The inherent design of cloud storage infrastructure creates a subtle yet profound vulnerability that allows malicious actors to reroute sensitive data streams by exploiting the global uniqueness of resource names across entire provider ecosystems. This architectural flaw, commonly referred to as bucket hijacking, stems from a fundamental conflict between the need for a globally accessible namespace and the transient nature of cloud resource ownership. In a landscape where organizations rely heavily on automated data pipelines for telemetry, logging, and large-scale data migration, the ability for an external party to claim a previously used resource name represents a high-severity risk. Security researchers identified this technique as a viable path for silent data exfiltration across the primary cloud service providers, including Google Cloud, Amazon Web Services, and Microsoft Azure. By understanding the mechanics of how these platforms manage storage identity, IT professionals can better appreciate the precariousness of default configurations that assume a name alone provides a secure destination.
The risk of bucket hijacking is not merely a theoretical curiosity but a practical challenge for any enterprise operating in a multi-tenant cloud environment during 2026. Because a storage bucket name must be unique across an entire provider, the first user to claim a specific string of characters effectively owns that piece of the global namespace. However, if that user ever deletes the bucket, the name immediately becomes available for anyone else to register. This creates a window of opportunity where an attacker can replace a legitimate destination with a malicious one while maintaining the same identifier. As data continues to flow through automated systems toward that identifier, the underlying infrastructure faithfully delivers the information to the new owner. This process bypasses traditional identity and access management updates because the routing logic remains pointed at the correct name, even though the underlying account ownership has shifted entirely.
1. Architectural Foundations: Global Namespaces and Data Streams
To comprehend the severity of this vulnerability, one must first examine the automated pipelines known as data streams that facilitate high-volume data movement between cloud services. These streams are designed to operate autonomously in the background, pushing telemetry, audit logs, or system objects from a source environment to a designated storage destination for long-term retention and analysis. In major cloud environments, these streams serve as the backbone for operational visibility. For instance, a cloud logging sink might act as a router for log entries, directing them toward a storage bucket for compliance or security monitoring. Because these systems are often configured once and left to run for years, the integrity of the destination bucket is rarely questioned. The system assumes that as long as the bucket name exists and the service agent has permission to write to it, the data is being delivered to the intended recipient within the organization.
The reliance on globally unique bucket names is the secondary architectural element that makes this attack possible. In systems like Amazon S3 or Google Cloud Storage, the design simplifies data establishment by providing a single, predictable target for any service to reach. However, this simplicity introduces a shared namespace risk where a destination’s identity is tied solely to its name rather than to an immutable account owner or a specific organizational ID. When a routing resource is established, it often uses this name as its primary reference. If an attacker possesses the rights to delete a bucket, or if a bucket is accidentally removed during a migration, the routing rule persists in a state of limbo. Any user on the same cloud platform can then claim that specific name for themselves. Once the name is reclaimed, the automated data stream resumes its delivery, unknowingly transmitting sensitive internal data directly into an environment controlled by an external adversary.
2. Standard Procedure: The Mechanics of a Hijack
Executing a bucket hijacking attack typically follows a specific sequence of actions that leverage the global namespace to reroute data. The process begins when an attacker gains unauthorized access to a cloud environment, which may occur through compromised credentials or exploited misconfigurations. Once inside, the adversary seeks the necessary permissions to remove a target storage container that currently receives a valuable data stream. Obtaining these deletion rights is often easier than gaining the granular update permissions required to modify the routing rules themselves. In many administrative roles, the ability to delete resources is bundled with broader management tasks, allowing the attacker to bypass the more restricted identity and access management protocols that would otherwise govern the modification of a data pipeline’s configuration.
After the target container is identified and the appropriate rights are secured, the attacker proceeds to delete the original storage container used by the active data stream. This creates a momentary vacuum in the global namespace. Immediately following the deletion, the attacker builds a new container with the identical name within their own external account. Because the cloud provider’s routing logic is still configured to send data to that specific name, and because the name is now associated with the attacker’s project, the data stream is effectively hijacked. The adversary then monitors their own environment to intercept the redirected data for exfiltration purposes. This method is particularly effective because the victim’s configuration still looks legitimate; the logs or objects are being sent to the “correct” bucket name, but the destination is now a ghost router owned by a third party.
3. Simulation 1: Google Cloud Logging Hijacking
Researchers demonstrated the vulnerability within Google Cloud by targeting the cloud logging sink mechanism. The first step in this simulation involved identifying a logging sink that pointed toward a specific storage resource, such as a Google Cloud Storage bucket. Sinks are common in enterprise environments for centralizing audit trails and system performance metrics. In this scenario, the attacker identified a bucket that was critical for security monitoring. By leveraging a role with sufficient permissions, the attacker was then able to remove the targeted storage resource from the victim’s project. This action broke the physical link to the storage but left the logging sink’s routing configuration intact, as the sink continued to attempt delivery to the specified bucket name regardless of its current availability.
