Identifying Amazon S3 requests using CloudTrail
In Amazon S3, you can identify requests using an AWS CloudTrail event log. AWS CloudTrail is the preferred way of identifying Amazon S3 requests, but if you are using Amazon S3 server access logs, see Using Amazon S3 server access logs to identify requests.
Topics
Identifying requests made to Amazon S3 in a CloudTrail log
After you set up CloudTrail to deliver events to a bucket, you should start to see objects go to your destination bucket on the Amazon S3 console. These are formatted as follows:
s3://
amzn-s3-demo-bucket1
/AWSLogs/111122223333
/CloudTrail/Region
/yyyy
/mm
/dd
Events logged by CloudTrail are stored as compressed, gzipped JSON objects in your S3 bucket. To efficiently find requests, you should use a service like Amazon Athena to index and query the CloudTrail logs.
For more information about CloudTrail and Athena, see Creating the table for AWS CloudTrail logs in Athena using partition projection in the Amazon Athena User Guide.
Identifying Amazon S3 Signature Version 2 requests by using CloudTrail
You can use a CloudTrail event log to identify which API signature version was used to sign a request in Amazon S3. This capability is important because support for Signature Version 2 will be turned off (deprecated). After that, Amazon S3 will no longer accept requests that use Signature Version 2, and all requests must use Signature Version 4 signing.
We strongly recommend that you use CloudTrail to help determine whether any of your workflows are using Signature Version 2 signing. Remediate them by upgrading your libraries and code to use Signature Version 4 instead to prevent any impact to your business.
For more information, see Announcement: AWS CloudTrail for Amazon S3 adds new fields for enhanced security
auditing
Note
CloudTrail events for Amazon S3 include the signature version in the request details
under the key name of 'additionalEventData
. To find the
signature version on requests made for objects in Amazon S3 such as
GET
, PUT
, and DELETE
requests,
you must enable CloudTrail data events. (This feature is turned off by
default.)
AWS CloudTrail is the preferred method for identifying Signature Version 2 requests. If you're using Amazon S3 server-access logs, see Identifying Signature Version 2 requests by using Amazon S3 access logs.
Topics
Athena query examples for identifying Amazon S3 Signature Version 2 requests
Example — Select all Signature Version 2 events, and print only
EventTime
, S3_Action
,
Request_Parameters
, Region
,
SourceIP
, and UserAgent
In the following Athena query, replace
with your Athena details, and increase or remove the limit as needed. s3_cloudtrail_events_db.cloudtrail_table
SELECT EventTime, EventName as S3_Action, requestParameters as Request_Parameters, awsregion as AWS_Region, sourceipaddress as Source_IP, useragent as User_Agent FROM
s3_cloudtrail_events_db.cloudtrail_table
WHERE eventsource='s3.amazonaws.com' AND json_extract_scalar(additionalEventData, '$.SignatureVersion')='SigV2' LIMIT 10;
Example — Select all requesters that are sending Signature Version 2 traffic
SELECT useridentity.arn, Count(requestid) as RequestCount FROM
s3_cloudtrail_events_db.cloudtrail_table
WHERE eventsource='s3.amazonaws.com' and json_extract_scalar(additionalEventData, '$.SignatureVersion')='SigV2' Group by useridentity.arn
Partitioning Signature Version 2 data
If you have a large amount of data to query, you can reduce the costs and running time of Athena by creating a partitioned table.
To do this, create a new table with partitions as follows.
CREATE EXTERNAL TABLE
s3_cloudtrail_events_db.cloudtrail_table
_partitioned( 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> > >, 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, resources ARRAY<STRUCT<ARN:STRING,accountId: STRING,type:STRING>>, eventType STRING, apiVersion STRING, readOnly STRING, recipientAccountId STRING, serviceEventDetails STRING, sharedEventID STRING, vpcEndpointId STRING ) PARTITIONED BY (region string, year string, month string, day string) ROW FORMAT SERDE 'org.apache.hadoop.hive.ql.io.orc.OrcSerde' STORED AS INPUTFORMAT 'org.apache.hadoop.hive.ql.io.SymlinkTextInputFormat' OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat' LOCATION 's3://amzn-s3-demo-bucket1
/AWSLogs/111122223333
/';
Then, create the partitions individually. You can't get results from dates that you haven't created.
ALTER TABLE
s3_cloudtrail_events_db.cloudtrail_table
_partitioned ADD PARTITION (region= 'us-east-1', year= '2019', month= '02', day= '19') LOCATION 's3://amzn-s3-demo-bucket1
/AWSLogs/111122223333
/CloudTrail/us-east-1/2019/02/19/' PARTITION (region= 'us-west-1', year= '2019', month= '02', day= '19') LOCATION 's3://amzn-s3-demo-bucket1
/AWSLogs/111122223333
/CloudTrail/us-west-1/2019/02/19/' PARTITION (region= 'us-west-2', year= '2019', month= '02', day= '19') LOCATION 's3://amzn-s3-demo-bucket1
/AWSLogs/111122223333
/CloudTrail/us-west-2/2019/02/19/' PARTITION (region= 'ap-southeast-1', year= '2019', month= '02', day= '19') LOCATION 's3://amzn-s3-demo-bucket1
/AWSLogs/111122223333
/CloudTrail/ap-southeast-1/2019/02/19/' PARTITION (region= 'ap-southeast-2', year= '2019', month= '02', day= '19') LOCATION 's3://amzn-s3-demo-bucket1
/AWSLogs/111122223333
/CloudTrail/ap-southeast-2/2019/02/19/' PARTITION (region= 'ap-northeast-1', year= '2019', month= '02', day= '19') LOCATION 's3://amzn-s3-demo-bucket1
/AWSLogs/111122223333
/CloudTrail/ap-northeast-1/2019/02/19/' PARTITION (region= 'eu-west-1', year= '2019', month= '02', day= '19') LOCATION 's3://amzn-s3-demo-bucket1
/AWSLogs/111122223333
/CloudTrail/eu-west-1/2019/02/19/' PARTITION (region= 'sa-east-1', year= '2019', month= '02', day= '19') LOCATION 's3://amzn-s3-demo-bucket1
/AWSLogs/111122223333
/CloudTrail/sa-east-1/2019/02/19/';
You can then make the request based on these partitions, and you don't need to load the full bucket.
