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@faun shared a link, 10 months ago

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The Cybersecurity Blind Spot in DevOps Pipelines

DevOps pipelines serve as superhighways for cybercriminals to target with credential leaks, supply chain infiltration, misconfigurations, and dependency vulnerabilities. Security must evolve with development to combat these sophisticated attacks... read more

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What Is IDOR? Finding and Preventing Insecure Direct Object References in AWS APIs

Attackers swap predictable IDs. They slip intoAWS APIs,Lambda functions, internal tools. Fuzzers likeffufflag sneaky HTTP 200s.Burp Intruderbubbles up 404 probes.CloudWatchlogs trace every call. Random UUIDs seal ID gaps... read more

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10 Best API Monitoring Tools in 2025

API monitoring tracks latency, errors and uptime. Tools tag real-time metrics. They fire alerts. They map traces. They automate tests. They crunch analytics. Examples span OSS starsPrometheus,Graphiteand SaaS champsAppDynamics,Postman. Each hooks into CI/CD pipelines and plants global synthetic prob.. read more

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Building a Secure, Scalable, and Automated Cloud-Native Platform on AWS with EKS, GitOps, and…

The blueprint carves out production-grade AWS infra. Terraform orchestrates VPCs with public and private subnets, deploys a Bastion host, spins up private EKS clusters, and stands up an internet-facing ALB armed with SSL/TLS. Argo CD drives GitOps. The CI pipeline runs SAST, builds Docker images, hu.. read more

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MCP Catalog: Finding the Right AI Tools for Your Project

Docker Desktop hatches a betaMCP CatalogandToolkit. It unleashes 100+ containerized Model Context Protocol servers loaded with metadata and use-case filters. Teams fire them via GUI or CLI. The catalog carvesDocker-builtimages from community builds, runs supply-chain scans, and seals isolation. Cust.. read more

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We Added Chaos to Our CI/CD Pipelines — It Made Everything More Stable.

Wix’sMREteam injectsAI-drivenchaosintoCI/CDpipelines. Mobile releases gain speed and rock-solid stability. They harness hackathon-born prompt tests to bulletproof builds and deployments. Signal: AI resilience trials in pipelines mark a shift from rigid builds to probabilistic validation... read more

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The Art of Azure RBAC for Kubernetes: A Complete Guide to Access Control Mastery

This article dives into Azure RBAC for Kubernetes. It maps each persona to pinpoint roles per namespace. Permissions stay minimal from the get-go. It ties role bindings toAzure AD groups, splits dev and prod, and flips on audit logs. Quarterly reviews, crisp docs keep RBAC lean and current... read more

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@faun shared a link, 10 months ago

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Critical VMware Tools VGAuth Vulnerabilities Enable Full System Access for Attackers

Two CVE-2025 vulns in VMware Tools allow SYSTEM access via named pipe hijacking and path traversal. Upgrade to 12.5.1+ ASAP for fixes. Administrators must upgrade... read more

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@faun shared a link, 10 months ago

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Serverless: The Illusion of Choice

A LinkedIn thread exposes a hack around AWS EventBridge’s256KBlimit. Someone chains Lambdas tocompressthendecompressevents. Serverless traps lurk: blown-upIAMpermissions. Triggers with zero validation. Wide-openegress. Unscanned packages fueling supply chain bombs... read more

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GitHub Spark in public preview for Copilot Pro+ subscribers

GitHub Spark spins natural-language prompts into full-stack AI apps in minutes. It tapsClaude Sonnet 4to scaffold UI and server logic. It hooks updata storage,LLM inference, hosting,GitHub Actions,Dependabot, plus multi-LLM smarts from OpenAI, Meta, DeepSeek and xAI—zero config. Trend to watch: AI .. read more

Gemini 3 is Google’s third-generation large language model family, designed to power advanced reasoning, multimodal understanding, and long-running agent workflows across consumer and enterprise products. It represents a major step forward in factual reliability, long-context comprehension, and tool-driven autonomy.

At its core, Gemini 3 emphasizes low hallucination rates, deep synthesis across large information spaces, and multi-step reasoning. Models in the Gemini 3 family are trained with scaled reinforcement learning for search and planning, enabling them to autonomously formulate queries, evaluate results, identify gaps, and iterate toward higher-quality outputs.

Gemini 3 powers advanced agents such as Gemini Deep Research, where it excels at producing well-structured, citation-rich reports by combining web data, uploaded documents, and proprietary sources. The model supports very large context windows, multimodal inputs (text, images, documents), and structured outputs like JSON, making it suitable for research, finance, science, and enterprise knowledge work.

Gemini 3 is available through Google’s AI platforms and APIs, including the Interactions API, and is being integrated across products such as Google Search, NotebookLM, Google Finance, and the Gemini app. It is positioned as Google’s most factual and research-capable model generation to date.