2026年07月21日 谷歌域名防红+QQ微信防红+防反诈屏蔽+APK爆毒检测结果怎么变成可视化趋势看板？零成本用免费工具搭建域名安全监控仪表盘实操教程

为什么要把域名检测数据从「表格」变成「图表」？

看看你现在的检测流程：打开谷歌Safe Browsing Transparency Report → 输入域名 → 记下「未发现安全问题」→ 切到QQ微信检测 → 模拟UA访问 → 记下「未拦截」→ 切到反诈DNS检测 → dig几个运营商DNS → 记下「正常解析」→ 切到Virustotal → 扫描APK → 记下「0/65」。

然后呢？然后你得到了4行文字记录，明天再做一遍，后天再做一遍。一个礼拜后你有了28条散落的记录——但它们之间没有任何关联。你完全看不出这个域名是在变好还是变坏，也无法判断哪个维度最先出问题。

免费搭建域名安全监控仪表盘需要用到哪些工具？

好消息是：不需要买任何商业BI工具，也不需要学复杂的Grafana或Kibana配置。下面这套组合拳全部免费，而且只需要基础的Shell和Python知识就能搭建。

如何用Python脚本自动采集谷歌/QQ微信/反诈/APK四大维度的检测数据？

数据采集是仪表盘的「水源」——没有持续稳定的数据流入，再漂亮的图表也是空壳。以下是经过验证的四维度自动化采集脚本框架，每个维度独立一个函数，方便单独调试和单独调度。

import requests
API_KEY = "你的谷歌API密钥"
def check_google_safebrowsing(domain):
    url = f"https://safebrowsing.googleapis.com/v4/threatMatches:find?key={API_KEY}"
    body = {
        "client": {"clientId":"333check-dashboard","clientVersion":"1.0"},
        "threatInfo": {
            "threatTypes": ["MALWARE","SOCIAL_ENGINEERING","UNWANTED_SOFTWARE","POTENTIALLY_HARMFUL_APPLICATION"],
            "platformTypes": ["ANY_PLATFORM"],
            "threatEntryTypes": ["URL"],
            "threatEntries": [{"url": domain}]
        }
    }
    r = requests.post(url, json=body)
    matches = r.json().get("matches", [])
    return 0 if not matches else len(matches)

import requests
def check_qq_wechat_block(domain):
    results = {}
    # QQ浏览器UA模拟
    qq_headers = {"User-Agent": "MQQBrowser/26 Mozilla/5.0"}
    r_qq = requests.get(f"https://{domain}", headers=qq_headers, timeout=10, allow_redirects=True)
    # 检查是否被重定向到QQ安全中心
    results["qq_blocked"] = "urlsec.qq.com" in r_qq.url or "已停止访问" in r_qq.text
    
    # 微信UA模拟
    wx_headers = {"User-Agent": "MicroMessenger/8.0"}
    r_wx = requests.get(f"https://{domain}", headers=wx_headers, timeout=10)
    results["wx_blocked"] = "已停止访问该网页" in r_wx.text or "非官方网页" in r_wx.text
    
    return 1 if (results["qq_blocked"] or results["wx_blocked"]) else 0

import subprocess, re
DNS_SERVERS = {
    "ct": "114.114.114.114",      # 电信
    "cu": "210.22.70.3",           # 联通  
    "cm": "211.137.32.178",        # 移动
    "public": "223.5.5.5"          # 阿里DNS（对照组）
}
BLOCKED_IPS = ["127.0.0.1", "0.0.0.0", "211.137.", "211.136."]

def check_antifraud_dns(domain):
    blocked_count = 0
    for isp, dns in DNS_SERVERS.items():
        result = subprocess.run(["dig", f"@{dns}", "+short", "A", domain],
                                capture_output=True, text=True, timeout=5)
        ip = result.stdout.strip()
        if any(bad in ip for bad in BLOCKED_IPS) or ip == "":
            blocked_count += 1
    return blocked_count  # 0=全通, 1-3=部分阻断, 4=全阻断

VT_API_KEY = "你的Virustotal API密钥"
def check_apk_virustotal(apk_hash_or_url):
    url = "https://www.virustotal.com/api/v3/files/" + apk_hash_or_url
    headers = {"x-apikey": VT_API_KEY, "accept": "application/json"}
    r = requests.get(url, headers=headers)
    if r.status_code == 200:
        stats = r.json()["data"]["attributes"]["last_analysis_stats"]
        return stats.get("malicious", 0) + stats.get("suspicious", 0)
    return -1  # 查询失败

