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A Managed Tokens Service for Securely Keeping and Distributing Grid Tokens

Fermilab is transitioning authentication and authorization for grid operations to using bearer tokens based on the WLCG Common JWT (JSON Web Token) Profile. One of the functionalities that Fermilab experimenters rely on is the ability to automate batch job submission, which in turn depends on the ability to securely refresh and distribute the necessary credentials to experiment job submit points. Thus, with the transition to using tokens for grid operations, we needed to create a service that would obtain, refresh, and distribute tokens for experimenters’ use. This service would avoid the need for experimenters to be experts in obtaining their own tokens and would better protect the most sensitive long-lived credentials. Further, the service needed to be widely scalable, as we are currently keeping credentials active for approximately 15 experiments, each with 1-3 different credentials, and distributing those credentials to 2-20 submit points per experiment, with those numbers steadily increasing. To address these issues, we created and deployed a Managed Tokens service. The service is written in Go, taking advantage of that language’s native concurrency primitives to easily be able to scale operations as we onboard experiments. The service uses as its first credentials a set of kerberos keytabs, stored on the same secure machine that the Managed Tokens service runs on. These kerberos credentials allow the service to use htgettoken via condor_vault_storer to store vault tokens in the HTCondor credential managers (credds) that run on the batch system scheduler machines (HTCondor schedds); as well as downloading a local, shorter-lived copy of the vault token. The kerberos credentials are then also used to distribute copies of the locally-stored vault tokens to experiment submit points. When experimenters schedule jobs to be submitted, these distributed vault tokens are used to access a Hashicorp Vault instance (run separately from the Managed Tokens service), and previously-stored refresh tokens there are used to obtain the bearer token that is submitted with the job. We will discuss here the design of the Managed Tokens service, including elaborating on certain choices we made with regards to concurrent operations, configuration, monitoring, and deployment.

Bhat, Shreyas↗

A Managed Tokens Service for Securely Keeping and Distributing Grid Tokens

Fermilab is transitioning authentication and authorization for grid operations to using bearer tokens based on the WLCG Common JWT (JSON Web Token) Profile. One of the functionalities that Fermilab experimenters rely on is the ability to automate batch job submission, which in turn depends on the ability to securely refresh and distribute the necessary credentials to experiment job submit points. Thus, with the transition to using tokens for grid operations, we needed to create a service that would obtain, refresh, and distribute tokens for experimenters' use. This service would avoid the need for experimenters to be experts in obtaining their own tokens and would better protect the most sensitive long-lived credentials. Further, the service needed to be widely scalable, as Fermilab hosts many experiments, each of which would need their own credentials. To address these issues, we created and deployed a Managed Tokens Service. The service is written in Go, taking advantage of that language's native concurrency primitives to easily be able to scale operations as we onboard experiments. The service uses as its first credentials a set of kerberos keytabs, stored on the same secure machine that the Managed Tokens service runs on. These kerberos credentials allow the service to use htgettoken via condor_vault_storer to store vault tokens in the HTCondor credential managers (credds) that run on the batch system scheduler machines (HTCondor schedds); as well as downloading a local, shorter-lived copy of the vault token. The kerberos credentials are then also used to distribute copies of the locally-stored vault tokens to experiment submit points.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Fermilab's Transition to Token Authentication

Fermilab is the first High Energy Physics institution to transition from X.509 user certificates to authentication tokens in production systems. All the experiments that Fermilab hosts are now using JSON Web Token (JWT) access tokens in their grid jobs. Many software components have been either updated or created for this transition, and most of the software is available to others as open source. The tokens are defined using the WLCG Common JWT Profile. Token attributes for all the tokens are stored in the Fermilab FERRY system which generates the configuration for the CILogon token issuer. High security-value refresh tokens are stored in Hashicorp Vault configured by htvault-config, and JWT access tokens are requested by the htgettoken client through its integration with HTCondor. The Fermilab job submission system jobsub was redesigned to be a lightweight wrapper around HTCondor. The grid workload management system GlideinWMS which is also based on HTCondor was updated to use tokens for pilot job submission. For automated job submissions a managed tokens service was created to reduce duplication of effort and knowledge of how to securely keep tokens active. The existing Fermilab file transfer tool ifdh was updated to work seamlessly with tokens, as well as the Fermilab POMS (Production Operations Management System) which is used to manage automatic job submission and the RCDS (Rapid Code Distribution System) which is used to distribute analysis code via the CernVM FileSystem. The dCache storage system was reconfigured to accept tokens for authentication in place of X.509 proxy certificates. As some services and sites have not yet implemented token support, proxy certificates are still sent with jobs for backwards compatibility, but some experiments are beginning to transition to stop using them.

