Tag: paper

  • Cloud Blog: How to Build Highly Available Multi-regional Services with Cloud Run

    Source URL: https://cloud.google.com/blog/topics/developers-practitioners/how-to-build-highly-available-multi-regional-services-with-cloud-run/ Source: Cloud Blog Title: How to Build Highly Available Multi-regional Services with Cloud Run Feedly Summary: Ever worry about your applications going down just when you need them most? The talk at Cloud Next 2025, Run high-availability multi-region services with Cloud Run, dives deep into building fault tolerant and reliable applications using…

  • Schneier on Security: Indirect Prompt Injection Attacks Against LLM Assistants

    Source URL: https://www.schneier.com/blog/archives/2025/09/indirect-prompt-injection-attacks-against-llm-assistants.html Source: Schneier on Security Title: Indirect Prompt Injection Attacks Against LLM Assistants Feedly Summary: Really good research on practical attacks against LLM agents. “Invitation Is All You Need! Promptware Attacks Against LLM-Powered Assistants in Production Are Practical and Dangerous” Abstract: The growing integration of LLMs into applications has introduced new security risks,…

  • The Register: Internet mapping and research tool Censys reveals state-based abuse, harassment

    Source URL: https://www.theregister.com/2025/09/03/censys_abuse_sigcomm_paper/ Source: The Register Title: Internet mapping and research tool Censys reveals state-based abuse, harassment Feedly Summary: ‘Universities are being used to proxy offensive government operations, turning research access decisions political’ Censys Inc, vendor of the popular Censys internet-mapping tool, has revealed that state-based actors are trying to abuse its services by hiding…

  • OpenAI : Estimating worst case frontier risks of open weight LLMs

    Source URL: https://openai.com/index/estimating-worst-case-frontier-risks-of-open-weight-llms Source: OpenAI Title: Estimating worst case frontier risks of open weight LLMs Feedly Summary: In this paper, we study the worst-case frontier risks of releasing gpt-oss. We introduce malicious fine-tuning (MFT), where we attempt to elicit maximum capabilities by fine-tuning gpt-oss to be as capable as possible in two domains: biology and…