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yolo-cage

AI coding agents that can't exfiltrate secrets

Details

External ID
46706796
Source
HN
Company
—
Product
yolo-cage
Website domain
github.com
Launched
Jan. 21, 2026
Cohort
—
Upvotes
60
Upvotes percentile
0.8353096179183136
Tags
—
Fetched at
Sept. 7, 2026, 9:25 p.m.
Updated at
Sept. 7, 2026, 9:25 p.m.

Description

I made this for myself, and it seemed like it might be useful to others. I'd love some feedback, both on the threat model and the tool itself. I hope you find it useful!Backstory: I've been using many agents in parallel as I work on a somewhat ambitious financial analysis tool. I was juggling agents working on epics for the linear solver, the persistence layer, the front-end, and planning for the second-generation solver. I was losing my mind playing whack-a-mole with the permission prompts. YOLO mode felt so tempting. And yet.Then it occurred to me: what if YOLO mode isn't so bad? Decision fatigue is a thing. If I could cap the blast radius of a confused agent, maybe I could just review once. Wouldn't that be safer?So that day, while my kids were taking a nap, I decided to see if I could put YOLO-mode Claude inside a sandbox that blocks exfiltration and regulates git access. The result is yolo-cage.Also: the AI wrote its own containment system from inside the system's own prototype. Which is either very aligned or very meta, depending on how you look at it.

Enrichment

Theme
AI agent frameworks and developer tools
Vertical
Security
Function
Agent / copilot
Audience
Developer
AI stance
AI-native
Project type
Hobby / open-source project
Normalized one-liner
ai coding agents with secret protection
Manually corrected
False

Could you build this?

No Preventing arbitrary AI coding agents from exfiltrating secrets requires deep security sandboxing, Linux kernel namespaces, seccomp filtering, and strict network/socket virtualization.

What it would actually take: A robust solution requires an isolated execution environment using microVMs (like Firecracker) or hard Linux containers configured with strict cgroups, user/network namespaces, and custom eBPF/seccomp syscall filtering. It must feature an egress-filtering proxy that performs deep packet inspection or TLS interception to prevent steganographic exfiltration and covert channels while preserving legitimate agent package installations.

Discussion

20 comments analyzed.

Competitors mentioned: cordum.io, docker-nixuser, vibebin, Claude Code CLI

Concerns raised: AI agents can hallucinate non-existent packages causing supply chain attacks, Build-time backdoor injection risk (weakened RNG, leaked keys, disabled SSL verification), Plaintext checks are not strong enough to prevent LLM violations of intent, AI-generated filters may not provide adequate protection if bypassed, Arbitrary command execution in production is higher risk than code changes

Feature requests: IDE integration support, Strict egress filtering via proxy for package fetching, Supervisor-mediated external access instead of direct agent connections, Network isolation rather than content-based filtering, Informative rejection messages explaining reasons for restrictions

Competitors

Other products that read as similar to this one — 337 launches clear the similarity bar, closest 8 shown.

Attention rank: #62 of 338 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 82 days after the earliest competitor.

Other launches for this product

Same idea, different domain

Nobody's really built a agent / copilot tool for Agriculture yet.