The rapid evolution of cloud infrastructure has introduced a silent yet pervasive vulnerability known as universal bucket hijacking that fundamentally challenges our assumptions about data isolation and resource ownership. As organizations in 2026 continue to expand their digital footprints across multiple service providers, the reliance on automated data streams has become a cornerstone of modern operations, facilitating the seamless movement of telemetry, logs, and sensitive objects. However, this convenience often masks an underlying architectural flaw rooted in the global uniqueness of storage bucket names. When a name is considered unique across an entire provider’s ecosystem, it creates a shared namespace where the identity of a destination is inextricably linked to its name rather than a specific, immutable account owner. This research highlights a critical risk where an attacker can intercept active data streams by simply reclaiming a deleted bucket name within their own environment. Because the routing configurations often remain static even after a target resource is removed, the data continues to seek its named destination, inadvertently delivering sensitive information to a malicious actor. This scenario represents a paradigm shift in cloud security, moving away from simple permission bypasses toward the exploitation of fundamental design principles that govern cloud resource allocation and lifecycle management.
1. Architectural Pillars: Foundations of the Cloud Data Stream
The infrastructure supporting modern cloud environments relies heavily on automated data streams, which act as continuous pipelines designed for high-volume data movement between various services. Once these streams are configured, they operate autonomously in the background, pushing telemetry, audit logs, or binary objects from a source environment to a designated storage destination for long-term retention and analysis. These pipelines are critical nodes for routing and processing data, ensuring that vital information reaches the correct storage tier without manual intervention. In platforms like Google Cloud, a logging sink serves as a primary router for log entries, directing them to a chosen destination such as a storage bucket. Similarly, Amazon Web Services provides replication features that automatically duplicate data from a source bucket to a destination bucket, often across different regions or accounts. These automated processes are built on the assumption that the destination remains under the control of the original creator, yet the underlying mechanics of how these destinations are identified can be manipulated by external parties who understand the lifecycle of cloud resource naming.
The vulnerability stems from the fact that cloud storage buckets typically exist within a global namespace, meaning that once a bucket name is chosen, it must be unique across the entire service provider’s customer base. This design was originally intended to simplify data access and provide a predictable target for developers, but it inadvertently ties the destination’s identity solely to its name rather than to a specific, immutable account owner. If a user deletes a bucket, the name is released back into the public pool, making it available for any other user on the platform to claim. This transition period between the deletion of a resource and its potential reclamation creates a window of opportunity where an attacker can register the exact same name within their own account. Because many automated data streams do not verify the account ID of the destination bucket after the initial setup, they continue to attempt delivery to the specified name. Consequently, the data stream is rerouted to the attacker’s environment without any visible change to the routing configuration, effectively bypassing traditional identity and access management barriers that are supposed to keep tenant data isolated.
2. The Standard Procedure: How Hijacking Bypasses Traditional Guardrails
The execution of a bucket hijacking attack begins with an attacker gaining unauthorized access to a victim’s cloud environment, specifically targeting accounts that possess the rights to remove storage containers. While most security focus is placed on update permissions—the rights required to change where a data stream points—this attack leverages deletion permissions instead. In many organizations, administrative roles are configured with broad deletion rights that are often easier to obtain or exploit than the specific permissions needed to modify a complex logging sink or replication rule. Once an attacker has identified a high-value data stream, they focus on the storage container acting as the terminal point for that pipeline. By obtaining the necessary rights to remove the target storage bucket, the attacker prepares to disrupt the legitimate flow of data while keeping the routing logic intact. This approach is particularly effective because the deletion of a resource is frequently treated as a routine maintenance task or a temporary cleanup action, often failing to trigger the same level of scrutiny as a change in routing policy.
