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網路組態驗證

部署前針對路由器與交換器組態進行預檢,包括危險指令、重複位址、子網重疊、無效參照、管理層面風險以及 IOS 風格的安全衛生檢查。

網路組態驗證 是什麼?

這個技能「網路組態驗證」專為網路工程師與自動化流程設計,在變更窗口或自動化工具接觸生產設備前,對路由器與交換器的組態進行多層次預檢。它支援 Cisco IOS/IOS-XE 等風格的組態片段,透過正規表示式(Regex)偵測危險指令、重複 IP 位址、子網重疊、無效的 ACL/路由映射/字首列表參照,以及管理平面(VTY)的暴露風險與安全衛生缺失。技能內建 Python 函式庫(如 `find_dangerous_commands`、`extract_interfaces`、`check_vty_blocks` 等),讓開發者能輕鬆整合到 Netmiko、NAPALM、Ansible 或廠商 API 自動化流程中作為閘門。驗證結果提供層級化的警告與建議,但最終仍需網路工程師審查意圖、平台語法與回滾步驟。適合用於變更窗口預檢、腳本生成組態審查,以及輕量級前處理腳本,避免常見的生產事故。

相容平台~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/ECC/tree/main/skills/network-config-validation

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說明文件

網路組態驗證 是做什麼的?

在變更窗口或自動化腳本接觸生產設備之前,使用此技能審查網路組態。

使用時機

  • 在部署前審查 Cisco IOS 或 IOS-XE 風格的組態片段。
  • 稽核由腳本或範本產生的組態。
  • 尋找危險指令、重複 IP 位址或子網重疊。
  • 檢查 ACL、route-map、prefix-list 或 line 策略是否被參照但未定義。
  • 為網路自動化建立輕量級的前置檢查腳本。

運作方式

將組態驗證視為「分層證據」,而非完整的解析器。正規表示式檢查對於前置警告很有用,但最終核准仍需網路工程師審查意圖、平台語法與回滾步驟。

請依以下順序進行驗證:

  1. 破壞性指令。
  2. 憑證與管理平面暴露。
  3. 重複位址與子網重疊。
  4. 對 ACL、route-map、prefix-list 和介面的無效參照。
  5. 營運衛生,例如 NTP、時間戳、遠端日誌與橫幅。

危險指令偵測

import re

DANGEROUS_PATTERNS: list[tuple[re.Pattern[str], str]] = [
    (re.compile(r"\breload\b", re.I), "reload 會導致停機"),
    (re.compile(r"\berase\s+(startup|nvram|flash)", re.I), "清除持久儲存裝置"),
    (re.compile(r"\bformat\b", re.I), "格式化裝置檔案系統"),
    (re.compile(r"\bno\s+router\s+(bgp|ospf|eigrp)\b", re.I), "移除路由程序"),
    (re.compile(r"\bno\s+interface\s+\S+", re.I), "移除介面組態"),
    (re.compile(r"\baaa\s+new-model\b", re.I), "變更驗證行為"),
    (re.compile(r"\bcrypto\s+key\s+(zeroize|generate)\b", re.I), "變更裝置 SSH 金鑰"),
]

def find_dangerous_commands(lines: list[str]) -> list[dict[str, str | int]]:
    findings = []
    for line_number, line in enumerate(lines, start=1):
        stripped = line.strip()
        for pattern, reason in DANGEROUS_PATTERNS:
            if pattern.search(stripped):
                findings.append({
                    "line": line_number,
                    "command": stripped,
                    "reason": reason,
                })
    return findings

