三次輸錯密碼后,系統(tǒng)是怎么做到不讓我繼續(xù)嘗試的?
故事背景
忘記密碼這件事,相信絕大多數(shù)人都遇到過,輸一次錯一次,錯到幾次以上,就不允許你繼續(xù)嘗試了。
但當(dāng)你嘗試重置密碼,又發(fā)現(xiàn)新密碼不能和原密碼重復(fù):
相信此刻心情只能用一張圖形容:
雖然,但是,密碼還是很重要的,順便我有了一個問題:三次輸錯密碼后,系統(tǒng)是怎么做到不讓我繼續(xù)嘗試的?
我想了想,有如下幾個問題需要搞定
- 是只有輸錯密碼才鎖定,還是賬戶名和密碼任何一個輸錯就鎖定?
- 輸錯之后也不是完全凍結(jié),為啥隔了幾分鐘又可以重新輸了?
- 技術(shù)棧到底麻不麻煩?
去網(wǎng)上搜了搜,也問了下ChatGPT,找到一套解決方案:SpringBoot+Redis+Lua腳本。這套方案也不算新,很早就有人在用了,不過難得是自己想到的問題和解法,就記錄一下吧。
順便回答一下上面的三個問題:
- 鎖定的是IP,不是輸入的賬戶名或者密碼,也就是說任一一個輸錯3次就會被鎖定
- Redis的Lua腳本中實現(xiàn)了key過期策略,當(dāng)key消失時鎖定自然也就消失了
- 技術(shù)棧同SpringBoot+Redis+Lua腳本
那么自己動手實現(xiàn)一下
1.前端部分
首先寫一個賬密輸入頁面,使用很簡單HTML加表單提交:
<!DOCTYPE html>
<html>
<head>
<title>登錄頁面</title>
<style>
body {
background-color: #F5F5F5;
}
form {
width: 300px;
margin: 0 auto;
margin-top: 100px;
padding: 20px;
background-color: white;
border-radius: 5px;
box-shadow: 0 0 10px rgba(0,0,0,0.2);
}
label {
display: block;
margin-bottom: 10px;
}
input[type="text"], input[type="password"] {
border: none;
padding: 10px;
margin-bottom: 20px;
border-radius: 5px;
box-shadow: 0 0 5px rgba(0,0,0,0.1);
width: 100%;
box-sizing: border-box;
font-size: 16px;
}
input[type="submit"] {
background-color: #30B0F0;
color: white;
border: none;
padding: 10px;
border-radius: 5px;
box-shadow: 0 0 5px rgba(0,0,0,0.1);
width: 100%;
font-size: 16px;
cursor: pointer;
}
input[type="submit"]:hover {
background-color: #1C90D6;
}
</style>
</head>
<body>
<form action="http://localhost:8080/login" method="get">
<label for="username">用戶名</label>
<input type="text" id="username" name="username" placeholder="請輸入用戶名" required>
<label for="password">密碼</label>
<input type="password" id="password" name="password" placeholder="請輸入密碼" required>
<input type="submit" value="登錄">
</form>
</body>
</html>
效果如下:
2.后端部分
(1) 技術(shù)選型分析
首先我們畫一個流程圖來分析一下這個登錄限制流程:
從流程圖上看,首先訪問次數(shù)的統(tǒng)計與判斷不是在登錄邏輯執(zhí)行后,而是執(zhí)行前就加1了; 其次登錄邏輯的成功與失敗并不會影響到次數(shù)的統(tǒng)計; 最后還有一點流程圖上沒有體現(xiàn)出來,這個次數(shù)的統(tǒng)計是有過期時間的,當(dāng)過期之后又可以重新登錄了。
那為什么是Redis+Lua腳本呢?