SELECT useridentity.arn, Count(requestid) AS RequestCount FROM
s3_cloudtrail_events_db.cloudtrail_table
_partitioned WHERE eventsource='s3.amazonaws.com' AND json_extract_scalar(additionalEventData, '$.SignatureVersion')='SigV2' AND region='us-east-1
' AND year='2019' AND month='02' AND day='19' Group by useridentity.arn
Identifying access to S3 objects by using CloudTrail
You can use your AWS CloudTrail event logs to identify Amazon S3 object access requests
for data events such as GetObject
, DeleteObject
, and
PutObject
, and discover additional information about those
requests.
The following example shows how to get all PUT
object requests
for Amazon S3 from an AWS CloudTrail event log.
Athena query examples for identifying Amazon S3 object access requests
In the following Athena query examples, replace
with your Athena details, and modify the date range as needed. s3_cloudtrail_events_db.cloudtrail_table
Example — Select all events that have PUT
object access
requests, and print only EventTime
,
EventSource
, SourceIP
,
UserAgent
, BucketName
,
object
, and UserARN
SELECT eventTime, eventName, eventSource, sourceIpAddress, userAgent, json_extract_scalar(requestParameters, '$.bucketName') as bucketName, json_extract_scalar(requestParameters, '$.key') as object, userIdentity.arn as userArn FROM
s3_cloudtrail_events_db.cloudtrail_table
WHERE eventName = 'PutObject' AND eventTime BETWEEN '2019-07-05T00:00:00Z
' and '2019-07-06T00:00:00Z
'
Example — Select all events that have GET
object access
requests, and print only EventTime
,
EventSource
, SourceIP
,
UserAgent
, BucketName
,
object
, and UserARN
SELECT eventTime, eventName, eventSource, sourceIpAddress, userAgent, json_extract_scalar(requestParameters, '$.bucketName') as bucketName, json_extract_scalar(requestParameters, '$.key') as object, userIdentity.arn as userArn FROM
s3_cloudtrail_events_db.cloudtrail_table
WHERE eventName = 'GetObject' AND eventTime BETWEEN '2019-07-05T00:00:00Z
' and '2019-07-06T00:00:00Z
'
Example — Select all anonymous requester events to a bucket in a
certain period and print only EventTime
,
EventName
, EventSource
,
SourceIP
, UserAgent
,
BucketName
, UserARN
, and
AccountID
SELECT eventTime, eventName, eventSource, sourceIpAddress, userAgent, json_extract_scalar(requestParameters, '$.bucketName') as bucketName, userIdentity.arn as userArn, userIdentity.accountId FROM
s3_cloudtrail_events_db.cloudtrail_table
WHERE userIdentity.accountId = 'anonymous' AND eventTime BETWEEN '2019-07-05T00:00:00Z
' and '2019-07-06T00:00:00Z
'
Example — Identify all requests that required an ACL for authorization
The following Amazon Athena query example shows how to identify all
requests to your S3 buckets that required an access control list (ACL)
for authorization. If the request required an ACL for authorization, the
aclRequired
value in additionalEventData
is Yes
. If no ACLs were required, aclRequired
is not present. You can use this information to migrate those ACL
permissions to the appropriate bucket policies. After you've created
these bucket policies, you can disable ACLs for these buckets. For more
information about disabling ACLs, see Prerequisites for
disabling ACLs.
SELECT eventTime, eventName, eventSource, sourceIpAddress, userAgent, userIdentity.arn as userArn, json_extract_scalar(requestParameters, '$.bucketName') as bucketName, json_extract_scalar(requestParameters, '$.key') as object, json_extract_scalar(additionalEventData, '$.aclRequired') as aclRequired FROM
s3_cloudtrail_events_db.cloudtrail_table
WHERE json_extract_scalar(additionalEventData, '$.aclRequired') = 'Yes' AND eventTime BETWEEN '2022-05-10T00:00:00Z' and '2022-08-10T00:00:00Z'
Note
-
These query examples can also be useful for security monitoring. You can review the results for
PutObject
orGetObject
calls from unexpected or unauthorized IP addresses or requesters and for identifying any anonymous requests to your buckets. -
This query only retrieves information from the time at which logging was enabled.
If you are using Amazon S3 server access logs, see Identifying object access requests by using Amazon S3 access logs.