重複 IP 與子網重疊

import ipaddress
import re
from collections import Counter

IP_ADDRESS_RE = re.compile(
    r"^\s*ip address\s+"
    r"(?P<ip>\d{1,3}(?:\.\d{1,3}){3})\s+"
    r"(?P<mask>\d{1,3}(?:\.\d{1,3}){3})\b",
    re.I | re.M,
)

def extract_interfaces(config: str) -> list[dict[str, str]]:
    results = []
    current = None
    for line in config.splitlines():
        if line.startswith("interface "):
            current = line.split(maxsplit=1)[1]
            continue
        match = IP_ADDRESS_RE.match(line)
        if current and match:
            ip = match.group("ip")
            mask = match.group("mask")
            network = ipaddress.ip_interface(f"{ip}/{mask}").network
            results.append({"interface": current, "ip": ip, "network": str(network)})
    return results

def find_duplicate_ips(config: str) -> list[str]:
    ips = [entry["ip"] for entry in extract_interfaces(config)]
    counts = Counter(ips)
    return sorted(ip for ip, count in counts.items() if count > 1)

def find_subnet_overlaps(config: str) -> list[tuple[str, str]]:
    networks = [ipaddress.ip_network(entry["network"]) for entry in extract_interfaces(config)]
    overlaps = []
    for index, left in enumerate(networks):
        for right in networks[index + 1:]:
            if left.overlaps(right):
                overlaps.append((str(left), str(right)))
    return overlaps

管理平面檢查

按章節解析 VTY 區塊,以避免存取類別檢查溢散至不相關的行。

import re

def iter_blocks(config: str, starts_with: str) -> list[str]:
    blocks = []
    current: list[str] = []
    for line in config.splitlines():
        if line.startswith(starts_with):
            if current:
                blocks.append("\n".join(current))
            current = [line]
            continue
        if current:
            if line and not line.startswith(" "):
                blocks.append("\n".join(current))
                current = []
            else:
                current.append(line)
    if current:
        blocks.append("\n".join(current))
    return blocks

def check_vty_blocks(config: str) -> list[str]:
    issues = []
    for block in iter_blocks(config, "line vty"):
        if re.search(r"transport\s+input\s+.*telnet", block, re.I):
            issues.append("VTY 允許 Telnet;請僅使用 SSH。")
        if not re.search(r"\baccess-class\s+\S+\s+in\b", block, re.I):
            issues.append("VTY 區塊沒有入站 access-class 來源限制。")
        if not re.search(r"\bexec-timeout\s+\d+\s+\d+\b", block, re.I):
            issues.append("VTY 區塊沒有明確的 exec-timeout。")
    return issues

安全衛生檢查

SECURITY_PATTERNS = [
    (re.compile(r"\bsnmp-server community\s+(public|private)\b", re.I),
     "已設定預設 SNMP 團體字串"),
    (re.compile(r"\bsnmp-server community\s+\S+", re.I),
     "已設定 SNMPv2 團體字串;建議改用 SNMPv3 authPriv"),
    (re.compile(r"\bip ssh version 1\b", re.I),
     "已啟用 SSH 第 1 版"),
    (re.compile(r"\benable password\b", re.I),
     "存在 enable password;請改用 enable secret"),
    (re.compile(r"\busername\s+\S+\s+password\b", re.I),
     "本機使用者名稱使用 password 而非 secret"),
]

BEST_PRACTICE_PATTERNS = [
    (re.compile(r"\bntp server\b", re.I), "NTP 伺服器"),
    (re.compile(r"\bservice timestamps\b", re.I), "記錄時間戳"),
    (re.compile(r"\blogging\s+\S+", re.I), "記錄目的地或緩衝區"),
    (re.compile(r"\bsnmp-server group\s+\S+\s+v3\s+priv\b", re.I), "SNMPv3 authPriv 群組"),
    (re.compile(r"\bbanner\s+(login|motd)\b", re.I), "登入橫幅"),
]

def check_security(config: str) -> list[str]:
    return [message for pattern, message in SECURITY_PATTERNS if pattern.search(config)]

def check_missing_hygiene(config: str) -> list[str]:
    return [
        f"缺少 {description}"
        for pattern, description in BEST_PRACTICE_PATTERNS
        if not pattern.search(config)
    ]

