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logginglogging 开发

Agent Skill

logging 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

250

周安装

10

GitHub Stars

9

下载量

81
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:logging(logging 开发)
来源仓库:https://github.com/florianbuetow/claude-code
仓库路径:skills/logging
安装命令:
npx skills add https://github.com/florianbuetow/claude-code --skill logging
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/florianbuetow/claude-code --skill logging

简介

用于查找、检索和筛选相关信息。logging 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

  • 适合根据关键词快速定位候选结果。
  • 可结合来源仓库继续核验具体用法。
  • 安装前建议确认权限和维护状态。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。
  • 注意是否会触发联网或文件读写。

SKILL.md

Security Logging and Monitoring Failures (A09:2021)

Analyze source code for security logging and monitoring failures including missing audit logging for security events, sensitive data in logs, log injection, absence of alerting on failures, logs only stored locally, and missing tamper protection.

This is the most architectural OWASP category. Scanners provide minimal coverage for logging failures, so Claude's analysis of code patterns, logging configuration, and event coverage is the primary value of this skill.

Supported Flags

Read ../../shared/schemas/flags.md for the full flag specification. This skill supports all cross-cutting flags. Key flags for this skill:

  • --scope determines which files to analyze (default: changed)
  • --depth standard reads code and checks logging around security-critical operations
  • --depth deep traces security event flows to verify each produces an audit log entry
  • --severity filters output (logging gaps are often medium, sensitive data in logs is high)

Framework Context

Read ../../shared/frameworks/owasp-top10-2021.md, section A09:2021 - Security Logging and Monitoring Failures, for the full category description, common vulnerabilities, and prevention guidance.

Key CWEs in scope:

  • CWE-117: Improper Output Neutralization for Logs (log injection)
  • CWE-223: Omission of Security-Relevant Information
  • CWE-532: Insertion of Sensitive Information into Log File
  • CWE-778: Insufficient Logging
  • CWE-779: Logging of Excessive Data

Detection Patterns

Read references/detection-patterns.md for the full catalog of code patterns, search heuristics, language-specific examples, and false positive guidance.

Workflow

1. Determine Scope

Parse flags and resolve the file list per ../../shared/schemas/flags.md. Filter to files likely to contain logging logic or security-critical operations:

  • Authentication modules (**/auth/**, **/login/**, **/session/**)
  • Access control and authorization (**/middleware/**, **/guards/**, **/policies/**)
  • Logging configuration (**/logging/**, **/logger/**, **/*log*config*)
  • Error handlers (**/errors/**, **/exceptions/**, **/handlers/**)
  • Route/controller definitions (**/routes/**, **/controllers/**, **/api/**)
  • Configuration files (**/config/**, *.yaml, *.toml, *.ini, *.env*)

2. Check for Available Scanners

Detect scanners per ../../shared/schemas/scanners.md:

  1. semgrep -- can detect some log injection and sensitive data in logs
  2. bandit -- Python-specific logging issues (e.g., sensitive data in debug logs)

Record which scanners are available and which are missing. Note: scanner coverage for logging failures is limited. Claude analysis is the primary detection mechanism for this category.

3. Run Scanners (If Available)

If semgrep is available, run with rules targeting logging patterns:

semgrep scan --config auto --json --quiet <target>

Filter results to rules matching log injection, sensitive data exposure in logs, and logging configuration issues. Normalize output to the findings schema.

4. Claude Code Analysis

This is the primary analysis step for logging failures. Perform manual code analysis:

  1. Authentication event logging: Find login, logout, failed login, password reset, and MFA flows. Verify each produces an audit log entry with user identity, timestamp, IP address, and outcome (success/failure).
  2. Access control failure logging: Find authorization checks and verify that denied access attempts are logged with sufficient detail for investigation.
  3. Sensitive data in logs: Grep for log statements and check that passwords, tokens, API keys, credit card numbers, SSNs, and other PII are not logged.
  4. Log injection: Find log statements that include user-controlled input and verify the input is sanitized or the logging framework handles neutralization.
  5. Error handling: Find catch/except blocks and verify they log the error rather than swallowing it silently.
  6. Logging configuration: Check for centralized logging setup, structured log format, log level configuration, and whether logs are sent to a remote destination.
  7. Tamper protection: For high-value audit trails, check for integrity controls (append-only storage, checksums, write-once destinations).

When --depth deep, additionally trace:

  • Complete authentication flow from entry to audit log
  • Exception propagation chains to verify no errors are silently dropped
  • Logging pipeline from application code to destination (local file, remote service, SIEM)

5. Report Findings

Format output per ../../shared/schemas/findings.md using the LOG prefix (e.g., LOG-001, LOG-002).

Include for each finding:

  • Severity and confidence
  • Exact file location with code snippet
  • Impact description specific to the logging failure
  • Concrete fix with diff when possible
  • CWE and OWASP references

What to Look For

These are the high-signal patterns specific to logging and monitoring failures. Each maps to a detection pattern in references/detection-patterns.md.

  1. Missing authentication event logging -- Login, failed login, logout, password reset, and MFA events that produce no audit log entry.
  2. Sensitive data in log statements -- Passwords, tokens, API keys, credit card numbers, or PII written to logs, especially at DEBUG or INFO level.
  3. Log injection via user input -- User-controlled strings passed directly into log format strings without sanitization, enabling log forgery or CRLF injection.
  4. Missing access control failure logging -- Authorization denials that are not logged, making it impossible to detect brute-force or enumeration attacks.
  5. Silent error swallowing -- Catch/except blocks with pass, empty bodies, or comments like "ignore" that discard errors without logging.
  6. No centralized logging configuration -- Logging set up ad-hoc per file with no consistent format, level, or destination configuration.
  7. Logs stored only locally -- Log output goes to local files or stdout with no forwarding to a centralized log management system.
  8. Missing alerting configuration -- No evidence of alerting thresholds for security-critical events (repeated failed logins, privilege escalation attempts).
  9. Excessive logging of request/response bodies -- Logging full HTTP bodies that may contain sensitive data without redaction.

Scanner Integration

ScannerCoverageCommand
semgrepLog injection, sensitive data in debug logssemgrep scan --config auto --json --quiet <target>
banditPython logging of sensitive databandit -r <target> -f json -q

Fallback (no scanner): Use Grep with patterns from references/detection-patterns.md to find log statements with user input interpolation, catch blocks without logging, authentication functions without log calls, and sensitive data patterns in log arguments. Report findings with confidence: medium.

Scanner coverage for this category is inherently limited. Most logging failures are architectural gaps (missing logging) rather than code-level bugs (present but incorrect code), making Claude analysis the primary detection mechanism.

Relevant semgrep rule categories:

  • python.lang.security.audit.logging.*
  • javascript.express.security.audit.logging.*
  • java.lang.security.audit.logging.*
  • generic.logging.security.*

Output Format

Use the findings schema from ../../shared/schemas/findings.md.

  • ID prefix: LOG (e.g., LOG-001)
  • metadata.tool: logging
  • metadata.framework: owasp
  • metadata.category: A09
  • references.owasp: A09:2021
  • references.stride: R (Repudiation)

Severity guidance for this category:

  • critical: Sensitive data (passwords, tokens) logged in plaintext in production
  • high: No audit logging for authentication events, log injection enabling log forgery
  • medium: Silent error swallowing in security-critical paths, logs only stored locally
  • low: Inconsistent log format, missing structured logging, minor gaps in non-critical logging

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

34.44%
按下载量换算28

Claude

29.83%
按下载量换算24

Cursor

17.73%
按下载量换算14

Gemini CLI

9%
按下载量换算7

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

Snyk

未通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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