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@laura_garcia shared a post, 5ย days ago
Software Developer, RELIANOID

๐—–๐—น๐—ผ๐˜‚๐—ฑ ๐—ฃ๐—ฟ๐—ผ๐—ฑ๐˜‚๐—ฐ๐˜ ๐——๐—ฒ๐˜ƒ๐—ฒ๐—น๐—ผ๐—ฝ๐—ฒ๐—ฟ (๐—™๐˜‚๐—น๐—น-๐˜๐—ถ๐—บ๐—ฒ | ๐—ฅ๐—ฒ๐—บ๐—ผ๐˜๐—ฒ / ๐—›๐˜†๐—ฏ๐—ฟ๐—ถ๐—ฑ)

๐Ÿš€ ๐—ช๐—ฒโ€™๐—ฟ๐—ฒ ๐—›๐—ถ๐—ฟ๐—ถ๐—ป๐—ด: ๐—–๐—น๐—ผ๐˜‚๐—ฑ ๐—ฃ๐—ฟ๐—ผ๐—ฑ๐˜‚๐—ฐ๐˜ ๐——๐—ฒ๐˜ƒ๐—ฒ๐—น๐—ผ๐—ฝ๐—ฒ๐—ฟ (๐—™๐˜‚๐—น๐—น-๐˜๐—ถ๐—บ๐—ฒ | ๐—ฅ๐—ฒ๐—บ๐—ผ๐˜๐—ฒ / ๐—›๐˜†๐—ฏ๐—ฟ๐—ถ๐—ฑ) At RELIANOID, weโ€™re accelerating the evolution of our cloud-native solutions โ€” and we need talented engineers to join us. Weโ€™re looking for ๐Ÿฎ ๐—–๐—น๐—ผ๐˜‚๐—ฑ ๐—ฃ๐—ฟ๐—ผ๐—ฑ๐˜‚๐—ฐ๐˜ ๐——๐—ฒ๐˜ƒ๐—ฒ๐—น๐—ผ๐—ฝ๐—ฒ๐—ฟ๐˜€ to join our Product Engineering team and help shape the future ..

careers RELIANOID hiring
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@devopslinks shared a link, 5ย days, 2ย hours ago
FAUN.dev()

Please stop externalizing your costs directly into my face

SourceHut spent20โ€“100%of weekly time mitigating hyperโ€‘aggressive LLM crawlers. That work caused dozens of short outages and delayed core projects. The crawlers ignorerobots.txt. They hit costly endpoints likegit blame. They scan full git logs and commits. They rotate randomUserโ€‘Agentsand thousands o.. read more ย 

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@devopslinks shared a link, 5ย days, 2ย hours ago
FAUN.dev()

Building a Least-Privilege AI Agent Gateway for Infrastructure Automation with MCP, OPA, and Ephemeral Runners

Introduces anAI Agent Gateway. It mediates agent requests, validates intent, enforcespolicy-as-code, and isolates execution inephemeral runners. Agents discover tools viaMCP. They submitJSON-RPCcalls and receiveOPAdecisions. Jobs queue and run in short-lived namespaces. Each run carries plan hashes,.. read more ย 

Building a Least-Privilege AI Agent Gateway for Infrastructure Automation with MCP, OPA, and Ephemeral Runners
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@devopslinks shared a link, 5ย days, 2ย hours ago
FAUN.dev()

The Only Claude Skill Every DevOps Engineer Needs

TheTerraform Claude SkillturnsClaude Codeinto a Terraform expert. It enforces modularity, strict naming, and consistent tagging. It treats thestate fileas the single source of truth. It wires in external tools: linting, security checks, and cost estimates. It forces real-doc validation and blocks in.. read more ย 

The Only Claude Skill Every DevOps Engineer Needs
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@devopslinks shared a link, 5ย days, 2ย hours ago
FAUN.dev()

The hunt for truly zero-CVE container images

Chainguard's Factory 2.0 andDriftlessAFrebuild images from source on upstream changes. They produce 2,000+ minimalzeroโ€‘CVEimages. Each image includes anSBOMand a cryptographicsignature. Docker'sDHIbuilds onDebianandAlpine. It mirrors Debian'snoโ€‘DSAtriage intoVEX. It also suppresses real CVEs until D.. read more ย 

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@devopslinks shared a link, 5ย days, 2ย hours ago
FAUN.dev()

Chinese Vulnerability Database: CNVD vs CNNVD Analysis

Investigation profilesCNNVDandCNVDechoCVE. They reveal manual errors and poor machine-readability. Chinaโ€™s July 2021RMSVmandates 48-hour reporting and bans pre-patch disclosure. Mapping gaps exist. The databases published about1.4kentries ahead ofCVE, with lead times measured in months... read more ย 

Chinese Vulnerability Database: CNVD vs CNNVD Analysis
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Magika is an open-source file type identification engine developed by Google that uses machine learning instead of traditional signature-based heuristics. Unlike classic tools such as file, which rely on magic bytes and handcrafted rules, Magika analyzes file content holistically using a trained model to infer the true file type.

It is designed to be both highly accurate and extremely fast, capable of classifying files in milliseconds. Magika excels at detecting edge cases where file extensions are incorrect, intentionally spoofed, or absent altogether. This makes it particularly valuable for security scanning, malware analysis, digital forensics, and large-scale content ingestion pipelines.

Magika supports hundreds of file formats, including programming languages, configuration files, documents, archives, executables, media formats, and data files. It is available as a Python library, a CLI, and integrates cleanly into automated workflows. The project is maintained by Google and released under an open-source license, making it suitable for both enterprise and research use.

Magika is commonly used in scenarios such as:

- Secure file uploads and content validation
- Malware detection and sandboxing pipelines
- Code repository scanning
- Data lake ingestion and classification
- Digital forensics and incident response