arXiv:2608.02681v1 Announce Type: new Abstract: Batch prompting is a practical inference strategy for large language models, but its safety implications remain underexplored. We show that the success …
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arXiv:2608.02681v1 Announce Type: new Abstract: Batch prompting is a practical inference strategy for large language models, but its safety implications remain underexplored. We show that the success …
arXiv:2608.02678v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) systems are vulnerable to corpus poisoning: an attacker who inserts a crafted document into the retrieval corpus ca…
arXiv:2608.02674v1 Announce Type: new Abstract: With the widespread deployment of large foundation models (LFMs) in open environments, safety threats are shifting from black-box jailbreaks toward whit…
arXiv:2608.02672v1 Announce Type: new Abstract: Cloud misconfiguration remains a leading cause of security incidents, yet whether LLMs and SLMs can generate security-compliant Infrastructure-as-Code i…
arXiv:2608.02671v1 Announce Type: new Abstract: Malware detection using Hardware Performance Counters (HPC) has emerged as a promising solution to improve the security of computing systems as a comple…
arXiv:2608.02670v1 Announce Type: new Abstract: Coding agents increasingly run inside organizations whose security controls (scoped credentials, restricted egress, read-only filesystems, non-root exec…
arXiv:2608.02669v1 Announce Type: new Abstract: Docker Hub is the registry underneath most container deployments, and a flaw in a widely reused base image is inherited by every image built on it. Prio…
arXiv:2608.02665v1 Announce Type: new Abstract: A benchmark score is a measurement instrument, yet most benchmarks read each item at a single canonical surface form. We ask whether that reading is fai…
arXiv:2608.02664v1 Announce Type: new Abstract: Deploying ML models in regulated decision-making (credit underwriting, fraud detection, loan approval) requires demonstrating fairness and robustness to…
arXiv:2608.02657v1 Announce Type: new Abstract: Agentic LLMs are vulnerable to indirect prompt injection (IPI) attacks, e.g., malicious side-tasks hidden in external tool results. While many efforts h…
arXiv:2608.02656v1 Announce Type: new Abstract: The Secured data safe guard transaction with multi-tenant environments run on private-protected authenticate platforms runs by secured handed environmen…
arXiv:2608.02627v1 Announce Type: new Abstract: Zero Trust Architecture (ZTA) principles need rigorous network segmentation and ongoing verification to reduce implicit trust and lateral threat propaga…
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arXiv:2608.01020v1 Announce Type: new Abstract: Collaborative inference deploys Large Vision-Language Models (LVLMs) by partitioning computation between edge devices and the cloud. While withholding r…
arXiv:2608.00965v1 Announce Type: new Abstract: Cryptographic code is critical infrastructure that must be correct, yet formally verifying production libraries remains difficult. Existing language-mod…
arXiv:2608.00958v1 Announce Type: new Abstract: This paper develops a single method, find what an accepted result silently assumed, make it a variable, and prove what follows once it is dropped, and s…
arXiv:2608.00954v1 Announce Type: new Abstract: The threat of quantum computers to classical public-key cryptography has created an urgent need to evolve secure communication protocols with post-quant…
arXiv:2608.00937v1 Announce Type: new Abstract: Autonomous AI agents, increasingly empowered by large language models, are becoming important components of human-machine systems for high-stakes decisi…