关于 performing-cloud-log-forensics-with-athena
面向 AWS 事件响应人员的 Athena 云日志取证指南,提供 CloudTrail、VPC Flow Logs、S3 和 ALB 日志表及调查查询,并介绍跨日志关联。
主要功能
- 01为多类日志创建 Athena 表
- 02使用分区投影发现数据
- 03查询未授权 API 调用等活动
- 04关联不同日志源的证据
- 05生成取证调查报告
适用场景
- 01调查 AWS 安全事件
- 02跨 CloudTrail 与网络日志追踪入侵迹象
- 03为审计或法律程序准备查询证据
安装
复制下面的命令,在终端中运行。
$
npx skills add https:/ / github.com/ mukul975/ anthropic-cybersecurity-skills --skill performing-cloud-log-forensics-with-athena安装后在 Claude Code 中输入/performing-cloud-log-forensics-with-athena确认已加载。
包含的文件
除 SKILL.md 外,安装时一起下载的参考资料和脚本。
LICENSEreferences/api-reference.mdathena-forensics-reference.mdscripts/agent.py详细介绍
使用 AWS Athena 进行云日志取证
何时使用
- 当调查需要查询海量云日志的 AWS 安全事件时
- 当跨 CloudTrail、VPC Flow Logs、S3 访问日志和 ALB 日志执行取证分析时
- 当为持续的事件响应构建带分区投影的可复用 Athena 表时
- 当同时在多个 AWS 日志源中搜寻妥协指标时
- 当为合规审计或法律程序创建证据级 SQL 查询时
前置条件
- 具有 Athena、S3 和 Glue 权限的 AWS 账户
- 已配置 CloudTrail 将日志投递到 S3 存储桶
- 已启用 VPC Flow Logs 并发布到 S3
- 已在目标存储桶上启用 S3 服务器访问日志记录
- 已启用 ALB 访问日志记录并发布到 S3
- 已安装 Python 3.8+ 和 boto3
- 具有适用于 Athena 查询和 S3 访问的相应 IAM 权限
操作步骤
阶段 1:创建 Athena 数据库和 CloudTrail 表
使用分区投影创建专用的取证数据库和 CloudTrail 表,以自动发现分区,无需手动执行 ALTER TABLE 语句。
CREATE DATABASE IF NOT EXISTS cloud_forensics;
CREATE EXTERNAL TABLE cloud_forensics.cloudtrail_logs (
eventVersion STRING,
userIdentity STRUCT<
type: STRING,
principalId: STRING,
arn: STRING,
accountId: STRING,
invokedBy: STRING,
accessKeyId: STRING,
userName: STRING,
sessionContext: STRUCT<
attributes: STRUCT<
mfaAuthenticated: STRING,
creationDate: STRING>,
sessionIssuer: STRUCT<
type: STRING,
principalId: STRING,
arn: STRING,
accountId: STRING,
userName: STRING>,
ec2RoleDelivery: STRING,
webIdFederationData: STRUCT<
federatedProvider: STRING,
attributes: MAP<STRING, STRING>>>>,
eventTime STRING,
eventSource STRING,
eventName STRING,
awsRegion STRING,
sourceIPAddress STRING,
userAgent STRING,
errorCode STRING,
errorMessage STRING,
requestParameters STRING,
responseElements STRING,
additionalEventData STRING,
requestId STRING,
eventId STRING,
readOnly STRING,
resources ARRAY<STRUCT<
arn: STRING,
accountId: STRING,
type: STRING>>,
eventType STRING,
apiVersion STRING,
recipientAccountId STRING,
serviceEventDetails STRING,
sharedEventID STRING,
vpcEndpointId STRING,
tlsDetails STRUCT<
tlsVersion: STRING,
cipherSuite: STRING,
clientProvidedHostHeader: STRING>
)
COMMENT 'CloudTrail logs with partition projection for forensic analysis'
PARTITIONED BY (
`account` STRING,
`region` STRING,
`timestamp` STRING
)
ROW FORMAT SERDE 'org.apache.hive.hcatalog.data.JsonSerDe'
STORED AS INPUTFORMAT 'com.amazon.emr.cloudtrail.CloudTrailInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
LOCATION 's3://YOUR-CLOUDTRAIL-BUCKET/AWSLogs/'
TBLPROPERTIES (
'projection.enabled' = 'true',
'projection.account.type' = 'enum',
'projection.account.values' = 'YOUR_ACCOUNT_ID',
'projection.region.type' = 'enum',
'projection.region.values' = 'us-east-1,us-west-2,eu-west-1',
'projection.timestamp.type' = 'date',
'projection.timestamp.format' = 'yyyy/MM/dd',
'projection.timestamp.range' = '2023/01/01,NOW',
'projection.timestamp.interval' = '1',
