Aioboto3

General Information

Field	Value
Package Name	aioboto3
Manufacturer / Vendor	Terri Cain (terrycain)
Software Category	Library
Primary Documentation	Documentation, GitHub, PyPI
Programming Language(s)	Python
License	Apache License 2.0
Deployed Version(s)	>=15.4.0 (version-locked at 15.5.0)
Most Recent Available Version	15.5.0
Last Review Date	2026-01-27

Overview

Aioboto3 is an async wrapper library that combines boto3 and aiobotocore to provide asynchronous interaction with AWS services using Python's native async/await syntax. The library enables non-blocking AWS operations while maintaining a near-identical API to boto3, making it straightforward to migrate synchronous boto3 code to async patterns. With 961 GitHub stars and 4,300+ dependent projects, aioboto3 has become the standard solution for async AWS operations in the Python ecosystem. The project is in Production/Stable status and supports Python 3.9 through 3.14.

Within the medical device software, aioboto3 serves as the asynchronous database access layer for the API Gateway service, enabling non-blocking DynamoDB operations that integrate seamlessly with the FastAPI/Starlette async request handling architecture. It is integrated through a dedicated AsyncDynamoDBClient wrapper class that provides:

• User credential storage: The DynamoDBUserRepository uses aioboto3 to asynchronously retrieve and store user authentication records, supporting user lookup by name (via GSI) and by primary key, as well as credential updates
• Account lockout management: The DynamoDBLockoutRepository tracks failed authentication attempts and account lockout states, with async operations for checking lockout status during login and updating lockout records after authentication failures
• API call audit logging: The DynamoDBCallRecordRepository persists all API interactions for regulatory compliance, recording request/response metadata, timing, user context, and error information asynchronously to avoid blocking the request pipeline
• Connection pooling: The AsyncDynamoDBClient configures botocore connection pool settings (10 max connections) with explicit timeouts (5s connect, 30s read) to ensure efficient resource utilization and prevent connection leaks

Aioboto3 was selected over synchronous boto3 for DynamoDB operations due to:

• Native async/await support compatible with FastAPI's async request handlers
• Identical API to boto3, reducing learning curve and enabling code reuse patterns
• Efficient connection handling in high-concurrency scenarios typical of API gateway workloads
• Context manager support for proper resource lifecycle management
• Apache 2.0 license permitting commercial use in medical device software
• Active maintenance with regular updates tracking boto3/botocore releases

Functional Requirements

The following functional capabilities of this SOUP are relied upon by the medical device software.

Requirement ID	Description	Source / Reference
FR-001	Create async session for AWS service access	aioboto3.Session() constructor
FR-002	Provide async context manager for DynamoDB resource	session.resource('dynamodb') with async with support
FR-003	Access DynamoDB tables asynchronously	await dynamodb.Table(table_name)
FR-004	Retrieve items by primary key asynchronously	await table.get_item(Key=key)
FR-005	Store items in DynamoDB tables asynchronously	await table.put_item(Item=item)
FR-006	Delete items from DynamoDB tables asynchronously	await table.delete_item(Key=key)
FR-007	Query tables with key conditions and GSI support asynchronously	await table.query() with KeyConditionExpression and IndexName
FR-008	Support botocore configuration for connection pooling	Config object with max_pool_connections parameter
FR-009	Support configurable timeouts for connect and read operations	Config object with connect_timeout, read_timeout

Performance Requirements

The following performance expectations are relevant to the medical device software.

Requirement ID	Description	Acceptance Criteria
PR-001	Async operations shall not block the event loop	Non-blocking I/O enabling concurrent request handling
PR-002	DynamoDB operations shall complete within configured timeout bounds	Operations timeout appropriately; no indefinite blocking
PR-003	Connection pooling shall reduce connection establishment overhead	Reused connections for repeated requests
PR-004	Memory usage shall remain stable during sustained database activity	No memory leaks during prolonged operation

Hardware Requirements

The following hardware dependencies or constraints are imposed by this SOUP component.

Requirement ID	Description	Notes / Limitations
HR-001	Network interface for AWS API communication	Required for DynamoDB service interactions
HR-002	x86-64 or ARM64 processor architecture	Pre-built wheels available for common platforms
HR-003	Sufficient system memory for response buffering	Memory scales with query result sizes

Software Requirements

The following software dependencies and environmental assumptions are required by this SOUP component.

