Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/ikarusmk/aicortex/docker-image-hardeningnpx skills add IkarusMK/AIcortex --skill docker-image-hardeninggit clone --depth 1 https://github.com/IkarusMK/AIcortexWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ikarusmk/aicortex/docker-image-hardening)<a href="https://agentmods.dev/skills/ikarusmk/aicortex/docker-image-hardening"><img src="https://agentmods.dev/badge/skills/ikarusmk/aicortex/docker-image-hardening.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00032 | $0.00304 |
| Opus 5 | $0.00016 | $0.00152 |
| Sonnet 5 | $0.00006 | $0.00061 |
| Haiku 4.5 | $0.00003 | $0.00030 |
Grade A, and why
docker-image-hardening scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Docker Image Hardening
When to use
Writing or reviewing a Dockerfile for anything that ships.
Checklist
- Pin the base to a digest or specific tag, not
latest. Prefer-slim/ distroless. - Multi-stage build: compile in a builder stage, copy only artifacts into the final image.
- Run as non-root: create a user,
USERit; drop to it beforeCMD. - No secrets in layers: never
COPY .envor bake tokens — pass at runtime / use a secret store. Layers are forever, even if a later layer deletes the file. - Minimize:
--no-install-recommends, clean apt lists in the sameRUN,.dockerignorethe build context. - Healthcheck so the orchestrator knows when it's actually up.
- Read-only where possible: mount data volumes explicitly; avoid writing into the image FS at runtime.
Smell tests
- Image > a few hundred MB for a small service → something heavy leaked in.
docker historyshows a secret or a huge dep layer → fix the Dockerfile, don't just squash.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 25 lines · 32 tokens per session scan A cf221a17f7b7
docker-image-hardening is a skill published in the GitHub repository IkarusMK/AIcortex (9 stars, last pushed 15d ago), licensed Apache-2.0. It adds 32 tokens to every session and 304 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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