Redis的選擇不難看出,這個流程比較重要的是存在一個用來計數(shù)的變量,這個變量既要滿足分布式讀寫需求,還要滿足全局遞增或遞減的需求,那Redis的incr方法是最優(yōu)選了。 那為什么需要Lua腳本呢?流程上在驗證用戶操作前有些操作,如圖:
這里至少有3步Redis的操作,get、incr、expire,如果全放到應(yīng)用里面來操作,有點慢且浪費資源。
Lua腳本的優(yōu)點如下:
- 減少網(wǎng)絡(luò)開銷??梢詫⒍鄠€請求通過腳本的形式一次發(fā)送,減少網(wǎng)絡(luò)時延。
- 原子操作。Redis會將整個腳本作為一個整體執(zhí)行,中間不會被其他請求插入。因此在腳本運行過程中無需擔(dān)心會出現(xiàn)競態(tài)條件,無需使用事務(wù)。
- 復(fù)用??蛻舳税l(fā)送的腳本會永久存在redis中,這樣其他客戶端可以復(fù)用這一腳本,而不需要使用代碼完成相同的邏輯。
「最后為了增加功能的復(fù)用性,我打算使用Java注解的方式實現(xiàn)這個功能?!?/p>
(2) 代碼實現(xiàn)
①項目結(jié)構(gòu)如下:
②配置文件:
pom.xml
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 https://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<parent>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-parent</artifactId>
<version>2.7.11</version>
<relativePath/> <!-- lookup parent from repository -->
</parent>
<groupId>com.example</groupId>
<artifactId>LoginLimit</artifactId>
<version>0.0.1-SNAPSHOT</version>
<name>LoginLimit</name>
<description>Demo project for Spring Boot</description>
<properties>
<java.version>1.8</java.version>
</properties>
<dependencies>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-web</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-test</artifactId>
<scope>test</scope>
</dependency>
<!-- redis -->
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-data-redis</artifactId>
</dependency>
<!-- Jedis -->
<dependency>
<groupId>redis.clients</groupId>
<artifactId>jedis</artifactId>
</dependency>
<!--切面依賴 -->
<dependency>
<groupId>org.aspectj</groupId>
<artifactId>aspectjweaver</artifactId>
</dependency>
<!-- commons-lang3 -->
<dependency>
<groupId>org.apache.commons</groupId>
<artifactId>commons-lang3</artifactId>
</dependency>
<!-- guava -->
<dependency>
<groupId>com.google.guava</groupId>
<artifactId>guava</artifactId>
<version>23.0</version>
</dependency>
<!-- lombok -->
<dependency>
<groupId>org.projectlombok</groupId>
<artifactId>lombok</artifactId>
<optional>true</optional>
</dependency>
</dependencies>
<build>
<plugins>
<plugin>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-maven-plugin</artifactId>
</plugin>
</plugins>
</build>
</project>
application.properties
## Redis配置
spring.redis.host=127.0.0.1
spring.redis.port=6379
spring.redis.password=
spring.redis.timeout=1000
## Jedis配置
spring.redis.jedis.pool.min-idle=0
spring.redis.jedis.pool.max-idle=500
spring.redis.jedis.pool.max-active=2000
spring.redis.jedis.pool.max-wait=10000
③注解部分
LimitCount.java
package com.example.loginlimit.annotation;
import java.lang.annotation.ElementType;
import java.lang.annotation.Retention;
import java.lang.annotation.RetentionPolicy;
import java.lang.annotation.Target;
/**
* 次數(shù)限制注解
* 作用在接口方法上
*/
@Target(ElementType.METHOD)
@Retention(RetentionPolicy.RUNTIME)
public @interface LimitCount {
/**
* 資源名稱,用于描述接口功能
*/
String name() default "";
/**
* 資源 key
*/
String key() default "";
/**
* key prefix
*
* @return
*/
String prefix() default "";
/**
* 時間的,單位秒
* 默認(rèn)60s過期
*/
int period() default 60;
/**
* 限制訪問次數(shù)
* 默認(rèn)3次
*/
int count() default 3;
}
核心處理邏輯類:LimitCountAspect.java
package com.example.loginlimit.aspect;
import java.io.Serializable;
import java.lang.reflect.Method;
import java.util.Objects;
import javax.servlet.http.HttpServletRequest;
import com.example.loginlimit.annotation.LimitCount;
import com.example.loginlimit.util.IPUtil;
import com.google.common.collect.ImmutableList;
import lombok.extern.slf4j.Slf4j;
import org.apache.commons.lang3.StringUtils;
import org.aspectj.lang.ProceedingJoinPoint;
import org.aspectj.lang.annotation.Around;