Dykstra, Dave [Fermilab] (ORCID:0000000326539015)↗

Fermilab s Transition to Token Authentication

Fermilab is the first High Energy Physics institution to transition from X.509 user certificates to authentication tokens in production systems. All of the experiments that Fermilab hosts are now using JSON Web Token (JWT) access tokens in their grid jobs. Many software components have been either updated or created for this transition, and most of the software is available to others as open source. The tokens are defined using the WLCG Common JWT Profile. Token attributes for all the tokens are stored in the Fermilab FERRY system which generates the configuration for the CILogon token issuer. High security-value refresh tokens are stored in Hashicorp Vault configured by htvault-config, and JWT access tokens are requested by the htgettoken client through its integration with HTCondor. The Fermilab job submission system jobsub was redesigned to be a lightweight wrapper around HTCondor. For automated job submissions a managed tokens service was created to reduce duplication of effort and knowledge of how to securely keep tokens active. The existing Fermilab file transfer tool ifdh was updated to work seamlessly with tokens, as well as the Fermilab POMS (Production Operations Management System) which is used to manage automatic job submission and the RCDS (Rapid Code Distribution System) which is used to distribute analysis code via the CernVM FileSystem. The dCache storage system was reconfigured to accept tokens for authentication in place of X.509 proxy certificates. As some services and sites have not yet implemented token support, proxy certificates are still sent with jobs for backwards compatibility but some experiments are beginning to transition to stop using them. There have been some glitches and learning curve issues but in general the system has been performing well and is being improved as operational problems are addressed.

Dykstra, David↗

CMS Token Transition

Within the LHC community, a momentous transition has been occurring in authorization. For nearly 20 years, services within the Worldwide LHC Computing Grid (WLCG) have authorized based on mapping an identity, derived from an X.509 credential, or a group/role, derived from a VOMS extension issued by the experiment. A fundamental shift is occurring to capabilities: the credential, a bearer token, asserts the authorizations of the bearer, not the identity. By the HL-LHC era, the CMS experiment plans for the transition to tokens, based on the WLCG Common JSON Web Token profile, to be complete. Services in the technology architecture include the INDIGO Identity and Access Management server to issue tokens; a HashiCorp Vault server to store and refresh access tokens for users and jobs; a managed token bastion server to push credentials to the HTCondor CredMon service; and HTCondor to maintain valid tokens in long-running batch jobs. We will describe the transition plans of the experiment, current status, configuration of the central authorization server, lessons learned in commissioning token-based access with sites, and operational experience using tokens for both job submissions and file transfers.

43 PARTICLE ACCELERATORS↗

Electron-Proton Scattering Event Generation using Structured Tokenization

Recent work such as Omnijet-$\alpha$ has demonstrated that effective tokenization combined with transformer-based architectures can produce effective foundation models for jet physics. While tokenization may help models capture generalizable event characteristics, it also introduces discretization errors that may compromise the precision required for downstream physics analyses. As the number and complexity of the particle features grow, these errors are likely to grow proportionally. In this study, we investigate new tokenization strategies to improve the application of generative transformer models to \textsc{Pythia8} simulations of electron-proton scattering at the Electron-Ion Collider. Specifically, we propose a feature-based structured tokenization approach that utilizes multiple tokens per particle, improving expressivity, while reducing the total number of unique tokens needed. We evaluate this method against grid-based binning, K-means clustering, and vector-quantized variational auto-encoders on the event simulations. Our results show that feature-based structured tokenization reduces discretization error, leading to more accurate generative modeling of particle-level events.

Goldenberg, Steven [Thomas Jefferson National Acce↗

Electron-Proton Scattering Event Generation using Structured Tokenization

Recent work such as Omnijet-$\alpha$ has demonstrated that effective tokenization combined with transformer-based architectures can produce effective foundation models for jet physics. While tokenization may help models capture generalizable event characteristics, it also introduces discretization errors that may compromise the precision required for downstream physics analyses. As the number and complexity of the particle features grow, these errors are likely to grow proportionally. In this study, we investigate new tokenization strategies to improve the application of generative transformer models to \textsc{Pythia8} simulations of electron-proton scattering at the Electron-Ion Collider. Specifically, we propose a feature-based structured tokenization approach that utilizes multiple tokens per particle, improving expressivity, while reducing the total number of unique tokens needed. We evaluate this method against grid-based binning, K-means clustering, and vector-quantized variational auto-encoders on the event simulations. Our results show that feature-based structured tokenization reduces discretization error, leading to more accurate generative modeling of particle-level events.

