EUVD-2012-1473

Malware in sbrugna...

EUVD-2012-1448

Malware in sbrugna...

EUVD-2012-1453

Malware in sbrugna...

EUVD-2012-1469

Malware in sbrugna...

EUVD-2010-3493

Malware in sbrugna...

EUVD-2016-4992

Malware in sbrugna...

EUVD-2016-10005

Malware in sbrugna...

EUVD-2012-1479

Malware in sbrugna...

EUVD-2008-5517

Malware in sbrugna...

EUVD-2015-8840

Malware in sbrugna...

EUVD-2012-1476

Malware in sbrugna...

EUVD-2009-1778

Malware in sbrugna...

EUVD-2018-19023

Malware in sbrugna...

EUVD-2008-5521

Malware in sbrugna...

EUVD-2012-1468

Malware in sbrugna...

EUVD-2007-3936

Malware in sbrugna...

Evaluating the Robustness of a Production Malware Detection System to Transferable Adversarial Attacks

As deep learning models become widely deployed as components within larger production systems, their individual shortcomings can create system-level vulnerabilities with real-world impact. This paper studies how adversarial attacks targeting an ML component can degrade or bypass an entire...

Binary Diff Summarization Using Large Language Models

Security of software supply chains is necessary to ensure that software updates do not contain maliciously injected code or introduce vulnerabilities that may compromise the integrity of critical infrastructure. Verifying the integrity of software updates involves binary differential analysis...

TRUSTCHECKPOINTS: Time Betrays Malware for Unconditional Software Root of Trust

Modern IoT and embedded platforms must start execution from a known trusted state to thwart malware, ensure secure firmware updates, and protect critical infrastructure. Current approaches to establish a root of trust depend on secret keys and/or specialized secure hardware, which drives up costs...

"Digital Camouflage": the LLVM Challenge in LLM-Based Malware Detection

Large Language Models LLMs have emerged as promising tools for malware detection by analyzing code semantics, identifying vulnerabilities, and adapting to evolving threats. However, their reliability under adversarial compiler-level obfuscation is yet to be discovered. In this study, we empirical...