After the original storage container is successfully removed, the attacker immediately builds a new container with the identical name within their own controlled cloud project or account. This rapid reclamation of the name is the core of the hijacking technique, as it takes advantage of the global namespace to redirect the data stream. Because the victim’s data pipeline is still active and programmed to send data to that specific name, it simply begins delivering the telemetry or files to the new bucket, which is now owned by the attacker. The transition is seamless and requires no modification to the victim’s data stream configuration, meaning that the victim may see their logs or data disappearing from their own storage while remaining unaware that the information is being exfiltrated to an external environment. The attacker then intercepts the redirected data, gaining access to sensitive logs, personal information, or proprietary assets that continue to flow into their hijacked container. This method effectively transforms a standard administrative action into a powerful tool for data exfiltration that leaves very few traces in the victim’s primary audit logs.
3. Simulation Scenario One: Exploiting Google Cloud Logging Sinks
In a controlled simulation of this attack within a Google Cloud environment, the first step involves identifying a cloud logging sink that is configured to route logs to a specific Cloud Storage resource. These sinks are often set up to capture comprehensive audit trails or system events, making them a prime target for attackers looking to gain insight into an organization’s internal operations. The researcher identifies the target storage resource and confirms that it is receiving a steady stream of data. Once the target is established, the next phase is the removal of the targeted storage resource. This action effectively severs the link between the logging sink and its intended destination, but the sink itself remains active, continuously attempting to deliver log entries to the name that no longer exists in the victim’s project. This creates a “ghost” routing path where the system is looking for a destination that has been vacated but not yet reassigned to a new owner.
To complete the hijacking simulation, a new storage container is generated using the same name, but this time it is created within a project controlled by the attacker. Because the Google Cloud Storage namespace is global, the attacker is able to claim the name as soon as it is released by the victim’s project. Once the new bucket is active, the system’s logging sink automatically detects that a resource with the matching name is now available and begins delivering logs to it. The researcher then verifies that the system logs, which were previously being stored securely within the victim’s project, are now flowing directly into the attacker’s environment. This simulation demonstrates that the logging service agent does not perform a check to ensure the bucket owner is the same as the sink owner. As long as the name matches and the service agent has the necessary permissions to write to that bucket—which are often granted broadly during initial setup—the data exfiltration continues indefinitely without any manual configuration changes on the victim’s part.
4. Simulation Scenario Two: Manipulating Google Cloud Pub/Sub Messaging
The hijacking technique also applies to messaging services, as seen in a simulation involving Google Cloud Pub/Sub. The process begins by establishing a new messaging topic and a corresponding subscription that is connected to a storage container for data archiving. This type of setup is common for handling high-velocity event data that needs to be persisted for later processing. To ensure the system functions correctly, the required permissions are assigned to allow the service agent access to the storage bucket. A test message is then transmitted to the topic, and the researcher confirms that the data is successfully delivered to the original container. This baseline confirms that the automated pipeline is working as intended and that the identity of the storage bucket is properly registered within the subscription’s configuration. At this stage, the connection is stable and appears secure, as it is operating within the boundaries of a single organizational tenant.
The attack then proceeds by wiping the initial container from the victim’s project and promptly rebuilding it within a different, external project owned by the attacker. By using the identical name for the new bucket, the attacker exploits the subscription’s reliance on the bucket name as its destination identifier. When another message is sent to the topic, the Pub/Sub service attempts to push the data to the configured destination. Since a bucket with that name now exists in the attacker’s project, the service agent delivers the message there. The simulation concludes by confirming that the data has been exfiltrated to the attacker’s project, demonstrating that the messaging pipeline remains operational even though the data is now reaching an unauthorized recipient. This highlights a critical oversight in how messaging subscriptions handle resource identities, as they fail to lock the destination to a specific project ID, allowing the global uniqueness of the bucket name to be used as a redirection mechanism.
5. Simulation Scenario Three: Intercepting Google Cloud Storage Transfer Tasks
Data migration and backup tasks are equally vulnerable, as shown in a simulation of the Google Cloud Storage Transfer Service. The scenario begins with the setup of a data migration task designed to move objects from a specific source container to a target container. This service is often used for large-scale data transfers between buckets, often for purposes of redundancy or regional optimization. The researcher grants the appropriate access levels to the service agent for both the source and target containers, ensuring that the migration process can proceed without interruption. Once the task is initiated, the migration begins moving data as scheduled. This process is highly automated and typically runs in the background, making it an ideal candidate for a silent hijacking attack where the owner of the source bucket may not be monitoring the target bucket’s activity in real-time.
