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 skills add UnboundCompute/security-agent-skills --skill hunting-kubelet-and-node-api-exposuregit clone --depth 1 https://github.com/UnboundCompute/security-agent-skillsWrote 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/unboundcompute/security-agent-skills/hunting-kubelet-and-node-api-exposure)<a href="https://agentmods.dev/skills/unboundcompute/security-agent-skills/hunting-kubelet-and-node-api-exposure"><img src="https://agentmods.dev/badge/skills/unboundcompute/security-agent-skills/hunting-kubelet-and-node-api-exposure/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/unboundcompute/security-agent-skills/hunting-kubelet-and-node-api-exposure"><img src="https://agentmods.dev/badge/skills/unboundcompute/security-agent-skills/hunting-kubelet-and-node-api-exposure.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00171 | $0.01926 |
| Opus 5.5 | $0.00068 | $0.00770 |
| Sonnet 5.5 | $0.00034 | $0.00385 |
| Haiku 4.5 | $0.00017 | $0.00193 |
Grade A, and why
hunting-kubelet-and-node-api-exposure 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Hunting kubelet and node API exposure: the control plane on every node
Every Kubernetes node runs a kubelet, and the kubelet is a powerful local API: it can list the pods on the node, stream their logs, and exec into their containers. That makes each node a small control plane, and the kubelet's authentication and authorization are the only thing between a caller who can reach it and node-level control over every pod scheduled there. The exposures are concrete: a kubelet configured to allow anonymous requests, a read-only port that serves pod and node data without auth, an authorization mode that authenticates the caller but then allows the action anyway, and reachability from a pod or the network that should never have existed. A caller who reaches an under-authenticated kubelet can read secrets from other pods' environments, exec into neighbors, and pivot. You hunt this by finding node endpoints that are reachable and testing whether their authentication actually refuses an unauthorized caller.
When to use
- Kubelet or other node-local endpoints may be reachable from pods or the surrounding network.
- The kubelet may allow anonymous requests or expose a read-only port without authentication.
- The kubelet's authorization mode may authenticate a caller without restricting the action.
Scope check
Test node endpoints only on clusters and nodes you own or are authorized to assess, on non-production nodes. Reaching a kubelet can read other pods' data and exec into containers, so use a non-production node and stop at proof rather than pivoting into neighboring pods. If you can't name the authorization, stop.
The loop
- Establish who should reach node endpoints first. Name what is supposed to talk to the kubelet and node services: the control plane, specific node agents, nothing from workload pods. This is the false-positive killer: a kubelet that requires authentication, uses an authorization mode that restricts actions, disables anonymous access and the read-only port, and is unreachable from pods is correctly closed. Name the intended callers, then find endpoints reachable beyond them.
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.
- 1mo ago First seen · 135 lines · 171 tokens per session scan A 62c1126522e1
hunting-kubelet-and-node-api-exposure is a skill published in the GitHub repository UnboundCompute/security-agent-skills (5 stars, last pushed 1mo ago), licensed MIT. It adds 171 tokens to every session and 1,926 once invoked, about $0.0007 per session on Opus 5.5. 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 2026-09-05.
Other skills, from other repositories
cloud-security-engineer
Cloud Security Engineer role bundle for cloud security posture management, IaC review, container security, and identity governance across AWS, Azure, and GCP. Orchestrates cloud-specific posture reviews and zero trust program assessments. Auto-invoked when the user needs help with cloud security configuration, IaC…
azure-review
Performs an Azure security posture review against the CIS Microsoft Azure Foundations Benchmark v2.1.0. Auto-invoked when reviewing Azure infrastructure, Entra ID configurations, NSG rules, Defender for Cloud settings, or Key Vault access policies. Walks through all nine benchmark sections, evaluates each…
gcp-review
Performs a GCP security posture review against the CIS Google Cloud Platform Foundation Benchmark v2.0.0. Auto-invoked when reviewing GCP infrastructure, IAM bindings, VPC firewall rules, Cloud Audit Logs, or GCS bucket security. Walks through all seven benchmark sections, evaluates each recommendation, and produces a…
aws-review
Performs an AWS security posture review against the CIS Amazon Web Services Foundations Benchmark v3.0.0. Auto-invoked when reviewing AWS infrastructure, IAM policies, S3 configurations, CloudTrail settings, VPC security groups, or RDS encryption. Walks through all five benchmark sections, evaluates each…
prodcheck-review
Review this codebase against the prodcheck pre-production checklists — security, performance, scale, integrations, post-launch readiness and people. Use when asked to check whether a project is ready to ship, to audit an area before launch, or to work through a specific checklist. Produces evidence with file:line…
cloud-pivot-finder
Maps cloud infrastructure from domains and identifies pivot paths from external to cloud internals. Detects cloud providers, enumerates S3/GCS/Azure storage, finds subdomain takeover opportunities, discovers serverless functions, CI/CD exposure, and IaC leaks. Use when user asks for "cloud security", "S3 enumeration"…