Goldenberg, Steven [Thomas Jefferson National Acce↗

WLCG transition from X.509 to Tokens: Progress and Outlook

Since 2017, the Worldwide LHC Computing Grid (WLCG) has been working towards enabling token-based authentication and authorization throughout its entire middleware stack.Taking guidance from the WLCG Token Transition Timeline, published in 2022, substantial progress has been achieved not only in making middleware compatible with the use of tokens, but also in understanding the limitations of the WLCG Common JWT Profiles, first published in 2019. Significant scalability experience has been gained from Data Challenge 2024, during which millions of files were transferred with tokens used as credentials - a significant percentage of the total transfers completed.Besides describing the state of affairs in the transition to tokens, revisions to the WLCG token profile, and the evolving road maps, this contribution also covers the corresponding transition from VOMS-Admin to INDIGO-IAM services, with continuing improvements in terms of functionality as well as deployment.

Dack, Thomas [Rutherford Appleton Laboratory]↗

Adoption of a token-based authentication model for the CMS Submission Infrastructure

The CMS Submission Infrastructure (SI) is the main computing resource provisioning system for CMS workloads. A number of HTCondor pools are employed to manage this infrastructure, which aggregates geographically distributed resources from the WLCG and other providers. Historically, the model of authentication among the diverse components of this infrastructure has relied on the Grid Security Infrastructure (GSI), based on identities and X509 certificates. In contrast, commonly used modern authentication standards are based on capabilities and tokens. The WLCG has identified this trend and aims at a transparent replacement of GSI for all its workload management, data transfer and storage access operations, to be completed during the current LHC Run 3. As part of this effort, and within the context of CMS computing, the Submission Infrastructure group is in the process of phasing out the GSI part of its authentication layers, in favor of IDTokens and Scitokens. The use of tokens is already well integrated into the HTCondor Software Suite, which has allowed us to fully migrate the authentication between internal components of SI. Additionally, recent versions of the HTCondor-CE support tokens as well, enabling CMS resource requests to Grid sites employing this CE technology to be granted by means of token exchange. After a rollout campaign to sites, successfully completed by the third quarter of 2022, the totality of HTCondor CEs in use by CMS are already receiving Scitoken-based pilot jobs. On the ARC CE side, a parallel campaign was launched to foster the adoption of the REST interface at CMS sites (required to enable token-based job submission via HTCondor-G), which is nearing completion as well. In this contribution, the newly adopted authentication model will be described. We will then report on the migration status and final steps towards complete GSI phase out in the CMS SI.

Pérez-Calero Yzquierdo, Antonio↗

Transitioning GlideinWMS, a multi domain distributed workload manager, from GSI proxies to tokens and other granular credentials

GlideinWMS is a distributed workload manager that has been used in production for many years to provision resources for experiments like CERN’s CMS, many Neutrino experiments, and the OSG. Its security model was based mainly on GSI (Grid Security Infrastructure), using X.509 certificate proxies and VOMS (Virtual Organization Membership Service) extensions. Even when other credentials, like SSH keys, were used to authenticate with resources, proxies were also added all the time, to establish the identity of the requestor and the associated memberships or privileges. This single credential was used for everything and was, often implicitly, forwarded wherever needed. The addition of identity and access tokens and the phase-out of GSI forced us to reconsider the security model of GlideinWMS, to handle multiple credentials which can differ in type, technology, and functionality. Both identity tokens and access tokens are supported. GSI proxies even if no more mandatory, are still used, together with various JWT (JSON Web Token) based tokens and other certificates. The functionality of the credentials, defined by issuer, audience, and scope, also differ: a credential can allow access to a computing resource, or can protect the GlideinWMS framework from tampering, or can grant read or write access to storage, can provide an identity for accounting or auditing, or can provide a combination of any the formers. Furthermore, the tools in use do not include automatic forwarding and renewal of the new credentials so credential lifetime and renewal requirements became part of the discussion as well. In this paper, we will present how GlideinWMS was able to change its design and code to respond to all these changes.

97 MATHEMATICS AND COMPUTING↗

WLCG Transition from X.509 to Tokens. Status, Plans, and Timeline

Since 2017, the Worldwide LHC Computing Grid (WLCG) has been working towards enabling token-based authentication and authorization throughout its entire middleware stack. Following the initial publication of the WLCG Token Schema v1.0 in 2019, OAuth2.0 token workflows have been integrated across grid middleware. There are many complex challenges to be addressed before the WLCG can be end-to-end token-based, including not just technical hurdles but also interoperability with the wider authentication and authorization landscape. This paper presents the status of the WLCG coordination and deployment work, and how it relates to software providers and partner communities. The authors also detail how the WLCG token transition timeline has progressed, and how it has changed since its publication.

