms, ai-assisted-programming, pelican-riding-a-bicycle, llm-release, coding-agents, gpt-5, codex-cli

Load Llama-3.2 WebGPU in your browser from a local folder (via) Inspired by a comment on Hacker News I decided to see if it was possible to modify the transformers.js-examples/tree/main/llama-3.2-webgpu Llama 3.2 chat demo (online here, I wrote about it last November) to add an option to open a local model file directly from a folder on disk, rather than waiting for it to download over the network.

I posed the problem to OpenAI's GPT-5-enabled Codex CLI like this:

git clone https://github.com/huggingface/transformers.js-examples
cd transformers.js-examples/llama-3.2-webgpu
codex

Then this prompt:

Modify this application such that it offers the user a file browse button for selecting their own local copy of the model file instead of loading it over the network. Provide a "download model" option too.

Codex churned away for several minutes, even running commands like curl -sL https://raw.githubusercontent.com/huggingface/transformers.js/main/src/models.js | sed -n '1,200p' to inspect the source code of the underlying Transformers.js library.

After four prompts total (shown here) it built something which worked!

To try it out you'll need your own local copy of the Llama 3.2 ONNX model. You can get that (a ~1.2GB) download) like so:

git lfs install
git clone https://huggingface.co/onnx-community/Llama-3.2-1B-Instruct-q4f16

Then visit my llama-3.2-webgpu page in Chrome or Firefox Nightly (since WebGPU is required), click "Browse folder", select that folder you just cloned, agree to the "Upload" confirmation (confusing since nothing is uploaded from your browser, the model file is opened locally on your machine) and click "Load local model".

Here's an animated demo (recorded in real-time, I didn't speed this up):

I pushed a branch with those changes here. The next step would be to modify this to support other models in addition to the Llama 3.2 demo, but I'm pleased to have got to this proof of concept with so little work beyond throwing some prompts at Codex to see if it could figure it out.

According to the Codex /status command this used 169,818 input tokens, 17,112 output tokens and 1,176,320 cached input tokens. At current GPT-5 token pricing ($1.25/million input, $0.125/million cached input, $10/million output) that would cost 53.942 cents, but Codex CLI hooks into my existing $20/month ChatGPT Plus plan so this was bundled into that.

# 8th September 2025, 8:53 pm / javascript, ai, generative-ai, llama, local-llms, llms, ai-assisted-programming, transformers-js, webgpu, llm-pricing, vibe-coding, gpt-5, codex-cli

openai/codex. Just released by OpenAI, a "lightweight coding agent that runs in your terminal". Looks like their version of Claude Code, though unlike Claude Code Codex is released under an open source (Apache 2) license.

Here's the main prompt that runs in a loop, which starts like this:

You are operating as and within the Codex CLI, a terminal-based agentic coding assistant built by OpenAI. It wraps OpenAI models to enable natural language interaction with a local codebase. You are expected to be precise, safe, and helpful.

You can:
- Receive user prompts, project context, and files.
- Stream responses and emit function calls (e.g., shell commands, code edits).
- Apply patches, run commands, and manage user approvals based on policy.
- Work inside a sandboxed, git-backed workspace with rollback support.
- Log telemetry so sessions can be replayed or inspected later.
- More details on your functionality are available at codex --help

The Codex CLI is open-sourced. Don't confuse yourself with the old Codex language model built by OpenAI many moons ago (this is understandably top of mind for you!). Within this context, Codex refers to the open-source agentic coding interface. [...]

I like that the prompt describes OpenAI's previous Codex language model as being from "many moons ago". Prompt engineering is so weird.

Since the prompt says that it works "inside a sandboxed, git-backed workspace" I went looking for the sandbox. On macOS it uses the little-known sandbox-exec process, part of the OS but grossly under-documented. The best information I've found about it is this article from 2020, which notes that man sandbox-exec lists it as deprecated. I didn't spot evidence in the Codex code of sandboxes for other platforms.

# 16th April 2025, 5:25 pm / cli, macos, open-source, sandboxing, ai, openai, prompt-engineering, generative-ai, llms, ai-assisted-programming, ai-agents, coding-agents, claude-code, codex-cli