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Tag: security systems

  • Hacker News: Operationalizing Macaroons

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    Kurt Seifried
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    Source URL: https://fly.io/blog/operationalizing-macaroons/ Source: Hacker News Title: Operationalizing Macaroons Feedly Summary: Comments AI Summary and Description: Yes Summary: The text provides a deep dive into the engineering and security aspects of Macaroon tokens used by Fly.io, highlighting their implementation, operational nuances, and the associated security measures. For professionals in AI, cloud, and infrastructure security, it…

  • Cisco Security Blog: The Benefits of a Broad and Open Integration Ecosystem

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    Kurt Seifried
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    Source URL: https://feedpress.me/link/23535/16991983/the-benefits-of-a-broad-and-open-integration-ecosystem Source: Cisco Security Blog Title: The Benefits of a Broad and Open Integration Ecosystem Feedly Summary: Since inception, Cisco XDR has followed the Open XDR philosophy. We integrate telemetry and data from dozens of Cisco and third-party security solutions. AI Summary and Description: Yes Summary: The text discusses Cisco XDR’s adherence to…

  • Wired: The Quantum Apocalypse Is Coming. Be Very Afraid

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    Kurt Seifried
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    Source URL: https://www.wired.com/story/q-day-apocalypse-quantum-computers-encryption/ Source: Wired Title: The Quantum Apocalypse Is Coming. Be Very Afraid Feedly Summary: What happens when quantum computers can finally crack encryption and break into the world’s best-kept secrets? It’s called Q-Day—the worst holiday maybe ever. AI Summary and Description: Yes Summary: The text discusses the impending threat posed by the advent…

  • Rekt: Not So Safe

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    Kurt Seifried
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    Source URL: https://www.rekt.news/not-so-safe Source: Rekt Title: Not So Safe Feedly Summary: North Korea’s Lazarus Group stole $1.4B from Bybit’s signers by exploiting a simple vulnerability in Safe’s system. A single yaml.load execution bypassed high-end security, turning a supposedly impenetrable system into one of the industry’s biggest disasters. AI Summary and Description: Yes Summary: The text…

  • Threat Research Archives – Unit 42: Uncovering .NET Malware Obfuscated by Encryption and Virtualization

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    Kurt Seifried
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    Source URL: https://unit42.paloaltonetworks.com/malware-obfuscation-techniques/ Source: Threat Research Archives – Unit 42 Title: Uncovering .NET Malware Obfuscated by Encryption and Virtualization Feedly Summary: AI Summary and Description: Yes **Summary:** This article provides a detailed examination of sophisticated obfuscation techniques utilized by various malware families, specifically focusing on how these methods enhance the ability of malware to evade…

  • Enterprise AI Trends: The New Alexa: Amazon’s Consumer AI Strategy Deep Dive

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    Kurt Seifried
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    Source URL: https://nextword.substack.com/p/the-new-alexa-amazons-consumer-ai Source: Enterprise AI Trends Title: The New Alexa: Amazon’s Consumer AI Strategy Deep Dive Feedly Summary: My thoughts on Alexa’s second act (as a former Alexa PM) AI Summary and Description: Yes Summary: The text discusses Amazon’s announcement of Alexa Plus and its enhanced capabilities, leveraging deep integrations within Amazon’s ecosystem to…

  • CSA: Simplicity is Complexity Resolved

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    Kurt Seifried
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    Source URL: https://www.zscaler.com/cxorevolutionaries/insights/simplicity-complexity-resolved Source: CSA Title: Simplicity is Complexity Resolved Feedly Summary: AI Summary and Description: Yes **Summary:** This text discusses the importance of simplifying security architectures, specifically through the lens of zero trust principles. It draws a parallel between SpaceX’s innovative approach to rocket design and the need for CISOs to streamline and optimize…

  • Hacker News: AI Mistakes Are Different from Human Mistakes

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    Kurt Seifried
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    Source URL: https://www.schneier.com/blog/archives/2025/01/ai-mistakes-are-very-different-from-human-mistakes.html Source: Hacker News Title: AI Mistakes Are Different from Human Mistakes Feedly Summary: Comments AI Summary and Description: Yes Summary: The text highlights the unique nature of mistakes made by AI, particularly large language models (LLMs), contrasting them with human errors. It emphasizes the need for new security systems that address AI’s…