While the data migration is in progress, the target container is deleted and then quickly recreated within the attacker’s account using the same name. To test the success of the hijack, a new object is placed into the source container to trigger the next transfer cycle. The researcher then confirms that the object appears in the hijacked target container within the attacker’s account, rather than the original victim’s environment. This result shows that the Storage Transfer Service relies on the bucket name at the time of each transfer operation, rather than verifying the immutable resource ID or the account ownership of the target bucket at the start of the task. As a result, the scheduled transfer continues to function perfectly from the perspective of the service, but the destination has been effectively changed to an external project. This illustrates the danger of “set-and-forget” migration tasks, where a single deletion event can reroute future data transfers to an unauthorized party.
6. Multi-Cloud Variations: Hijacking AWS S3 Replication Pipelines
The threat of bucket hijacking is not limited to a single provider, as demonstrated by simulations of AWS S3 bucket replication. In this scenario, a storage container is set up with a replication rule that automatically copies every new object to a second destination container, which could be in a different region for disaster recovery purposes. This replication process is a standard best practice for data durability, yet it relies on the same naming logic that enables hijacking. The researcher removes the second destination container and immediately recreates it using the same name within an entirely separate AWS account. Because S3 bucket names are globally unique across all of AWS, the attacker can claim the name as long as it is not currently in use. The replication configuration in the source account remains unchanged, as it still points to the name of the destination bucket that was originally specified.
Once the hijacked bucket is active in the unauthorized account, the researcher saves a file to the primary source container to trigger the replication engine. The test confirms that the file appears in the destination container located in the attacker’s account, proving that the replication service continues to honor the naming convention regardless of account ownership. This variation of the attack is particularly dangerous because AWS users often rely on cross-account replication for centralized logging or backup strategies, and the failure of a destination bucket might not be immediately obvious if the replication metrics do not explicitly highlight ownership changes. The simulation reveals that the replication service agent, much like its counterparts in other clouds, prioritizes the target’s name over its account identity, allowing an attacker to effectively “step into” a pre-existing data pipeline by simply winning a race to reclaim a deleted bucket name.
7. Azure Specifics: Navigating Diagnostic Settings and Storage Reclamation
In the Microsoft Azure ecosystem, the hijacking technique takes a slightly different form but remains equally effective, particularly concerning resource logs. The simulation begins by locating a storage account that is used for exporting resource logs through diagnostic settings, which is a common method for monitoring the health and security of Azure resources. The researcher must first ensure that the “soft-delete” feature, which usually protects storage accounts from accidental deletion for a set period, is turned off or has expired. Once the storage account is deleted, the unique name is released back into the Azure global pool. The researcher then reclaims the identical name by creating a new storage account in a different subscription within the same Azure tenant or even a different tenant, depending on the specific service’s naming scope.
As the diagnostic pipeline continues to run, it attempts to write logs to the storage account name specified in its configuration. Because the name has been reclaimed by the researcher in a different subscription, the logs are directed to the new, unauthorized storage account. The simulation confirms that the logs are successfully collected, demonstrating that Azure’s diagnostic settings do not bind the log export to a specific resource ID of the storage account, but rather to its name. This allows an attacker to intercept sensitive platform logs, which might contain information about user activity, network traffic, or system errors. The ability to reclaim names across subscriptions within the same tenant, or across different tenants, underscores the risk of relying on shared namespaces for critical security telemetry. This simulation highlights the importance of understanding the reclamation policies of each cloud provider, as the timing and scope of name availability can vary significantly.
8. The Detection Crisis: Why Traditional Monitoring Often Fails
Detecting a bucket hijacking attack presents a significant challenge for security teams because the activity often mimics legitimate administrative behavior. Common administrative roles frequently grant broad deletion rights, which are necessary for managing the lifecycle of cloud resources but also provide the leverage needed for this attack. Because the deletion of a bucket is a standard operation, it may not trigger high-priority alerts unless specifically configured to do so. Furthermore, the attacker does not need to modify the data stream’s routing configuration, which is the traditional indicator of a compromised pipeline. Instead, the pipeline remains “valid” from the perspective of the cloud provider’s configuration management tools, as it is still pointing to a correctly named resource. This creates a state of “ghost routing,” where the metadata suggests everything is functioning normally, while the actual data is being diverted to an external account.
