Spring Security OAuth 2.0授权服务器结合Redis实现获取accessToken速率限制
概述
在生产环境中,我们通常颁发给OAuth2客户端有效期较长的token,但是授权服务无从知晓OAuth2客户端服务是否频繁获取token,便于我们主动控制token的颁发,减少数据库操作,本文我们将结合Redis实现滑动窗口算法限制速率解决此问题。
先决条件
- java 8+
- Redis
- Lua
授权服务器
本节中我们将使用Spring Authorization Server 搭建一个简单的授权服务器,并通过扩展OAuth2TokenCustomizer
实现access_token的速率限制。
Maven依赖
org.springframework.boot
spring-boot-starter-security
2.6.7
org.springframework.security
spring-security-oauth2-authorization-server
0.3.1
org.springframework.boot
spring-boot-starter-web
2.6.7
org.springframework.boot
spring-boot-starter-data-redis
2.6.7
配置
首先添加spring.redis
配置连接本地Redis服务:
server:
port: 8080
spring:
redis:
host: localhost
database: 0
port: 6379
password: 123456
timeout: 1800
lettuce:
pool:
max-active: 20
max-wait: 60
max-idle: 5
min-idle: 0
shutdown-timeout: 100
接下来我们需要注册一个OAuth2客户端,声明客户端如下:
@Bean
public RegisteredClientRepository registeredClientRepository() {
RegisteredClient registeredClient = RegisteredClient.withId(UUID.randomUUID().toString())
.clientId("relive-client")
.clientSecret("{noop}relive-client")
.clientAuthenticationMethods(s -> {
s.add(ClientAuthenticationMethod.CLIENT_SECRET_POST);
s.add(ClientAuthenticationMethod.CLIENT_SECRET_BASIC);
})
.authorizationGrantType(AuthorizationGrantType.CLIENT_CREDENTIALS)
.redirectUri("http://127.0.0.1:8070/login/oauth2/code/messaging-client-model")
.scope("message.read")
.clientSettings(ClientSettings.builder()
.requireAuthorizationConsent(false)
.requireProofKey(false)
.build())
.tokenSettings(TokenSettings.builder()
.accessTokenFormat(OAuth2TokenFormat.SELF_CONTAINED)
.idTokenSignatureAlgorithm(SignatureAlgorithm.RS256)
.accessTokenTimeToLive(Duration.ofSeconds(30 * 60))
.refreshTokenTimeToLive(Duration.ofSeconds(60 * 60))
.reuseRefreshTokens(true)
.setting("accessTokenLimitTimeSeconds", 5 * 60)
.setting("accessTokenLimitRate", 3)
.build())
.build();
return new InMemoryRegisteredClientRepository(registeredClient);
}
上述OAuth2客户端信息如下:
- clientId: relive-client
- clientSecret: relive-client
- clientAuthenticationMethod: client_secret_post,client_secret_basic
- authorizationGrantType: client_credentials
- redirectUri: http://127.0.0.1:8070/login/oauth2/code/messaging-client-model
- scope: message.read
特别注意:我们额外添加了两个参数用于控制AccessToken的速率限制,
accessTokenLimitTimeSeconds
访问限制时间,accessTokenLimitRate
访问限制次数。
此外,我们为单个客户端添加限制参数,由此可以针对不同OAuth2客户端设置不同的速率限制或者取消。
使用Spring Authorization Server提供的授权服务默认配置,并将未认证的授权请求重定向到登录页面:
@Bean
@Order(Ordered.HIGHEST_PRECEDENCE)
public SecurityFilterChain authorizationServerSecurityFilterChain(HttpSecurity http) throws Exception {
OAuth2AuthorizationServerConfiguration.applyDefaultSecurity(http);
return http.exceptionHandling(exceptions -> exceptions.
authenticationEntryPoint(new LoginUrlAuthenticationEntryPoint("/login"))).build();
}
其余常规配置本文将不再赘述,您可以参考以往文章或从文末链接中获取源码。
接下来我们将利用Redis sorted set
数据结构实现滑动窗口算法用于access_token
速率限制,我们将利用Lua脚本保证Redis操作的原子性,节省网络开销。
redis.replicate_commands()
local key = KEYS[1]
local windowSize = tonumber(ARGV[1])
local rate = tonumber(ARGV[2])
local now = tonumber(redis.call("TIME")[1])
redis.call("zadd", key, now, now)
local start = math.max(0, now - windowSize)
local requestRate = tonumber(redis.call("zcount", key, start, now))
local result = true
if requestRate > rate then
result = false
end
redis.call("zremrangebyscore", key, "-inf", "("..start)
return result
上述Lua脚本遵循以下步骤:
- 将当前时间(秒)作为value和score 添加进有序集合(sorted set)中
- 计算窗口长度,统计窗口中成员总数,该总数表示该窗口长度中已请求次数
- 判断请求次数是否超过阈值
- 移除已失效成员
RedisAccessTokenLimiter
从TokenSettings
获取参数accessTokenLimitTimeSeconds,accessTokenLimitRate,由RedisTemplate
执行Lua脚本,并传递参数信息。
@Slf4j
public class RedisAccessTokenLimiter implements AccessTokenLimiter {
private static final String ACCESS_TOKEN_LIMIT_TIME_SECONDS = "accessTokenLimitTimeSeconds";
private static final String ACCESS_TOKEN_LIMIT_RATE = "accessTokenLimitRate";
private final RedisTemplate redisTemplate;
private final RedisScript script;
public RedisAccessTokenLimiter(RedisTemplate redisTemplate, RedisScript script) {
Assert.notNull(redisTemplate, "redisTemplate can not be null");
Assert.notNull(script, "script can not be null");
