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BD hunt-k8s

Hunt Kubernetes & Docker — API anonymous access, kubelet 10250 exec (SPDY/WebSocket, NOT plain POST) and the simpler /run primitive, etcd 2379 unauth, dashboard skip-login, RBAC misconfig, secret/SA-token abuse, docker.sock host escape, runc/container-escape (Leaky Vessels CVE-2024-21626), API-server-mediated nodes/proxy RCE, EphemeralContainers node-shell, bound/projected SA-token audience+expiry abuse, admission-controller bypass, Helm/Tiller remnants. Use when target runs containerized infra, exposes K8s ports (6443/10250/10255/2379/8443), or cloud metadata reveals K8s service accounts.

elementalsouls/Claude-BugHunter Agent Skills author: elementalsouls 1 file body ≈ 4 813 tokens Open the sourcegithub.com↗ analyzed 2 h ago

Hunt Kubernetes & Docker — API anonymous access, kubelet 10250 exec (SPDY/WebSocket, NOT plain POST) and the simpler /run primitive, etcd 2379 unauth…

As a process D 45/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationDockerKubernetesAWSInfrastructuretype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
93
Quality 40%
80
Run on models
none yet
Process rating
D
45/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 7

    ✓ No critical or high findings

    Medium and low: 7
    • low Secrets in code secret-high-entropy-token SKILL.md:52
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      TOK=$(curl -s -X PUT "http://169.254.169.254/latest/api/token" -H "X-aw…ds: 60") # IMDSv2
      quoted
    • low Exfiltration net-credential-use SKILL.md:139
      Credential used in a network call (verify the destination is the intended service) (documentation of a security skill)
      NODE=$(curl -sk -H "Authorization: Bearer $TOKEN" "$SRV/api/v1/nodes" | grep -o '"name":"[^"]*"' | head -1 | cut -d'"' -f4)
      security skill
    • low Exfiltration net-credential-use SKILL.md:142
      Credential used in a network call (verify the destination is the intended service) (documentation of a security skill)
      curl -sk -X POST -H "Authorization: Bearer $TOKEN" \
      security skill
    • low Exfiltration net-credential-use SKILL.md:146
      Credential used in a network call (verify the destination is the intended service) (documentation of a security skill)
      curl -sk -H "Authorization: Bearer $TOKEN" "$SRV/api/v1/nodes/$NODE/proxy/pods"
      security skill
    • low Exfiltration net-credential-use SKILL.md:193
      Credential used in a network call (verify the destination is the intended service) (documentation of a security skill)
      curl -sk "$API/api/v1/namespaces/$NS/secrets" -H "Authorization: Bearer $TOKEN"
      security skill
    • low Exfiltration net-credential-use SKILL.md:246
      Credential used in a network call (verify the destination is the intended service) (documentation of a security skill)
      curl -sk "$SRV/apis/admi….io/v1/validatingwebhookconfigurations" -H "Authorization: Bearer $TOKEN"
      security skill
    • low Risky intent intent-offensive-security SKILL.md:258
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      | Kubelet 10250 `/run` | exec in any pod → steal SA token → API | Cluster privilege escalation |

    Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "sources"
    • note frontmatter-key unknown frontmatter key "report_count"

    Process rating: all ten parameters 45/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 6 mutating operations with no state check
    • 55Failures and branches. 1 branches
    • 60Tools and files. Uses tools (bash, web, node) that frontmatter does not declare
    • 70Execution cost. Instruction body is 4813 tokens
    • 85Steps. 33 steps, 1 vague phrases
    • 100Consistency. Name and required fields are in place
    • low 14 top-level sections: this looks like several domains in one skill
    • low The response is described with custom markup (6 tags): a typed call is more reliable

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • -2localhost URLs: will not work for another user
    • +1No license
    • +2Single-language instructions
    • +3Description length 596: enough signal without eating the budget
    • +4Structure: 15 headings
    • +3Step-by-step instructions: 33 items
    • +4Has examples (9 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.