The Amazon Scraper plugin for WordPress is vulnerable to Cross-Site Request Forgery in all versions up to, and including, 1.1. This is due to missing or incorrect nonce validation on a function. This makes it possible for unauthenticated attackers to update settings and inject malicious web scripts via a forged request granted they can trick a site administrator into performing an action such as clicking on a link.

In the AWS Secrets Manager and SSM Parameter Store secrets backends of `apache-airflow-providers-amazon` prior to 9.28.0, the team-scoping logic could resolve a `conn_id` containing a `/` (e.g. `"my_team/conn"`) to the same path as another team's team-scoped secret when the caller had no team context. A privileged caller without team context could therefore retrieve another team's secret by crafting a colliding `conn_id`. Fixed in 9.28.0 by switching the team-scope separator to `--` and rejecting team-shaped `conn_id`s when team context is absent. Affects the experimental multi-tenant teams feature only. Users are recommended to upgrade to `apache-airflow-providers-amazon` 9.28.0, which fixes the issue.

Unsafe use of Python's eval() on server-received data in the vector_in() function in amazon-redshift-python-driver before 2.1.14 allows a rogue server or man-in-the-middle actor to execute arbitrary code on the client. To remediate this issue, users should upgrade to version 2.1.14.

Missing integrity verification in the Triton inference handler in Amazon SageMaker Python SDK v2 before v2.257.2 and v3 before v3.8.0 might allow a remote authenticated actor to achieve code execution in inference containers via replacement of model artifacts in S3 with a specially crafted pickle payload that is deserialized without verification. This issue requires a remote authenticated actor with S3 write access to the model artifact path. To remediate this issue, we recommend upgrading to Amazon SageMaker Python SDK v2.257.2 or v3.8.0 and rebuild any Triton models previously created with ModelBuilder using the updated SDK.

Cleartext storage of sensitive information in the ModelBuilder/Serve component in Amazon SageMaker Python SDK before v2.257.2 and v3 before v3.8.0 might allow a remote authenticated actor to extract the HMAC signing key from SageMaker API responses and forge valid integrity signatures for specially crafted model artifacts, achieving code execution in inference containers. This issue requires a remote authenticated actor with permissions to call SageMaker describe APIs and S3 write access to the model artifact path. To remediate this issue, we recommend upgrading to Amazon SageMaker Python SDK v2.257.2 or v3.8.0 and rebuild any models previously created with ModelBuilder using the updated SDK.

django-s3file is a lightweight file upload input for Django and Amazon S3. Prior to 7.0.2, S3FileMiddleware is vulnerable to relative path traversal attacks, where an attacker can use a modified request to escape pre-signed upload locations and have the Django application load files from random locations into request.FILES. Depending on how files are handled, this may lead to confidentiality and integrity issues. This vulnerability is fixed in 7.0.2.

Amazon::Credentials versions through 1.2.0 for Perl uses rand to generate encryption keys. Amazon::Credentials stores credentials in an obfuscated form to prevent access to the secrets from a data dump of the object. Before version 1.3.0, the secrets were encrypted using a 64-bit key that was generated using the built-in rand function, which is predictable and unsuitable for cryptography.

Plunk is an open-source email platform built on top of AWS SES. Prior to version 0.9.0, the /webhooks/sns endpoint accepts Amazon SNS notification payloads from unauthenticated requests without verifying the SNS signature, certificate, or topic ARN, meaning anyone can forge a valid-looking webhook request. This allows an unauthenticated attacker to spoof SNS events to trigger workflow automations, unsubscribe contacts, manipulate email delivery metrics, and potentially exhaust billing credits. This issue has been patched in version 0.9.0.

An issue exists in Amazon Redshift JDBC Driver versions prior to 2.2.2. Under certain conditions, the driver could load and execute arbitrary classes when processing JDBC connection URL parameters. An actor who can influence the connection URL could potentially execute code in the application context, provided a suitable class is available on the application's classpath. To mitigate this issue, users should upgrade to version 2.2.2 or later.

Improper privilege management in the log rotation mechanism of the Skylight Workspace Config Service in Amazon WorkSpaces for Windows before 2.6.2034.0 allows a local non-admin authenticated user to place arbitrary files into arbitrary locations bypassing file system permission protections, leading to local privilege escalation to SYSTEM.

Improper neutralization of inputs used in an OS command in the FSx Windows File Server volume mounting component in Amazon ECS Agent on Windows before version 1.103.0 might allow a remote authenticated threat actor to execute shell commands with SYSTEM privileges on the underlying host via a specially crafted username field in an ECS task definition. This issue requires permissions to register ECS task definitions or write to the Secrets Manager or SSM Parameter Store credentials used by the FSx volume configuration. To remediate this issue, users should upgrade to version 1.103.0.

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Penetration Testing engineers at Amazon have identified a security flaw related to request handling in the web server component that could, under certain conditions, lead to unintended access to protected functions. The manufacturer has released patch firmware for the flaw, please refer to the manufacturer's report for details and workarounds

Penetration Testing engineers at Amazon discovered a vulnerability where the camera system failed to properly validate input, allowing specially crafted requests containing malicious commands to be executed on the device. The manufacturer has released patch firmware for the flaw; please refer to the manufacturer's report for details and workarounds.

Penetration Testing engineers at Amazon have discovered a flaw where the camera system fails to properly handle data supplied in certain requests, causing a service disruption. The manufacturer has released patch firmware for the flaw, please refer to the manufacturer's report for details and workarounds.

Cryptographic algorithm downgrade in the caching layer of Amazon AWS Encryption SDK for Python before version 3.3.1 and before version 4.0.5 might allow an authenticated local threat actor to bypass key commitment policy enforcement via a shared key cache, resulting in ciphertext that can be decrypted to multiple different plaintexts. To remediate this issue, users should upgrade to version 3.3.1, 4.0.5 or above.

OS command injection in the browser-based authentication component in Amazon Athena ODBC driver before 2.0.5.1 on Linux might allow a threat actor to execute arbitrary code by using specially crafted connection parameters that are loaded by the driver during a local user-initiated connection. To remediate this issue, users should upgrade to version 2.0.5.1 or later.

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Allocation of resources without limits in the parsing components in Amazon Athena ODBC driver before 2.1.0.0 might allow a threat actor to cause a denial of service by delivering crafted input that triggers excessive resource consumption during the driver's parsing operations. To remediate this issue, users should upgrade to version 2.1.0.0.

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Insufficient authentication security controls in the browser-based authentication components in Amazon Athena ODBC driver before 2.1.0.0 might allow a threat actor to intercept or hijack authentication sessions due to insufficient protections in the browser-based authentication flows. To remediate this issue, users should upgrade to version 2.1.0.0.

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Improper certificate validation in the identity provider connection components in Amazon Athena ODBC driver before 2.1.0.0 might allow a man-in-the-middle threat actor to intercept authentication credentials due to insufficient default transport security when connecting to identity providers. This only applies to connections with external identity providers and does not apply to connections with Athena. To remediate this issue, users should upgrade to version 2.1.0.0.

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Out-of-bounds write in the query processing components in Amazon Athena ODBC driver before 2.1.0.0 might allow a threat actor to crash the driver by using specially crafted data that is processed by the driver during query operations. To remediate this issue, users should upgrade to version 2.1.0.0.

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Improper neutralization of special elements in the authentication components in Amazon Athena ODBC driver before 2.1.0.0 might allow a threat actor to execute arbitrary code or redirect authentication flows by using specially crafted connection parameters that are processed by the driver during user-initiated authentication. To remediate this issue, users should upgrade to version 2.1.0.0.

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