Performing Cloud Log Forensics With Athena

Performing Cloud Log Forensics with AWS Athena

When to Use

• When investigating AWS security incidents that require querying massive volumes of cloud logs
• When performing forensic analysis across CloudTrail, VPC Flow Logs, S3 access logs, and ALB logs
• When building reusable Athena tables with partition projection for ongoing incident response
• When hunting for indicators of compromise across multiple AWS log sources simultaneously
• When creating evidence-grade SQL queries for compliance audits or legal proceedings

Prerequisites

• AWS account with Athena, S3, and Glue permissions
• CloudTrail configured to deliver logs to an S3 bucket
• VPC Flow Logs enabled and publishing to S3
• S3 server access logging enabled on target buckets
• ALB access logging enabled and publishing to S3
• Python 3.8+ with boto3 installed
• Appropriate IAM permissions for Athena queries and S3 access

Instructions

Phase 1: Create Athena Database and CloudTrail Table

Create a dedicated forensics database and CloudTrail table using partition projection to automatically discover partitions without manual ALTER TABLE statements.

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}'
);

Phase 2: Create VPC Flow Logs Table

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}'
);

Phase 3: Create S3 Access Logs Table

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/';

Phase 4: Create ALB Access Logs Table

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}'
);

Phase 5: Forensic Investigation Queries

Detect Unauthorized API Calls

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;

Detect Privilege Escalation Attempts

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;

Detect Data Exfiltration via S3

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;

Detect Lateral Movement via VPC Flow Logs

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;

Detect Port Scanning Activity

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;

Detect Suspicious S3 Bulk Downloads

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;

Detect ALB-Level Injection Attempts

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;

Phase 6: Cross-Log Correlation

Correlate findings across log sources for comprehensive incident timelines.

-- 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;

Examples

# 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

Source: mukul975/Anthropic-Cybersecurity-Skills → skills/performing-cloud-log-forensics-with-athena/SKILL.md