import org.aspectj.lang.annotation.Aspect;
import org.aspectj.lang.annotation.Pointcut;
import org.aspectj.lang.reflect.MethodSignature;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.core.script.DefaultRedisScript;
import org.springframework.data.redis.core.script.RedisScript;
import org.springframework.stereotype.Component;
import org.springframework.web.context.request.RequestContextHolder;
import org.springframework.web.context.request.ServletRequestAttributes;
@Slf4j
@Aspect
@Component
public class LimitCountAspect {
private final RedisTemplate<String, Serializable> limitRedisTemplate;
@Autowired
public LimitCountAspect(RedisTemplate<String, Serializable> limitRedisTemplate) {
this.limitRedisTemplate = limitRedisTemplate;
}
@Pointcut("@annotation(com.example.loginlimit.annotation.LimitCount)")
public void pointcut() {
// do nothing
}
@Around("pointcut()")
public Object around(ProceedingJoinPoint point) throws Throwable {
HttpServletRequest request = ((ServletRequestAttributes)Objects.requireNonNull(
RequestContextHolder.getRequestAttributes())).getRequest();
MethodSignature signature = (MethodSignature)point.getSignature();
Method method = signature.getMethod();
LimitCount annotation = method.getAnnotation(LimitCount.class);
//注解名稱
String name = annotation.name();
//注解key
String key = annotation.key();
//訪問IP
String ip = IPUtil.getIpAddr(request);
//過期時間
int limitPeriod = annotation.period();
//過期次數(shù)
int limitCount = annotation.count();
ImmutableList<String> keys = ImmutableList.of(StringUtils.join(annotation.prefix() + "_", key, ip));
String luaScript = buildLuaScript();
RedisScript<Number> redisScript = new DefaultRedisScript<>(luaScript, Number.class);
Number count = limitRedisTemplate.execute(redisScript, keys, limitCount, limitPeriod);
log.info("IP:{} 第 {} 次訪問key為 {},描述為 [{}] 的接口", ip, count, keys, name);
if (count != null && count.intValue() <= limitCount) {
return point.proceed();
} else {
return "接口訪問超出頻率限制";
}
}
/**
* 限流腳本
* 調(diào)用的時候不超過閾值,則直接返回并執(zhí)行計算器自加。
*
* @return lua腳本
*/
private String buildLuaScript() {
return "local c" +
"\nc = redis.call('get',KEYS[1])" +
"\nif c and tonumber(c) > tonumber(ARGV[1]) then" +
"\nreturn c;" +
"\nend" +
"\nc = redis.call('incr',KEYS[1])" +
"\nif tonumber(c) == 1 then" +
"\nredis.call('expire',KEYS[1],ARGV[2])" +
"\nend" +
"\nreturn c;";
}
}
獲取IP地址的功能我寫了一個工具類IPUtil.java,代碼如下:
package com.example.loginlimit.util;
import javax.servlet.http.HttpServletRequest;
public class IPUtil {
private static final String UNKNOWN = "unknown";
protected IPUtil() {
}
/**
* 獲取 IP地址
* 使用 Nginx等反向代理軟件, 則不能通過 request.getRemoteAddr()獲取 IP地址
* 如果使用了多級反向代理的話,X-Forwarded-For的值并不止一個,而是一串IP地址,
* X-Forwarded-For中第一個非 unknown的有效IP字符串,則為真實IP地址
*/
public static String getIpAddr(HttpServletRequest request) {
String ip = request.getHeader("x-forwarded-for");
if (ip == null || ip.length() == 0 || UNKNOWN.equalsIgnoreCase(ip)) {
ip = request.getHeader("Proxy-Client-IP");
}
if (ip == null || ip.length() == 0 || UNKNOWN.equalsIgnoreCase(ip)) {
ip = request.getHeader("WL-Proxy-Client-IP");
}
if (ip == null || ip.length() == 0 || UNKNOWN.equalsIgnoreCase(ip)) {
ip = request.getRemoteAddr();
}
return "0:0:0:0:0:0:0:1".equals(ip) ? "127.0.0.1" : ip;
}
}
另外就是Lua限流腳本的說明,腳本代碼如下:
private String buildLuaScript() {
return "local c" +
"\nc = redis.call('get',KEYS[1])" +
"\nif c and tonumber(c) > tonumber(ARGV[1]) then" +
"\nreturn c;" +
"\nend" +
"\nc = redis.call('incr',KEYS[1])" +
"\nif tonumber(c) == 1 then" +
"\nredis.call('expire',KEYS[1],ARGV[2])" +
"\nend" +
"\nreturn c;";
}