97 MATHEMATICS AND COMPUTING↗

Tokenized Data for FORGE Foundation Models

This dataset comprises a vast corpus of 257 billion tokens, accompanied by the corresponding vocabulary file employed in the pre-training of FORGE foundation models. The primary data source for this corpus is scientific documents derived from diverse origins, and they have been tokenized using the Hugging Face BPE tokenizer. Further details about this research can be found in the publication titled FORGE: Pre-Training Open Foundation Models for Science authored by Junqi Yin, Sajal Dash, Feiyi Wang, and Mallikarjun (Arjun) Shankar, presented at SC'23. The data tokenization pipeline and resulting artifacts use CORE data [Ref: Knoth, P., and Zdrahal, Z. (2012). CORE: three access levels to underpin open access. D-Lib Magazine, 18(11/12)]. For use of these data sets for any purpose, please follow the guidelines provided in https://core.ac.uk/terms .

Yin, Junqi↗

Addressing tokens dynamic generation, propagation, storage and renewal to secure the GlideinWMS pilot based jobs and system

GlideinWMS has been one of the first middleware in the WLCG community to transition from X.509 to support also tokens. The first step was to get from the prototype in 2019 to using tokens in production in 2022. This paper will present the challenges introduced by the wider adoption of tokens and the evolution plans for securing the pilot infrastructure of GlideinWMS and supporting the new requirements. In the last couple of years, the GlideinWMS team supported the migration to tokens of experiments and resources. Inadequate support in the current infrastructure, more stringent requirements, and the higher spatial and temporal granularity forced GlideinWMS to revisit once more how credentials are generated, used, and propagated. The new credential modules have been designed to be used in multiple systems (GWMS, HC) and use a model where credentials have type, purpose, and different flows. Credentials are dynamically generated in order to customize the duration and limit the scope to the targeted resource. This allows to enforce the least privilege principle. Finally, we also considered adding credential storage, renewal, and invalidation mechanisms within the GlideinWMS infrastructure to serve better the experiments’ needs.

Mambelli, Marco↗

Addressing tokens dynamic generation, propagation, storage and renewal to secure the GlideinWMS pilot based jobs and system

GlideinWMS has been one of the first middleware in the WLCG community to transition from X.509 to support also tokens. The first step was to get from the prototype in 2019 to using tokens in production in 2022. This paper will present the challenges introduced by the wider adoption of tokens and the evolution plans for securing the pilot infrastructure of GlideinWMS and supporting the new requirements. In the last couple of years, the GlideinWMS team supported the migration of experiments and resources to tokens. Inadequate support in the current infrastructure, more stringent requirements, and the higher spatial and temporal granularity forced GlideinWMS to revisit once more how credentials are generated, used, and propagated. The new credential modules have been designed to be used in multiple systems (GlideinWMS, HEPCloud) and use a model where credentials have type, purpose, and different flows. Credentials are dynamically generated in order to customize the duration and limit the scope to the targeted resource. This allows to enforce the least privilege principle. Finally, we also considered adding credential storage, renewal, and invalidation mechanisms within the GlideinWMS infrastructure to better serve the experiments' needs.

Coimbra, Bruno Moreira [Fermilab] (ORCID:000900022↗

Is tokenization needed for masked particle modeling?

In this work, we significantly enhance masked particle modeling (MPM), a self-supervised learning scheme for constructing highly expressive representations of unordered sets relevant to developing foundation models for high-energy physics. In MPM, a model is trained to recover the missing elements of a set, a learning objective that requires no labels and can be applied directly to experimental data. We achieve significant performance improvements over previous work on MPM by addressing inefficiencies in the implementation and incorporating a more powerful decoder. We compare several pre-training tasks and introduce new reconstruction methods that utilize conditional generative models without data tokenization or discretization. We show that these new methods outperform the tokenized learning objective from the original MPM on a new test bed for foundation models for jets, which includes using a wide variety of downstream tasks relevant to jet physics, such as classification, secondary vertex finding, and track identification.

conditional generative models↗

Did You Win the GPU Cloud Lottery? Benchmarking from TFLOPS to Tokens/$

Cloud GPUs are commonly assumed to deliver consistent performance for a given GPU model. This assumption does not always hold: cloud providers employ diverse system configurations and virtualization mechanisms, and GPUs themselves exhibit non-negligible manufacturing variability (the silicon lottery). In this work, we present a large-scale measurement study of GPU performance variability across 11 cloud providers, covering over 3,500 physical GPUs and 6,800 benchmark runs. Our hierarchical analysis shows that while execution-level variation stays below 9%, performance varies by up to 38% across devices and providers for the same GPU model. Regression analysis indicates that driver- and OS-related software factors contribute less than 1% of the variance; instead, silicon lottery effects dominate observed performance variation, and cloud providers further amplify them through persistent, systematic second-order effects.

Slynko, Platon [Silicon Data, New York, USA] (ORCI↗