'projection.timestamp.interval.unit' = 'DAYS',
'storage.location.template' = 's3://YOUR-CLOUDTRAIL-BUCKET/AWSLogs/${account}/CloudTrail/${region}/${timestamp}'
);
阶段 2:创建 VPC Flow Logs 表
CREATE EXTERNAL TABLE cloud_forensics.vpc_flow_logs (
version INT,
account_id STRING,
interface_id STRING,
srcaddr STRING,
dstaddr STRING,
srcport INT,
dstport INT,
protocol BIGINT,
packets BIGINT,
bytes BIGINT,
start BIGINT,
`end` BIGINT,
action STRING,
log_status STRING,
vpc_id STRING,
subnet_id STRING,
az_id STRING,
sublocation_type STRING,
sublocation_id STRING,
pkt_srcaddr STRING,
pkt_dstaddr STRING,
region STRING,
pkt_src_aws_service STRING,
pkt_dst_aws_service STRING,
flow_direction STRING,
traffic_path INT
)
PARTITIONED BY (
`date` STRING
)
ROW FORMAT DELIMITED
FIELDS TERMINATED BY ' '
LOCATION 's3://YOUR-VPC-FLOW-LOGS-BUCKET/AWSLogs/YOUR_ACCOUNT_ID/vpcflowlogs/'
TBLPROPERTIES (
'skip.header.line.count' = '1',
'projection.enabled' = 'true',
'projection.date.type' = 'date',
'projection.date.format' = 'yyyy/MM/dd',
'projection.date.range' = '2023/01/01,NOW',
'projection.date.interval' = '1',
'projection.date.interval.unit' = 'DAYS',
'storage.location.template' = 's3://YOUR-VPC-FLOW-LOGS-BUCKET/AWSLogs/YOUR_ACCOUNT_ID/vpcflowlogs/us-east-1/${date}'
);
阶段 3:创建 S3 访问日志表
CREATE EXTERNAL TABLE cloud_forensics.s3_access_logs (
bucket_owner STRING,
bucket_name STRING,
request_datetime STRING,
remote_ip STRING,
requester STRING,
request_id STRING,
operation STRING,
key STRING,
request_uri STRING,
http_status INT,
error_code STRING,
bytes_sent BIGINT,
object_size BIGINT,
total_time INT,
turn_around_time INT,
referrer STRING,
user_agent STRING,
version_id STRING,
host_id STRING,
signature_version STRING,
cipher_suite STRING,
authentication_type STRING,
host_header STRING,
tls_version STRING,
access_point_arn STRING,
acl_required STRING
)
ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.RegexSerDe'
WITH SERDEPROPERTIES (
'serialization.format' = '1',
'input.regex' = '([^ ]*) ([^ ]*) \\[(.*?)\\] ([^ ]*) ([^ ]*) ([^ ]*) ([^ ]*) ([^ ]*) (\"[^\"]*\"|-) (-|[0-9]*) ([^ ]*) ([^ ]*) ([^ ]*) ([^ ]*) ([^ ]*) ([^ ]*) (\"[^\"]*\"|-) ([^ ]*) ([^ ]*) ([^ ]*) ([^ ]*) ([^ ]*) ([^ ]*) ([^ ]*) ([^ ]*) ([^ ]*)'
)
STORED AS INPUTFORMAT 'org.apache.hadoop.mapred.TextInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
LOCATION 's3://YOUR-S3-ACCESS-LOGS-BUCKET/logs/';
阶段 4:创建 ALB 访问日志表
CREATE EXTERNAL TABLE cloud_forensics.alb_access_logs (
type STRING,
time STRING,
elb STRING,
client_ip STRING,
client_port INT,
target_ip STRING,
target_port INT,
request_processing_time DOUBLE,
target_processing_time DOUBLE,
response_processing_time DOUBLE,
elb_status_code INT,
target_status_code STRING,
received_bytes BIGINT,
sent_bytes BIGINT,
request_verb STRING,
request_url STRING,
request_proto STRING,
user_agent STRING,
ssl_cipher STRING,
ssl_protocol STRING,
target_group_arn STRING,
trace_id STRING,
domain_name STRING,
chosen_cert_arn STRING,
matched_rule_priority STRING,
request_creation_time STRING,
actions_executed STRING,
redirect_url STRING,