這段腳本有一個判斷, tonumber(c) > tonumber(ARGV[1])這行表示如果當(dāng)前key 的值大于了limitCount,直接返回;否則調(diào)用incr方法進(jìn)行累加1,且調(diào)用expire方法設(shè)置過期時間。
最后就是RedisConfig.java,代碼如下:
package com.example.loginlimit.config;
import java.io.IOException;
import java.io.Serializable;
import java.time.Duration;
import java.util.Arrays;
import com.fasterxml.jackson.core.JsonProcessingException;
import com.fasterxml.jackson.databind.ObjectMapper;
import org.apache.commons.lang3.StringUtils;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.boot.autoconfigure.condition.ConditionalOnMissingBean;
import org.springframework.cache.CacheManager;
import org.springframework.cache.annotation.CachingConfigurerSupport;
import org.springframework.cache.interceptor.KeyGenerator;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.data.redis.cache.RedisCacheManager;
import org.springframework.data.redis.connection.RedisConnectionFactory;
import org.springframework.data.redis.connection.RedisPassword;
import org.springframework.data.redis.connection.RedisStandaloneConfiguration;
import org.springframework.data.redis.connection.jedis.JedisClientConfiguration;
import org.springframework.data.redis.connection.jedis.JedisConnectionFactory;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.core.StringRedisTemplate;
import org.springframework.data.redis.serializer.GenericJackson2JsonRedisSerializer;
import org.springframework.data.redis.serializer.RedisSerializer;
import org.springframework.data.redis.serializer.SerializationException;
import org.springframework.data.redis.serializer.StringRedisSerializer;
import redis.clients.jedis.JedisPool;
import redis.clients.jedis.JedisPoolConfig;
@Configuration
public class RedisConfig extends CachingConfigurerSupport {
@Value("${spring.redis.host}")
private String host;
@Value("${spring.redis.port}")
private int port;
@Value("${spring.redis.password}")
private String password;
@Value("${spring.redis.timeout}")
private int timeout;
@Value("${spring.redis.jedis.pool.max-idle}")
private int maxIdle;
@Value("${spring.redis.jedis.pool.max-wait}")
private long maxWaitMillis;
@Value("${spring.redis.database:0}")
private int database;
@Bean
public JedisPool redisPoolFactory() {
JedisPoolConfig jedisPoolConfig = new JedisPoolConfig();
jedisPoolConfig.setMaxIdle(maxIdle);
jedisPoolConfig.setMaxWaitMillis(maxWaitMillis);
if (StringUtils.isNotBlank(password)) {
return new JedisPool(jedisPoolConfig, host, port, timeout, password, database);
} else {
return new JedisPool(jedisPoolConfig, host, port, timeout, null, database);
}
}
@Bean
JedisConnectionFactory jedisConnectionFactory() {
RedisStandaloneConfiguration redisStandaloneConfiguration = new RedisStandaloneConfiguration();
redisStandaloneConfiguration.setHostName(host);
redisStandaloneConfiguration.setPort(port);
redisStandaloneConfiguration.setPassword(RedisPassword.of(password));
redisStandaloneConfiguration.setDatabase(database);
JedisClientConfiguration.JedisClientConfigurationBuilder jedisClientConfiguration = JedisClientConfiguration
.builder();
jedisClientConfiguration.connectTimeout(Duration.ofMillis(timeout));
jedisClientConfiguration.usePooling();
return new JedisConnectionFactory(redisStandaloneConfiguration, jedisClientConfiguration.build());
}
@Bean(name = "redisTemplate")
@SuppressWarnings({"rawtypes"})
@ConditionalOnMissingBean(name = "redisTemplate")
public RedisTemplate<Object, Object> redisTemplate(RedisConnectionFactory redisConnectionFactory) {
RedisTemplate<Object, Object> template = new RedisTemplate<>();
//使用 fastjson 序列化
