ListObjects
权限开放导致6TB客户数据泄露,直接损失**$2.3M**三重防护体系架构图(Mermaid)
图解:
// 危险配置示例(通配符滥用)
{
"Version": "1",
"Statement": [
{
"Effect": "Allow",
"Action": "oss:*",
"Resource": "*" // 致命错误!
}
]
}
场景:仅允许特定IP下载财务部门Bucket
{
"Version": "1",
"Statement": [
{
"Effect": "Allow",
"Action": "oss:GetObject",
"Resource": "acs:oss:cn-hangzhou:123456:bucket-finance/*",
"Condition": {
"IpAddress": {"acs:SourceIp": ["192.168.1.0/24"]}
}
}
]
}
# 启用Bucket Policy继承保护
aliyun oss bucket-policy --bucket-name mybucket \
--policy '{
"Statement":[
{
"Effect":"Deny",
"Principal":"*",
"Action":"*",
"Resource":"acs:oss:*:*:mybucket/*",
"Condition":{
"StringNotLike":{"acs:Referer":["https://company.com/*"]}
}
}
]
}'
测试用例 | 预期结果 | 实际结果 | 通过率 |
---|---|---|---|
合法IP下载文件 | 允许 | 允许 | 100% |
非法IP访问 | 拒绝 | 拒绝 | 100% |
跨部门Bucket访问 | 拒绝 | 拒绝 | 100% |
# OSS访问日志示例
Time,SourceIP,Operation,Bucket,Object,HTTPStatus
2024-06-24T03:45:12Z,203.0.113.12,GetObject,finance-bucket,invoice.pdf,200
2024-06-24T03:46:51Z,198.51.100.78,PutObject,hr-bucket,salary.xlsx,403 # 异常点!
# 基于SLS的异常检测规则
def detect_anomaly(event):
if event['Operation'] in ['DeleteObject', 'PutObjectAcl']:
if event['SourceIP'] not in whitelist:
send_alert(f"高危操作告警: {event['Operation']} by {event['SourceIP']}")
if event['HTTPStatus'] == 403 and event['Bucket'] == 'finance-bucket':
analyze_brute_force(event['SourceIP']) # 暴力破解检测
图解:
图解:
# 敏感数据识别规则
- name: 身份证检测
patterns:
- \b[1-9]\d{5}(18|19|20)\d{2}(0[1-9]|1[0-2])(0[1-9]|[12]\d|3[01])\d{3}[0-9Xx]\b
risk_level: CRITICAL
- name: 银行卡识别
patterns:
- \b[1-9]\d{9,18}\b
context_check:
keywords: ["卡号", "bank", "account"]
# 基于内容嗅探的优化逻辑
def need_scan(obj):
# 跳过已扫描文件(ETag验证)
if obj.etag in scanned_cache:
return False
# 根据扩展名过滤
if obj.key.endswith(('.jpg','.mp4')):
return False
# 小文件直接扫描,大文件抽样
if obj.size > 100*1024*1024:
return random_sample(0.1) # 10%抽样
return True
# Terraform集成部署
module "oss_protection" {
source = "git::https://protection-module"
bucket_name = "finance-data"
ram_policy = file("policies/finance_rw.json")
scan_schedule = "0 2 * * *" # 每天2AM执行
alert_webhook = var.slack_webhook
}
防护层 | 检测能力 | 响应延时 | 覆盖率 |
---|---|---|---|
RAM策略 | 权限越界访问 | 实时 | 100% |
日志审计 | 异常行为模式 | <60s | 95% |
敏感数据扫描 | 存储内容风险 | 定时 | 80%* |
*注:扫描覆盖率可通过抽样策略提升至98%
测试用例:模拟攻击者尝试下载/confidential/employee_list.xlsx
# 防护系统日志输出
[RAM BLOCK] 2024-06-24T08:12:34Z IP:203.0.113.12 DENY GetObject
finance-bucket/confidential/employee_list.xlsx
Reason: IP not in whitelist
[SCAN ALERT] 2024-06-24T02:30:21Z Object: salary_template.docx
RiskType: ID_CARD Exposure Score: 92
# 生成带策略的临时Token
def gen_temp_token(user):
policy = {
"Version": "1",
"Statement": [{
"Effect": "Allow",
"Action": "oss:GetObject",
"Resource": f"acs:oss:*:*:{user.bucket}/{user.department}/*",
"Condition": {"IpAddress": {"acs:SourceIp": user.ip}}
}]
}
return aliyun.sts.assume_role(policy, duration=900) # 15分钟有效期
-- 通过DataWorks实现查询脱敏
CREATE VIEW masked_employee AS
SELECT
id,
name,
mask(id_card) AS id_card, -- 脱敏函数
department
FROM raw_employee_data;
防护层级 | 必须实施措施 | 推荐工具 |
---|---|---|
RAM策略 | 1. 禁用* 资源标识符2. 强制IP白名单 |
策略模拟器 |
日志审计 | 1. 实时403监控 2. 低频操作告警 |
SLS+告警中心 |
敏感数据扫描 | 1. 正则规则库 2. AI增强识别 |
OSS-Inventory+DataWorks |