lambda_error_reason STRING,
target_port_list STRING,
target_status_code_list STRING,
classification STRING,
classification_reason STRING,
conn_trace_id STRING
)
PARTITIONED BY (
`day` STRING
)
ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.RegexSerDe'
WITH SERDEPROPERTIES (
'serialization.format' = '1',
'input.regex' = '([^ ]*) ([^ ]*) ([^ ]*) ([^ ]*):([0-9]*) ([^ ]*)[:-]([0-9]*) ([-.0-9]*) ([-.0-9]*) ([-.0-9]*) (|[0-9]*) (-|[0-9]*) ([-0-9]*) ([-0-9]*) \"([^ ]*) (.*) (- |[^ ]*)\" \"([^\"]*)\" ([A-Z0-9-_]+) ([A-Za-z0-9.-]*) ([^ ]*) \"([^\"]*)\" \"([^\"]*)\" \"([^\"]*)\" ([-.0-9]*) ([^ ]*) \"([^\"]*)\" \"([^\"]*)\" \"([^ ]*)\" \"([^\"]*)\" \"([^ ]*)\" \"([^ ]*)\" \"([^ ]*)\"'
)
STORED AS INPUTFORMAT 'org.apache.hadoop.mapred.TextInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
LOCATION 's3://YOUR-ALB-LOGS-BUCKET/AWSLogs/YOUR_ACCOUNT_ID/elasticloadbalancing/us-east-1/'
TBLPROPERTIES (
'projection.enabled' = 'true',
'projection.day.type' = 'date',
'projection.day.format' = 'yyyy/MM/dd',
'projection.day.range' = '2023/01/01,NOW',
'projection.day.interval' = '1',
'projection.day.interval.unit' = 'DAYS',
'storage.location.template' = 's3://YOUR-ALB-LOGS-BUCKET/AWSLogs/YOUR_ACCOUNT_ID/elasticloadbalancing/us-east-1/${day}'
);
阶段 5:取证调查查询
检测未授权的 API 调用
SELECT
eventtime,
useridentity.arn AS caller_arn,
useridentity.accountid AS account,
eventsource,
eventname,
errorcode,
errormessage,
sourceipaddress,
useragent
FROM cloud_forensics.cloudtrail_logs
WHERE errorcode IN ('AccessDenied', 'UnauthorizedAccess', 'Client.UnauthorizedAccess')
AND timestamp BETWEEN '2024/01/01' AND '2024/12/31'
ORDER BY eventtime DESC
LIMIT 1000;
检测权限提升尝试
SELECT
eventtime,
useridentity.arn AS actor,
eventname,
eventsource,
json_extract_scalar(requestparameters, '$.policyArn') AS policy_arn,
json_extract_scalar(requestparameters, '$.roleName') AS role_name,
json_extract_scalar(requestparameters, '$.userName') AS target_user,
sourceipaddress
FROM cloud_forensics.cloudtrail_logs
WHERE eventname IN (
'AttachUserPolicy', 'AttachRolePolicy', 'AttachGroupPolicy',
'PutUserPolicy', 'PutRolePolicy', 'PutGroupPolicy',
'CreatePolicyVersion', 'SetDefaultPolicyVersion',
'AddUserToGroup', 'UpdateAssumeRolePolicy',
'CreateAccessKey', 'CreateLoginProfile',
'UpdateLoginProfile', 'AssumeRole'
)
AND timestamp BETWEEN '2024/01/01' AND '2024/12/31'
ORDER BY eventtime DESC;
检测通过 S3 的数据窃取
SELECT
eventtime,
useridentity.arn AS actor,
eventname,
json_extract_scalar(requestparameters, '$.bucketName') AS bucket,
json_extract_scalar(requestparameters, '$.key') AS object_key,
sourceipaddress,
useragent
FROM cloud_forensics.cloudtrail_logs
WHERE eventsource = 's3.amazonaws.com'
AND eventname IN ('GetObject', 'CopyObject', 'PutBucketPolicy',
'PutBucketAcl', 'PutObjectAcl', 'SelectObjectContent')
AND sourceipaddress NOT LIKE '10.%'
AND sourceipaddress NOT LIKE '172.%'
AND sourceipaddress NOT LIKE '192.168.%'
AND timestamp BETWEEN '2024/01/01' AND '2024/12/31'
ORDER BY eventtime DESC;
通过 VPC Flow Logs 检测横向移动
SELECT
srcaddr,
dstaddr,
dstport,
protocol,