Requirement ID	Description	Dependency / Version Constraints
SR-001	Python runtime environment	Python >=3.9 (Python 3.12 used in device)
SR-002	Aiobotocore async botocore wrapper	Bundled dependency; provides core async AWS functionality
SR-003	Aiofiles for async file operations	Bundled dependency; used for S3 transfer operations
SR-004	Boto3 synchronous SDK	Bundled via aiobotocore; provides service definitions
SR-005	AWS credentials (IAM role or access keys)	Via default credential chain or explicit configuration
SR-006	Network access to AWS API endpoints	HTTPS connectivity to regional AWS DynamoDB endpoints
SR-007	Asyncio event loop for async operations	Python standard library

Known Anomalies Assessment

This section evaluates publicly reported issues, defects, or security vulnerabilities associated with this SOUP component and their relevance to the medical device software.

Anomaly Reference	Status	Applicable	Rationale	Reviewed At
CVE-2025-50181 (urllib3 redirect bypass)	Open	No	Medium severity (CVSS 5.3) SSRF via redirect policy bypass in urllib3 <2.5.0. Not applicable: the device does not use PoolManager-level redirect configuration and AWS SDK handles redirects internally	2026-01-27
CVE-2025-50182 (urllib3 Pyodide redirect)	Fixed	No	Medium severity (CVSS 5.3) redirect control vulnerability in Pyodide runtime. Not applicable: the device runs in standard Python runtime environment, not Pyodide/browser contexts	2026-01-27
GitHub Issue #3499 (botocore urllib3 version constraint)	Open	No	Botocore constrains urllib3 to <1.27, preventing upgrade to 2.5.0. Not applicable: the device's usage pattern does not expose the vulnerable redirect configuration; AWS SDK uses standard credential flows	2026-01-27

As of the review date (2026-01-27), no security vulnerabilities have been reported directly against aioboto3 in the National Vulnerability Database (NVD), GitHub Security Advisories, or Snyk vulnerability database. The reported vulnerabilities relate to transitive dependencies (urllib3 via botocore/aiobotocore) rather than aioboto3 itself.

The device's usage pattern minimizes attack surface exposure:

• Internal service only: Aioboto3 is used exclusively within the API Gateway service for DynamoDB operations; no user-supplied AWS parameters are processed
• IAM credential chain: The device uses IAM roles when running in AWS infrastructure; no hardcoded credentials exist in the codebase
• HTTPS-only communication: All DynamoDB API calls use HTTPS with TLS certificate validation
• Controlled table access: Table names are configured by operators at deployment time, not derived from user input
• Timeout enforcement: Explicit timeout configuration (5s connect, 30s read) prevents indefinite blocking
• Connection limits: Maximum connection pool size (10 connections) prevents resource exhaustion
• Async isolation: Each request handler operates within its own async context, preventing cross-request interference

Risk Control Measures

The following risk control measures are implemented to mitigate potential security and operational risks associated with this SOUP component:

• Version locking via requirements_lock.txt ensures reproducible, auditable deployments
• IAM roles with least-privilege permissions limit potential blast radius of credential compromise
• DynamoDB tables use encryption at rest with AWS-managed keys
• Container isolation limits network access to required AWS endpoints only
• Async context managers ensure proper resource cleanup on errors
• Exception wrapping provides controlled error handling without information leakage

Assessment Methodology

The following methodology was used to identify and assess known anomalies:

• Sources consulted:

  • National Vulnerability Database (NVD) search for "aioboto3" and "aiobotocore"
  • GitHub Security Advisories for terrycain/aioboto3
  • Snyk vulnerability database for aioboto3
  • Snyk vulnerability database for aiobotocore
  • boto3 and botocore security advisories (as core dependencies)
  • PyPI package security reports

• Criteria for determining applicability:

  • Vulnerability must affect deployed version (aioboto3 15.5.0)
  • Vulnerability must be exploitable through the device's operational context (containerized API Gateway, IAM authentication)
  • Attack vector must be reachable through the device's interfaces (no user-supplied AWS parameters)
  • Timeout configuration, credential management, and container isolation must not already mitigate the vulnerability

Signature meaning

The signatures for the approval process of this document can be found in the verified commits at the repository for the QMS. As a reference, the team members who are expected to participate in this document and their roles in the approval process, as defined in Annex I Responsibility Matrix of the GP-001, are:

• Author: Team members involved
• Reviewer: JD-003, JD-004
• Approver: JD-001