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 Youngmaidainon/Agent-Level-Up --skill analyzing-kubernetes-audit-logsgit clone --depth 1 https://github.com/Youngmaidainon/Agent-Level-UpWrote 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/youngmaidainon/agent-level-up/analyzing-kubernetes-audit-logs)<a href="https://agentmods.dev/skills/youngmaidainon/agent-level-up/analyzing-kubernetes-audit-logs"><img src="https://agentmods.dev/badge/skills/youngmaidainon/agent-level-up/analyzing-kubernetes-audit-logs/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/youngmaidainon/agent-level-up/analyzing-kubernetes-audit-logs"><img src="https://agentmods.dev/badge/skills/youngmaidainon/agent-level-up/analyzing-kubernetes-audit-logs.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 | $0.00071 | $0.00555 |
| Opus 5 | $0.00036 | $0.00278 |
| Sonnet 5 | $0.00014 | $0.00111 |
| Haiku 4.5 | $0.00007 | $0.00056 |
Grade A, and why
analyzing-kubernetes-audit-logs 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 12d 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.
This is a copy
80% identical to analyzing-kubernetes-audit-logs — 32 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Analyzing Kubernetes Audit Logs
When to Use
- When investigating security incidents that require analyzing kubernetes audit logs
- When building detection rules or threat hunting queries for this domain
- When SOC analysts need structured procedures for this analysis type
- When validating security monitoring coverage for related attack techniques
Prerequisites
- Familiarity with container security concepts and tools
- Access to a test or lab environment for safe execution
- Python 3.8+ with required dependencies installed
- Appropriate authorization for any testing activities
Instructions
Parse Kubernetes audit log files (JSON lines format) to detect security-relevant events including unauthorized access, privilege escalation, and data exfiltration.
import json
with open("/var/log/kubernetes/audit.log") as f:
for line in f:
event = json.loads(line)
verb = event.get("verb")
resource = event.get("objectRef", {}).get("resource")
user = event.get("user", {}).get("username")
if verb == "create" and resource == "pods/exec":
print(f"Pod exec by {user}")
Key events to detect:
- pods/exec and pods/attach (shell into containers)
- secrets access (get/list/watch)
- clusterrolebindings creation (RBAC escalation)
- Privileged pod creation
- Anonymous or system:unauthenticated access
Examples
# Detect secret enumeration
if verb in ("get", "list") and resource == "secrets":
print(f"Secret access: {user} -> {event['objectRef'].get('name')}")
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 83 lines · 71 tokens per session scan A 76c6fec70d8e
analyzing-kubernetes-audit-logs is a skill published in the GitHub repository Youngmaidainon/Agent-Level-Up (3 stars, last pushed 17d ago), licensed MIT. It adds 71 tokens to every session and 555 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 80% identical to analyzing-kubernetes-audit-logs, differing in 32 lines, and is treated as a copy.
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Parses Kubernetes API server audit logs (JSON lines) to detect exec-into-pod, secret access, RBAC modifications, privileged pod creation, and anonymous API access. Builds threat detection rules from audit event patterns. Use when investigating Kubernetes cluster compromise or building k8s-specific SIEM detection rules.
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