JacksonRedisSerializer jacksonRedisSerializer = new JacksonRedisSerializer<>(Object.class);
// value 值的序列化采用 fastJsonRedisSerializer
template.setValueSerializer(jacksonRedisSerializer);
template.setHashValueSerializer(jacksonRedisSerializer);
// key 的序列化采用 StringRedisSerializer
template.setKeySerializer(new StringRedisSerializer());
template.setHashKeySerializer(new StringRedisSerializer());
template.setConnectionFactory(redisConnectionFactory);
return template;
}
//緩存管理器
@Bean
public CacheManager cacheManager(RedisConnectionFactory redisConnectionFactory) {
RedisCacheManager.RedisCacheManagerBuilder builder = RedisCacheManager.RedisCacheManagerBuilder
.fromConnectionFactory(redisConnectionFactory);
return builder.build();
}
@Bean
@ConditionalOnMissingBean(StringRedisTemplate.class)
public StringRedisTemplate stringRedisTemplate(RedisConnectionFactory redisConnectionFactory) {
StringRedisTemplate template = new StringRedisTemplate();
template.setConnectionFactory(redisConnectionFactory);
return template;
}
@Bean
public KeyGenerator wiselyKeyGenerator() {
return (target, method, params) -> {
StringBuilder sb = new StringBuilder();
sb.append(target.getClass().getName());
sb.append(method.getName());
Arrays.stream(params).map(Object::toString).forEach(sb::append);
return sb.toString();
};
}
@Bean
public RedisTemplate<String, Serializable> limitRedisTemplate(RedisConnectionFactory redisConnectionFactory) {
RedisTemplate<String, Serializable> template = new RedisTemplate<>();
template.setKeySerializer(new StringRedisSerializer());
template.setValueSerializer(new GenericJackson2JsonRedisSerializer());
template.setConnectionFactory(redisConnectionFactory);
return template;
}
}
class JacksonRedisSerializer<T> implements RedisSerializer<T> {
private Class<T> clazz;
private ObjectMapper mapper;
JacksonRedisSerializer(Class<T> clazz) {
super();
this.clazz = clazz;
this.mapper = new ObjectMapper();
mapper.enableDefaultTyping(ObjectMapper.DefaultTyping.NON_FINAL);
}
@Override
public byte[] serialize(T t) throws SerializationException {
try {
return mapper.writeValueAsBytes(t);
} catch (JsonProcessingException e) {
e.printStackTrace();
return null;
}
}
@Override
public T deserialize(byte[] bytes) throws SerializationException {
if (bytes.length <= 0) {
return null;
}
try {
return mapper.readValue(bytes, clazz);
} catch (IOException e) {
e.printStackTrace();
return null;
}
}
}
LoginController.java
package com.example.loginlimit.controller;
import javax.servlet.http.HttpServletRequest;
import com.example.loginlimit.annotation.LimitCount;
import lombok.extern.slf4j.Slf4j;
import org.apache.commons.lang3.StringUtils;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RequestParam;
import org.springframework.web.bind.annotation.RestController;
@Slf4j
@RestController
public class LoginController {
@GetMapping("/login")
@LimitCount(key = "login", name = "登錄接口", prefix = "limit")
public String login(
@RequestParam(required = true) String username,
@RequestParam(required = true) String password, HttpServletRequest request) throws Exception {
if (StringUtils.equals("張三", username) && StringUtils.equals("123456", password)) {
return "登錄成功";
}
return "賬戶名或密碼錯誤";
}
}
LoginLimitApplication.java
package com.example.loginlimit;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
@SpringBootApplication
public class LoginLimitApplication {
public static void main(String[] args) {
SpringApplication.run(LoginLimitApplication.class, args);
}
}
演示一下效果
上面這套限流的邏輯感覺用在小型或中型的項目上應(yīng)該問題不大,不過目前的登錄很少有直接鎖定賬號不能輸入的,一般都是彈出一個驗證碼框,讓你輸入驗證碼再提交。我覺得用我這套邏輯改改應(yīng)該不成問題,核心還是接口嘗試次數(shù)的限制嘛!