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analyzing-kubernetes-audit-logs

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.

59

Quality

68%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./skills/analyzing-kubernetes-audit-logs/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Discovery

100%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

This is an excellent skill description that clearly articulates specific capabilities (parsing K8s audit logs for five distinct threat patterns), includes rich natural trigger terms covering both full and abbreviated forms, and provides explicit 'Use when' guidance. It occupies a well-defined niche that minimizes conflict risk with other skills.

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions: parsing Kubernetes API server audit logs, detecting exec-into-pod, secret access, RBAC modifications, privileged pod creation, anonymous API access, and building threat detection rules from audit event patterns.

3 / 3

Completeness

Clearly answers both what (parses K8s audit logs to detect specific threat patterns and builds detection rules) and when ('Use when investigating Kubernetes cluster compromise or building k8s-specific SIEM detection rules').

3 / 3

Trigger Term Quality

Includes strong natural keywords users would say: 'Kubernetes', 'audit logs', 'exec-into-pod', 'secret access', 'RBAC', 'privileged pod', 'k8s', 'SIEM detection rules', 'cluster compromise'. Good coverage of both full names and abbreviations (Kubernetes/k8s).

3 / 3

Distinctiveness Conflict Risk

Highly distinctive niche targeting Kubernetes API server audit logs specifically, with clear triggers around k8s security investigation and SIEM rule building. Unlikely to conflict with general log analysis or other security skills.

3 / 3

Total

12

/

12

Passed

Implementation

37%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The skill provides a reasonable starting point with executable Python for basic Kubernetes audit log parsing, but it falls short on completeness and workflow structure. It promises coverage of 5 detection categories and SIEM rule building but only delivers concrete code for 2 categories, with no investigation workflow, no validation steps, and no structured output format for detection results.

Suggestions

Add executable code examples for all 5 listed detection categories (RBAC escalation, privileged pod creation, anonymous access) rather than just listing them as bullet points.

Define a clear multi-step investigation workflow: 1) validate log format, 2) parse and filter events, 3) run detection rules, 4) correlate findings, 5) output structured results—with explicit validation at each step.

Remove the generic 'Prerequisites' and 'When to Use' sections or compress them to 1-2 lines; replace with actionable content like expected audit log field schemas or example SIEM rule output formats.

Add a structured output format (e.g., JSON schema for detection findings) so downstream consumers know what to expect from the analysis.

DimensionReasoningScore

Conciseness

The 'When to Use' and 'Prerequisites' sections contain generic filler (e.g., 'Familiarity with container security concepts,' 'Appropriate authorization for any testing activities') that Claude already knows and doesn't need. The core instructions are reasonably lean but surrounded by unnecessary padding.

2 / 3

Actionability

The main code snippet is executable and concrete for the basic exec detection case, but the list of 5 key event types only provides detection code for 2 of them (pods/exec and secrets). Privileged pod creation detection, RBAC escalation detection, and anonymous access detection are listed but lack concrete code or field-level details to implement them.

2 / 3

Workflow Clarity

There is no clear multi-step workflow for analyzing audit logs end-to-end. The skill lists detection categories but doesn't sequence them into an investigation process, provide validation steps (e.g., confirming log format, handling malformed lines), or describe what to do after detections are found. For a threat investigation skill, the lack of any feedback loop or structured procedure is a significant gap.

1 / 3

Progressive Disclosure

The content is organized into sections (When to Use, Prerequisites, Instructions, Examples) which provides some structure, but all content is inline with no references to supporting files. For a skill covering 5+ detection categories plus threat hunting and SIEM rule building, the content is too thin rather than appropriately split—it would benefit from either more inline depth or references to detailed detection rule files.

2 / 3

Total

7

/

12

Passed

Validation

90%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation10 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

10

/

11

Passed

Repository
mukul975/Anthropic-Cybersecurity-Skills
Reviewed

Table of Contents

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