範例

變更窗口預檢

  1. 對要貼上的確切片段執行危險指令檢查。
  2. 對完整的候選組態執行重複 IP 與子網重疊檢查。
  3. 確認每個被參照的 ACL、route-map 與 prefix-list 都存在。
  4. 在進行任何管理平面變更前,確認回滾指令與帶外存取。

自動化預檢

在 Netmiko、NAPALM、Ansible 或廠商 API 自動化推送產生的組態之前,使用驗證作為阻斷閘門。針對危險指令與憑證應直接失敗關閉。針對變更範圍外的最佳實務缺口則提出警告。

反模式

  • 將正規表示式驗證當作裝置解析器來使用。
  • 未進行乾執行比對就套用產生的組態。
  • 以監控需求為由推薦使用 SNMPv2 團體字串。
  • 使用可能意外跨越不相關區段的正規表示式來檢查 VTY 區塊。
  • 透過停用 ACL 來測試防火牆行為,而非檢視計數器或記錄。

另請參閱

  • Agent:network-config-reviewer
  • Agent:network-troubleshooter
  • Skill:network-interface-health

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.

affaan-m/content-engine

Create platform-native content systems for X, LinkedIn, TikTok, YouTube, newsletters, and repurposed multi-platform campaigns. Use when the user wants social posts, threads, scripts, content calendars, or one source asset adapted cleanly across platforms.

affaan-m/ECC

Multi-platform content distribution across X, LinkedIn, Threads, and Bluesky. Adapts content per platform using content-engine patterns. Never posts identical content cross-platform. Use when the user wants to distribute content across social platforms.

affaan-m/fal-ai-media

Unified media generation via fal.ai MCP — image, video, and audio. Covers text-to-image (Nano Banana), text/image-to-video (Seedance, Kling, Veo 3), text-to-speech (CSM-1B), and video-to-audio (ThinkSound). Use when the user wants to generate images, videos, or audio with AI.

affaan-m/manim-video

日本語翻訳:このファイルは manim-video 用の日本語翻訳が必要です

affaan-m/remotion-video-creation

Remotion のベストプラクティス - React で動画を作成する。3D、アニメーション、音声、字幕、チャート、トランジションなどをカバーするドメイン固有の29のルール。

affaan-m/video-editing

AI-assisted video editing workflows for cutting, structuring, and augmenting real footage. Covers the full pipeline from raw capture through FFmpeg, Remotion, ElevenLabs, fal.ai, and final polish in Descript or CapCut. Use when the user wants to edit video, cut footage, create vlogs, or build video content.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

agent-self-evaluation

Use after completing any non-trivial task. The agent self-rates its output on 5 axes — accuracy, completeness, clarity, actionability, conciseness — with concrete evidence per criterion. Produces a structured 1-5 scorecard with specific improvement suggestions.

agent-sort

Build an evidence-backed ECC install plan for a specific repo by sorting skills, commands, rules, hooks, and extras into DAILY vs LIBRARY buckets using parallel repo-aware review passes. Use when ECC should be trimmed to what a project actually needs instead of loading the full bundle.

ai-first-engineering

Engineering operating model for teams where AI agents generate a large share of implementation output. Use when setting team process, review gates, or ownership rules for a codebase largely written by agents.

ai-regression-testing

Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where the same model writes and reviews code. Use when adding regression coverage to AI-assisted code, or when the same model both wrote and reviewed a change.

android-clean-architecture

Clean Architecture patterns for Android and Kotlin Multiplatform projects — module structure, dependency rules, UseCases, Repositories, and data layer patterns. Use when structuring modules, layers, or data flow in an Android or KMP project.

angular-developer

Generates Angular code and provides architectural guidance. Trigger when creating projects, components, or services, or for best practices on reactivity (signals, linkedSignal, resource), forms, dependency injection, routing, SSR, accessibility (ARIA), animations, styling (component styles, Tailwind CSS), testing, or CLI tooling.

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