With the original resource gone, the simulation moved to the reclamation phase. The attacker generated a new container using the same name in a separate project entirely under their control. Because bucket names are unique across all of Google Cloud, once the name was freed by the deletion, it was available for any project to claim. Once the new bucket was active, the attacker simply had to wait for the next batch of system logs to be generated. The final step of the simulation confirmed that system logs were now flowing into the attacker’s environment. The Google Cloud service agent responsible for the logging sink automatically recognized the new bucket as the valid destination for the name it was told to use. No additional permissions were needed on the sink itself, making the transition seamless and difficult for the victim to detect through standard configuration audits.
4. Simulation 2: Google Cloud Pub/Sub Messaging Exfiltration
The vulnerability also extends to messaging services like Google Cloud Pub/Sub, which are often used to bridge communication between different microservices or to trigger automated workflows. In a controlled simulation, researchers established a new messaging topic and a subscription connected to a storage container. This setup represented a common architecture where data from a web application or an internal service is buffered through Pub/Sub before being persisted in a bucket for later processing. To ensure the initial setup was functional, the appropriate permissions were assigned to allow the service agent access to the target bucket. A message was then transmitted to the topic to confirm successful delivery to the original container, establishing a baseline for the legitimate data flow.
Once the baseline was established, the attacker initiated the hijacking procedure by wiping the initial container from the victim’s project. Without changing any settings in the Pub/Sub subscription, the attacker rebuilt the container within a different, external project while keeping the name exactly the same. When another message was sent through the messaging topic, the Pub/Sub service agent continued to attempt delivery to the specified bucket name. Because the new bucket was configured to allow the service agent to write to it, the data was successfully delivered to the hijacked container. Analysts confirmed that the data was exfiltrated to the attacker’s project, demonstrating that even sophisticated messaging pipelines can be subverted if they rely on names as the primary identifier for their storage destinations.
5. Simulation 3: Google Cloud Storage Transfer Service Manipulation
Data migration tasks represent another significant attack surface, particularly when using tools like the Google Cloud Storage Transfer Service. In a research simulation, a data migration task was set up with a specific source and target container to move large datasets between regions or projects. The service agent was granted the appropriate access levels for both containers to facilitate the transfer. After starting the data migration process, the researchers simulated an attacker who possessed the ability to delete the target container. By deleting the destination and promptly recreating it in the attacker’s own account, the adversary effectively took control of the endpoint for all future transfer operations. This was done without stopping the migration job or altering its internal logic.
The final phase of this simulation involved placing a new object into the source container to test the continuity of the hijacked pipeline. Because the Transfer Service operates on a schedule or is triggered by new objects, it eventually attempted to move the file to the target container. Since the target container name was now registered in the attacker’s project, the Transfer Service faithfully moved the data to the unauthorized location. The researchers confirmed that the object appeared in the hijacked target container after the scheduled transfer completed. This specific scenario highlights the risk of long-running background tasks; a job that is safe today could become a vehicle for exfiltration tomorrow if the target resource is deleted and reclaimed by an outside party during the migration window.
6. Simulation 4: AWS S3 Bucket Replication Hijacking
Amazon Web Services is equally susceptible to this technique, specifically through the S3 bucket replication feature. In a test environment, a storage container was set up with a rule to automatically copy data to a second destination container, simulating a standard cross-region backup or disaster recovery configuration. This type of replication is a critical component of many compliance strategies. To execute the hijack, the second container was removed from its original AWS account and immediately recreated using the same name in an external AWS account controlled by the researcher. Because S3 bucket names are globally unique across all AWS regions and accounts, this recreation was successful as soon as the original name was purged from the global registry.
The effectiveness of this attack was validated by saving a file to the primary source container in the original account. Under normal circumstances, AWS replication processes would copy the file to the designated backup bucket. In the simulation, the replication engine followed its instructions to send the data to the specified destination name. Because the bucket name now existed in the unauthorized account, the file appeared in the destination container located in that account. The original account owner received no notification that the destination bucket had changed ownership, as the replication rule remained valid in the eyes of the AWS S3 service. This lack of transparency between the replication rule and the actual account ownership of the target bucket demonstrates a clear visibility gap in automated storage workflows.
7. Simulation 5: Azure Cross-Subscription Attack
Microsoft Azure presents a slightly different but equally dangerous variation of this attack, particularly concerning how resource logs are exported via diagnostic settings. In an Azure environment, researchers located a storage account used for exporting diagnostic data from various services. One critical detail in Azure is the soft-delete feature, which is designed to prevent accidental data loss. To successfully hijack the name, the attacker first ensured that soft-delete was turned off or waited for the retention period to expire, then deleted the storage account to release the name back into the global pool. This released the unique identifier associated with the storage account, making it available for any Azure user across the globe to claim.