The stealthy nature of this technique is further compounded by the lack of visibility into external accounts. A victim can see that their bucket was deleted, but they have no native way to see that the same name has been registered by another user in a different project or tenant. To the victim’s monitoring tools, the data stream might simply appear to be failing due to a missing destination, or it might not show an error at all if the service agent successfully delivers the data to the hijacked bucket. In many cases, the victim may not realize their data is being sent elsewhere until they attempt to perform an audit or a recovery operation and find that their storage is empty. This gap in visibility between the internal configuration of a data stream and the external ownership of its destination bucket is a fundamental blind spot in current cloud security architectures, making it difficult for organizations to distinguish between a routine resource cleanup and a sophisticated data exfiltration event.
9. Resilience and Recovery: Building Defensible Cloud Infrastructure
To defend against the threat of universal bucket hijacking, organizations must implement a multi-layered security strategy that addresses both identity management and architectural design. The first line of defense is the enforcement of restricted access to deletion permissions, such as the storage.buckets.delete permission in Google Cloud or the DeleteBucket action in AWS. These rights should be granted only to a minimal number of highly trusted identities and should require multi-factor authentication or a manual approval workflow for sensitive resources. By treating the deletion of a storage container with the same level of caution as a major configuration change, organizations can significantly reduce the risk of an attacker successfully clearing a bucket name for reclamation. This administrative hurdle is the most direct way to prevent the first step of the hijacking procedure.
Beyond identity controls, organizations should implement security boundaries that prevent data from being written to accounts outside their controlled environment. Tools like VPC Service Controls in Google Cloud or Service Control Policies in AWS can be configured to restrict where a service agent is allowed to deliver data, ensuring that even if a bucket name is reclaimed by an attacker, the system will refuse to send information to a destination that sits outside the organization’s trust boundary. Additionally, where possible, organizations should utilize account-specific or regional namespaces that prevent a deleted name from being claimed by a different account. Setting up active monitoring for the deletion of high-value storage resources is also essential; creating high-priority alerts for these events allows security teams to respond immediately if a critical data destination is removed. These proactive measures move the defense from a reactive posture to one of structural resilience, ensuring that the global namespace remains a manageable risk rather than a wide-open vulnerability.
10. Strategic Advancements: Protecting the Future of Cloud Data Integrity
The discovery of universal bucket hijacking prompted a significant shift in how security teams approached the lifecycle of cloud resources and the integrity of their data pipelines. Organizations identified that the traditional “set-and-forget” mentality for configuring data streams was no longer sufficient in an environment where resource names could be weaponized. Security leaders realized that the reliance on globally unique strings as destination identifiers created an inherent architectural flaw that required a more robust, account-aware verification process. By moving toward a model that verified the destination’s immutable resource ID and its associated account owner, many companies successfully eliminated the possibility of silent data redirection. These strategic shifts emphasized that data provenance was just as important as the data itself, leading to the adoption of more rigorous validation steps during both the initial configuration and the ongoing operation of automated pipelines.
Furthermore, the industry transitioned toward more integrated monitoring solutions that specifically tracked the ownership status of external data targets. Security researchers demonstrated that by correlating resource deletion events with the activity of service agents, it was possible to identify hijacking attempts before significant data exfiltration occurred. Organizations that adopted these advanced monitoring techniques found that they could close the visibility gaps that previously allowed ghost routers to operate undetected. This progress transformed cloud security from a focus on static permissions to a dynamic understanding of resource relationships and namespace dynamics. Ultimately, the lessons learned from the risks of global namespaces paved the way for a more resilient cloud ecosystem where data isolation was enforced not just by names, but by deep architectural guardrails that prioritized organizational boundaries over naming convenience.