this.redisTemplate = redisTemplate;
this.script = script;
}
@Override
public boolean isAllowed(RegisteredClient registeredClient) {
TokenSettings tokenSettings = registeredClient.getTokenSettings();
if (tokenSettings == null || tokenSettings.getSetting(ACCESS_TOKEN_LIMIT_TIME_SECONDS) == null ||
tokenSettings.getSetting(ACCESS_TOKEN_LIMIT_RATE) == null) {
return true;
}
int accessTokenLimitTimeSeconds = tokenSettings.getSetting(ACCESS_TOKEN_LIMIT_TIME_SECONDS);
int accessTokenLimitRate = tokenSettings.getSetting(ACCESS_TOKEN_LIMIT_RATE);
String clientId = registeredClient.getClientId();
try {
List keys = getKeys(clientId);
return redisTemplate.execute(this.script, keys, accessTokenLimitTimeSeconds, accessTokenLimitRate);
} catch (Exception e) {
/*
* 我们不希望硬依赖 Redis 来允许访问。 确保设置
* 一个警报,知道发生了许多次。
*/
log.error("Error determining if user allowed from redis", e);
}
return true;
}
static List getKeys(String id) {
// 在key周围使用 `{}` 以使用 Redis Key hash tag
// 这允许使用 redis 集群
String prefix = "access_token_rate_limiter.{" + id;
String key = prefix + "}.client";
return Arrays.asList(key);
}
}
已知OAuth2TokenCustomizer
提供了自定义OAuth2Token的属性的能力,但是在本示例中我们将使用OAuth2TokenCustomizer
作为扩展点,使用AccessTokenLimiter提供了速率限制,当请求超过阈值时,将抛出OAuth2AuthenticationException异常。
public class AccessTokenRestrictionCustomizer implements OAuth2TokenCustomizer {
private static final String DEFAULT_ERROR_URI = "https://datatracker.ietf.org/doc/html/rfc6749#section-4.1.2.1";
private final AccessTokenLimiter tokenLimiter;
public AccessTokenRestrictionCustomizer(AccessTokenLimiter tokenLimiter) {
Assert.notNull(tokenLimiter, "accessTokenLimiter can not be null");
this.tokenLimiter = tokenLimiter;
}
/**
* 通过{@link AccessTokenLimiter} 为OAuth2 客户端模式访问令牌添加访问限制
*
* @param context
*/
@Override
public void customize(JwtEncodingContext context) {
if (AuthorizationGrantType.CLIENT_CREDENTIALS.equals(context.getAuthorizationGrantType())) {
RegisteredClient registeredClient = context.getRegisteredClient();
if (registeredClient == null) {
OAuth2Error error = new OAuth2Error(OAuth2ErrorCodes.INVALID_REQUEST, "OAuth 2.0 Parameter: " + OAuth2ParameterNames.CLIENT_ID, DEFAULT_ERROR_URI);
throw new OAuth2AuthenticationException(error);
}
boolean requiresGenerateToken = this.tokenLimiter.isAllowed(registeredClient);
if (!requiresGenerateToken) {
OAuth2Error error = new OAuth2Error(OAuth2ErrorCodes.ACCESS_DENIED,
"The token generation fails, and the same client is prohibited from repeatedly obtaining the token within a short period of time.", null);
throw new OAuth2AuthenticationException(error);
}
}
}
}
注意:上述示例中我们使用OAuth 2.0 客户端模式。
测试
本示例中我们限制access_token请求5分钟响应3次,我们将使用以下单元测试简单测试。
@Test
public void authorizationWhenObtainingTheAccessTokenSucceeds() throws Exception {
MultiValueMap parameters = new LinkedMultiValueMap<>();
parameters.set(OAuth2ParameterNames.GRANT_TYPE, AuthorizationGrantType.CLIENT_CREDENTIALS.getValue());
parameters.set(OAuth2ParameterNames.CLIENT_ID, "relive-client");
parameters.set(OAuth2ParameterNames.CLIENT_SECRET, "relive-client");
this.mockMvc.perform(post("/oauth2/token")
.params(parameters))
.andExpect(status().is2xxSuccessful());
}
@Test
public void authorizationWhenTokenAccessRestrictionIsTriggeredThrowOAuth2AuthenticationException() throws Exception {
MultiValueMap parameters = new LinkedMultiValueMap<>();
parameters.set(OAuth2ParameterNames.GRANT_TYPE, AuthorizationGrantType.CLIENT_CREDENTIALS.getValue());
parameters.set(OAuth2ParameterNames.CLIENT_ID, "relive-client");
parameters.set(OAuth2ParameterNames.CLIENT_SECRET, "relive-client");
this.mockMvc.perform(post("/oauth2/token")
.params(parameters))
.andExpect(status().isBadRequest())
.andExpect(result -> assertEquals("{\"error_description\":\"The token generation fails, and the same client is prohibited from repeatedly obtaining the token within a short period of time.\",\"error\":\"access_denied\"}", result.getResponse().getContentAsString()));
}
结论
可能有人会有疑问,一般服务都会由网关限流,为什么使用本示例中方式。当然,从实现上并不妨碍我们在网关中进行限制,这只是一个选择问题。后续文章中我将会介绍如何通过Spring Cloud Gateway结合授权服务对OAuth2客户端进行速率限制。
与往常一样,本文中使用的源代码可在 GitHub 上获得。