cloud-docker-registry
Skill26 starsChanged 31 days agoMITView on GitHub
Find and loot exposed container registries — image pull/push, secrets baked in layers, and registry misconfig. Load on exposed Docker registry (port 5000, /v2/), a registry URL, harbor/ECR/ GCR/ACR references, or "container registry". Signals: /v2/_catalog, registry:2, unauth pull/push.
- Reads credentials
2 other projects use a version of this.
Adopted by
Most recently taken up by
- NoorQureshi/roninword for word, first seen Oct 11, 2026
- NoorQureshi/security-skillsword for word, first seen Oct 11, 2026
Other versions2 projects use a version of this.
Word for word · 2
- NoorQureshi/security-skills★ 27100% same
- NoorQureshi/ronin★ 26100% same
Edited · 0
None found.
Wrote their own version · 0
None found.
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository207 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- ad-adcsSkill
- ad-dacl-abuseSkill
- ad-delegation-abuseSkill
- ad-kerberoastingSkill
- ad-pivot-arsenalSkill
- ai-agent-tool-abuseSkill
- ai-insecure-output-handlingSkill
- ai-jailbreakSkill
- ai-llm-dosSkill
- ai-mcp-securitySkill
- ai-model-extractionSkill
- ai-prompt-injectionSkill
- ai-rag-poisoningSkill
- ai-sensitive-data-disclosureSkill
- ai-supply-chainSkill
- ai-system-prompt-leakageSkill
- api-auth-attacksSkill
- api-bolaSkill
- api-fuzzingSkill
- api-graphqlSkill
- api-grpcSkill
- api-mass-assignmentSkill
- api-mongo-agg-facet-bypassSkill
- api-testing-checklistSkill
- api-versioningSkill
- automation-browserSkill
- automation-nuclei-templatesSkill
- automation-recon-pipelineSkill
- cloud-azureSkill
- cloud-container-escapeSkill
- cloud-docker-api-abuseSkill
- cloud-gcpSkill
- cloud-iam-privescSkill
- cloud-imds-ssrfSkill
- cloud-kubernetesSkill
- cloud-s3-exposureSkill
- code-review-cicdSkill
- code-review-cppSkill
- code-review-dangerous-sinksSkill
- code-review-dotnetSkill
- code-review-goSkill
- code-review-iacSkill
- code-review-javaSkill
- code-review-methodologySkill
- code-review-nodejsSkill
- code-review-phpSkill
- code-review-pythonSkill
- code-review-rubySkill
- code-review-rustSkill
- code-review-secrets-detectionSkill
- code-review-soliditySkill
- crypto-oracle-attacksSkill
- crypto-rsa-attacksSkill
- ctf-cryptoSkill
- ctf-forensicsSkill
- ctf-methodologySkill
- ctf-pwnSkill
- ctf-revSkill
- The first 60 shown.
The file
We split this skill into the rules it gives an agent
3 rules. About 0 are common, 2 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 37
Push (critical): if anonymous/weak push works, you can poison images (supply-chain) — prove with a harmless tag, don't tamper real images.
- Very specific: line 39
Cloud registries: test misconfigured ECR/GCR/ACR policies.
- Distinctive: line 44
Only pull what proves the issue.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Exposed container registry
When it applies
A Docker/OCI registry is reachable — a self-hosted registry (:5000, /v2/), or a cloud one
(ECR/GCR/ACR/Harbor) with weak auth. Images are goldmines: source, configs, and baked-in secrets.
Why it works
Registries are often deployed without auth ("internal only") or with over-broad pull access. Image
layers preserve everything added at build time — .env files, cloud keys, private source,
tokens — even if a later layer deletes them, earlier layers keep them.
Method
- Detect & enumerate:
curl -s https://registry:5000/v2/_catalog(repo list) and.../v2/<repo>/tags/list.registry:2banner / an unauth/v2/= exposed. - Pull images:
docker pull registry:5000/<repo>:<tag>orcrane pull(no docker daemon). Anonymous pull of private images is the finding. - Mine layers for secrets:
crane export/docker savethen scan withtrufflehog filesystem/ grep for keys,.env, kubeconfig, cloud creds (→ validate withcode-review-secrets-detection). - Push (critical): if anonymous/weak push works, you can poison images (supply-chain) — prove with a harmless tag, don't tamper real images.
- Cloud registries: test misconfigured ECR/GCR/ACR policies; leaked registry creds → pull private images.
Gotchas
- Scan all layers/history, not just the final image — secrets hide in intermediate layers.
- Anonymous push is critical (supply-chain); anonymous pull of private images is high — rate accordingly.
- Only pull what proves the issue; images can be large and contain real data — handle carefully.
Verify success
Anonymous/unauthorized pull of a private image, a live secret extracted from its layers, or a successful (harmless) push proving write access.
References
Docker registry API docs; crane/trufflehog; "hacking Docker registries" write-ups.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
Reviews can't be read right now.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