The attacker then reclaimed the identical name by creating a new storage account in a different subscription within the same Azure tenant or even a completely different tenant. Despite the deletion and recreation of the storage account, the diagnostic settings on the original resources remained unchanged. These settings continued to point to the storage account name as the designated endpoint for logs. As new diagnostic data was generated, the pipeline continued to write to the hijacked name. The researchers were able to collect the logs directly from the new storage account, proving that the diagnostic pipeline does not verify the specific Resource ID or the account ownership of the target once the initial link is established by name. This reinforces the cross-cloud nature of the global namespace risk.
8. Exploitation and Detection: The Visibility Gap
One of the most concerning aspects of bucket hijacking is the permission risk associated with common administrative roles in cloud environments. Many organizations grant broad deletion rights to users or service accounts to facilitate routine maintenance and resource cleanup. However, these deletion permissions are often much easier to obtain than the specific identity and access management update permissions required to change a data stream’s configuration. This creates a security imbalance where an attacker can achieve the same result as a configuration change by simply destroying and recreating a resource. Furthermore, the concept of ghost routers—where a routing rule exists for a non-existent container—means that any user on the platform can proactively claim names that are likely to be used for logging or backups, effectively lying in wait for data to arrive.
Detection of these attacks is exceptionally difficult because the data pipeline remains technically valid in the configuration console. From the perspective of a victimized organization, the logging sink or replication rule still appears to be functioning perfectly. There are no error messages or “destination not found” alerts once the attacker has reclaimed the bucket name. The victim may not realize their data is being sent elsewhere until a thorough audit of account ownership for all external destinations is performed, which is a labor-intensive and infrequent task for most enterprises. Because the data transfer happens through internal cloud provider backplanes, standard network monitoring tools may not flag the traffic as exfiltration, as it appears to be a routine service-to-service communication within the same cloud ecosystem.
9. Mitigation and Defense: Strengthening Cloud Boundaries
Defending against bucket hijacking requires a multi-layered approach that moves beyond simple configuration checks. The first priority for any organization should be to enforce restricted access by strictly limiting who can use delete permissions, such as the storage.buckets.delete permission in Google Cloud or the DeleteBucket action in AWS. By treating the ability to delete a storage resource with the same level of scrutiny as the ability to modify security policies, companies can reduce the likelihood that a malicious actor or a compromised account can trigger the first stage of a hijack. Additionally, implementing security boundaries like VPC Service Controls in Google Cloud or Service Control Policies in AWS can prevent data from being written to buckets that reside outside the organization’s verified account structure.
Another effective strategy involves the use of account-specific namespaces where available. In some cloud environments, utilizing regional or private namespaces can ensure that a deleted name cannot be claimed by a different account, effectively neutralizing the global namespace risk. Organizations should also set up active monitoring and high-priority alerts for the deletion of any sensitive storage resources. If a bucket that is known to be the destination for a critical data stream is deleted, security teams must be notified immediately to ensure the name is not reclaimed by an unauthorized party. Automation can be used to re-reserve names or to disable associated routing rules the moment a destination bucket is removed, closing the window of opportunity for an attacker to intercept the flow of sensitive information.
10. Future Outlook: Actionable Next Steps for Cloud Security
The discovery of the bucket hijacking technique highlighted a significant architectural oversight in how global namespaces were managed across the cloud industry. Because the reliance on static, globally unique names created a persistent cross-cloud vulnerability, researchers advocated for a shift toward more robust identity verification within data pipelines. Moving away from set-and-forget configurations was essential, as the research demonstrated that a valid destination today could become a point of exfiltration tomorrow. Organizations that adopted a cloud-agnostic security mindset were better prepared to handle these risks, as they did not rely solely on the native security assumptions of a single provider but instead implemented their own layers of verification and monitoring.
To address these findings, the primary cloud service providers began implementing changes to how bucket names are released and reclaimed. Microsoft Azure, Amazon Web Services, and Google Cloud all acknowledged the potential for misuse and provided updated guidance on securing automated data streams. Security teams realized that the most effective way to prevent hijacking was to integrate account-level validation into every routing rule, ensuring that a name was only considered valid if it belonged to a trusted project or organization ID. The transition to these more secure practices was a critical step in maturing cloud security. Ultimately, the industry learned that global uniqueness, while convenient for developers, required significant guardrails to prevent it from being weaponized by sophisticated adversaries seeking to exploit the very infrastructure designed to protect corporate data.