如何把采集到的检测数据变成实时趋势图和告警仪表盘？

数据有了之后，下面是最关键的一步：把每天的检测记录存入SQLite，然后用Matplotlib自动绑图，最后用Flask把图表网页化。整个过程完全自动化——cron定时跑采集脚本→写入数据库→重新绑图→覆盖旧的仪表盘PNG。

import sqlite3
conn = sqlite3.connect("/var/dashboard/domain_security.db")
conn.execute("""
  CREATE TABLE IF NOT EXISTS detections (
    id INTEGER PRIMARY KEY AUTOINCREMENT,
    domain TEXT NOT NULL,
    dimension TEXT NOT NULL,  -- google / qq_wx / antifraud / apk
    score INTEGER NOT NULL,  -- 0=安全, 1=警告, 2=被标红
    detail TEXT,             -- JSON格式存储详细数据
    checked_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
  )
""")
conn.execute("CREATE INDEX IF NOT EXISTS idx_domain_time ON detections(domain, checked_at)")
conn.commit()

import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import sqlite3
from datetime import datetime, timedelta

def generate_trend_chart(domain):
    conn = sqlite3.connect("/var/dashboard/domain_security.db")
    cursor = conn.cursor()
    since = (datetime.now() - timedelta(days=14)).strftime("%Y-%m-%d")
    
    dimensions = {"google":"谷歌Safe Browsing","qq_wx":"QQ/微信防红",
                  "antifraud":"防反诈屏蔽","apk":"APK爆毒"}
    colors = {"google":"#0a74bd","qq_wx":"#059669",
              "antifraud":"#ef4444","apk":"#d97706"}
    
    fig, ax = plt.subplots(figsize=(12, 6), facecolor="#f8fafd")
    ax.set_facecolor("#f8fafd")
    
    for dim_key, dim_label in dimensions.items():
        cursor.execute("""
            SELECT date(checked_at), AVG(score) FROM detections
            WHERE domain=? AND dimension=? AND date(checked_at)>=?
            GROUP BY date(checked_at) ORDER BY checked_at
        """, (domain, dim_key, since))
        rows = cursor.fetchall()
        if rows:
            dates = [datetime.strptime(r[0], "%Y-%m-%d") for r in rows]
            scores = [r[1] for r in rows]
            ax.plot(dates, scores, color=colors[dim_key], label=dim_label,
                    linewidth=2.5, marker="o", markersize=5)
    
    ax.axhline(y=0.5, color="#e2e8f0", linestyle="--", linewidth=1)
    ax.axhline(y=1.0, color="#f59e0b", linestyle="--", linewidth=1, alpha=0.5, label="警告线")
    ax.axhline(y=1.5, color="#ef4444", linestyle="--", linewidth=1, alpha=0.5, label="标红线")
    ax.set_ylim(-0.1, 2.3)
    ax.set_yticks([0, 1, 2])
    ax.set_yticklabels(["安全","警告","标红"])
    ax.legend(loc="upper left")
    ax.set_title(f"{domain} · 域名安全四维趋势（近14天）", fontsize=14, fontweight="bold")
    ax.xaxis.set_major_formatter(mdates.DateFormatter("%m/%d"))
    plt.tight_layout()
    plt.savefig(f"/var/dashboard/static/{domain}_trend.png", dpi=120, bbox_inches="tight")
    plt.close()

from flask import Flask, render_template_string
app = Flask(__name__)

HTML = """<!DOCTYPE html><html><head>
<meta charset="UTF-8"><title>域名安全监控仪表盘</title>
<meta http-equiv="refresh" content="300">
<style>body{font-family:sans-serif;background:#f8fafd;padding:20px}
h1{color:#0f172a}.grid{display:grid;grid-template-columns:repeat(2,1fr);gap:20px}
.card{background:#fff;border-radius:12px;padding:16px;box-shadow:0 2px 8px rgba(0,0,0,0.06)}
img{width:100%;border-radius:8px}</style></head><body>
<h1>🛡️ 域名安全监控仪表盘 · {{ date }}</h1>
<div class="grid">
{% for d in domains %}
<div class="card">
  <h3>{{ d }}</h3>
  <img src="/static/{{ d }}_trend.png" alt="{{ d }}">
</div>
{% endfor %}
</div></body></html>"""

@app.route("/")
def dashboard():
    from datetime import date
    return render_template_string(HTML,
        date=date.today().strftime("%Y-%m-%d"),
        domains=["yourdomain.com"])  # 替换为你的域名列表

if __name__ == "__main__":
    app.run(host="0.0.0.0", port=8899)

检测趋势图中出现哪些信号时必须立刻响应？

仪表盘建好之后，你不会每天都盯着看——这很正常。但你必须知道哪些信号出现了就意味着需要立刻行动。以下是经过验证的四大红色告警信号和对应的响应动作：