SUM(packets) AS total_packets,
SUM(bytes) AS total_bytes,
COUNT(*) AS connection_count,
MIN(from_unixtime(start)) AS first_seen,
MAX(from_unixtime("end")) AS last_seen
FROM cloud_forensics.vpc_flow_logs
WHERE action = 'ACCEPT'
AND srcaddr LIKE '10.%'
AND dstport IN (22, 3389, 5985, 5986, 445, 135, 139)
AND date BETWEEN '2024/06/01' AND '2024/06/30'
GROUP BY srcaddr, dstaddr, dstport, protocol
HAVING COUNT(*) > 100
ORDER BY connection_count DESC;
检测端口扫描活动
SELECT
srcaddr,
COUNT(DISTINCT dstport) AS unique_ports_scanned,
COUNT(DISTINCT dstaddr) AS unique_targets,
SUM(packets) AS total_packets,
MIN(from_unixtime(start)) AS first_seen,
MAX(from_unixtime("end")) AS last_seen
FROM cloud_forensics.vpc_flow_logs
WHERE action = 'REJECT'
AND date BETWEEN '2024/06/01' AND '2024/06/30'
GROUP BY srcaddr
HAVING COUNT(DISTINCT dstport) > 25
ORDER BY unique_ports_scanned DESC;
检测可疑的 S3 批量下载
SELECT
remote_ip,
requester,
bucket_name,
COUNT(*) AS request_count,
SUM(bytes_sent) AS total_bytes_downloaded,
COUNT(DISTINCT key) AS unique_objects,
MIN(request_datetime) AS first_request,
MAX(request_datetime) AS last_request
FROM cloud_forensics.s3_access_logs
WHERE operation LIKE '%GET%'
AND http_status = 200
GROUP BY remote_ip, requester, bucket_name
HAVING COUNT(*) > 500
ORDER BY total_bytes_downloaded DESC;
检测 ALB 层面的注入尝试
SELECT
time,
client_ip,
request_verb,
request_url,
elb_status_code,
target_status_code,
user_agent
FROM cloud_forensics.alb_access_logs
WHERE (
request_url LIKE '%UNION%SELECT%'
OR request_url LIKE '%<script%'
OR request_url LIKE '%../../../%'
OR request_url LIKE '%/etc/passwd%'
OR request_url LIKE '%cmd.exe%'
OR request_url LIKE '%/proc/self%'
OR request_url LIKE '%SLEEP(%'
OR request_url LIKE '%WAITFOR%'
)
AND day BETWEEN '2024/06/01' AND '2024/06/30'
ORDER BY time DESC;
阶段 6:跨日志关联
关联各日志源中的发现,构建完整的事件时间线。
-- Correlate suspicious CloudTrail actor with VPC Flow Logs
WITH suspicious_ips AS (
SELECT DISTINCT sourceipaddress AS ip
FROM cloud_forensics.cloudtrail_logs
WHERE errorcode = 'AccessDenied'
AND timestamp BETWEEN '2024/06/01' AND '2024/06/30'
)
SELECT
v.srcaddr,
v.dstaddr,
v.dstport,
v.protocol,
SUM(v.bytes) AS total_bytes,
COUNT(*) AS flow_count
FROM cloud_forensics.vpc_flow_logs v
JOIN suspicious_ips s ON v.srcaddr = s.ip
WHERE v.date BETWEEN '2024/06/01' AND '2024/06/30'
GROUP BY v.srcaddr, v.dstaddr, v.dstport, v.protocol
ORDER BY total_bytes DESC;
示例
# Quick-start: run the forensics agent for a full investigation
python agent.py \
--action full_investigation \
--database cloud_forensics \
--start-date 2024-06-01 \
--end-date 2024-06-30 \
--output forensics_report.json
# Run specific queries only
python agent.py \
--action privilege_escalation \
--database cloud_forensics \
--start-date 2024-06-15 \
--end-date 2024-06-16
# Create all forensic tables from scratch
python agent.py \
--action setup_tables \
--cloudtrail-bucket my-cloudtrail-logs \
--vpc-flow-bucket my-vpc-flow-logs \
--s3-access-bucket my-s3-access-logs \
--alb-bucket my-alb-logs \
--account-id 123456789012 \
--regions us-east-1,us-west-2
评论
支持 Markdown