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Summary

The following cybersecurity agencies coauthored this joint Cybersecurity Advisory (hereafter collectively referred to as the authoring agencies):

United States: The Cybersecurity and Infrastructure Security Agency (CISA), the Federal Bureau of Investigation (FBI), and National Security Agency (NSA) Australia: Australian Signals Directorate’s Australian Cyber Security Centre (ACSC) Canada: Canadian Centre for Cyber Security (CCCS) New Zealand: New Zealand National Cyber Security Centre (NCSC-NZ) and Computer Emergency Response Team New Zealand (CERT NZ) United Kingdom: National Cyber Security Centre (NCSC-UK)

This advisory provides details, collected and compiled by the authoring agencies, on the Common Vulnerabilities and Exposures (CVEs) routinely and frequently exploited by malicious cyber actors in 2023 and their associated Common Weakness Enumerations (CWEs). Malicious cyber actors exploited more zero-day vulnerabilities to compromise enterprise networks in 2023 compared to 2022, allowing them to conduct operations against high priority targets.

The authoring agencies strongly encourage vendors, designers, developers, and end-user organizations to implement the following recommendations, and those found within the Mitigations section of this advisory, to reduce the risk of compromise by malicious cyber actors.

Vendors, designers, and developers. Implement secure by design and default principles and tactics to reduce the prevalence of vulnerabilities in your software. Follow the SP 800-218 Secure Software Development Framework (SSDF) and implement secure by design practices into each stage of the software development life cycle (SDLC).

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U.S. National Science Foundation

Directorate for Mathematical and Physical Sciences
     Division of Mathematical Sciences

Directorate for Biological Sciences
     Division of Biological Infrastructure
     Division of Environmental Biology
     Division of Integrative Organismal Systems
     Division of Molecular and Cellular Biosciences

Full Proposal Deadline(s) (due by 5 p.m. submitting organization’s local time):

March 03, 2025

March 1, Annually Thereafter

Important Information And Revision Notes

The Division of Biological Infrastructure (DBI) in the Directorate for Biological Sciences (BIO) will participate in this updated solicitation.

Any proposal submitted in response to this solicitation should be submitted in accordance with the NSF Proposal & Award Policies & Procedures Guide (PAPPG) that is in effect for the relevant due date to which the proposal is being submitted. The NSF PAPPG is regularly revised and it is the responsibility of the proposer to ensure that the proposal meets the requirements specified in this solicitation and the

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Submission Window Date(s) (due by 5 p.m. submitting organization’s local time):

NSF recognizes the unique lived experiences of individuals from communities that are underrepresented and/or underserved in science, technology, engineering, and mathematics (STEM) and the barriers to inclusion and access to STEM education and careers. NSF highly encourages the leadership, partnership, and contributions in all NSF opportunities of individuals who are members of such communities supported by NSF. This includes leading and designing STEM research and education proposals for funding; serving as peer reviewers, advisory committee members, and/or committee of visitor members; and serving as NSF leadership, program, and/or administrative staff. NSF also highly encourages demographically diverse institutions of higher education (IHEs) to lead, partner, and contribute to NSF opportunities on behalf of their research and education communities. NSF expects that all individuals, including those who are members of groups that are underrepresented and/or underserved in

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Tech companies have been funneling billions of dollars into quantum computers for years. The hope is that they’ll be a game changer for fields as diverse as finance, drug discovery, and logistics.

Those expectations have been especially high in physics and chemistry, where the weird effects of quantum mechanics come into play. In theory, this is where quantum computers could have a huge advantage over conventional machines.

But while the field struggles with the realities of tricky quantum hardware, another challenger is making headway in some of these most promising use cases. AI is now being applied to fundamental physics, chemistry, and materials science in a way that suggests quantum computing’s purported home turf might not be so safe after all.

The scale and complexity of quantum systems that can be simulated using AI is advancing rapidly, says Giuseppe Carleo, a professor of computational

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