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@viktoriiagolovtseva shared a post, 2 weeks, 3 days ago

Post-mortem Incident Review

Why Structured Post-mortem Reviews Matter Security incidents, outages, and failures are inevitable, especially in fast-moving agile environments. But what separates high-performing teams from the rest is how they learn from them. A well-run incident postmortem (or post-mortem meeting) focuses on unc..

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@kala shared an update, 2 weeks, 4 days ago

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A Meta AI Agent Posted Without Permission. Then Things Got Worse.

#OpenCla... #Securit... #Authori... #Faceboo... #AI assi...

A Meta AI agent posted to an internal forum without authorization, triggering a Sev 1 incident that exposed proprietary code and user data for two hours. The advice it gave was wrong. The engineer followed it anyway. This wasn't a one-off - autonomous agents now account for more than 1 in 8 enterprise AI breaches, and most organizations have no mechanism to stop them from acting beyond their intended scope.

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@mashka posted an event From Code to Runtime: Why SAST + DAST Are Both Essential for Modern AppSec by Xygeni , 2 weeks, 4 days ago.

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@laura_garcia shared a post, 2 weeks, 4 days ago

Software Developer, RELIANOID

Discover why Cloud Security Posture Management (CSPM) is a game-changer for companies in today's digital landscape!

Discover why Cloud Security Posture Management (CSPM) is a game-changer for companies in today's digital landscape! In our latest article, we take you on a narrative journey exploring the vital role CSPM plays in maintaining robust cloud security—from continuously monitoring digital infrastructures ..

AIStor is an enterprise-grade, high-performance object storage platform built for modern data workloads such as AI, machine learning, analytics, and large-scale data lakes. It is designed to handle massive datasets with predictable performance, operational simplicity, and hyperscale efficiency, while remaining fully compatible with the Amazon S3 API. AIStor is offered under a commercial license as a subscription-based product.

At its core, AIStor is a software-defined, distributed object store that runs on commodity hardware or in containerized environments like Kubernetes. Rather than being limited to traditional file or block interfaces, it exposes object storage semantics that scale from petabytes to exabytes within a single namespace, enabling consistent, flat addressing of vast datasets. It is engineered to sustain very high throughput and concurrency, with examples of multi-TiB/s read performance on optimized clusters.

AIStor is optimized specifically for AI and data-intensive workloads, where throughput, low latency, and horizontal scalability are critical. It integrates broadly with modern AI and analytics tools, including frameworks such as TensorFlow, PyTorch, Spark, and Iceberg-style table engines, making it suitable as the foundational storage layer for pipelines that demand both performance and consistency.

Security and enterprise readiness are central to AIStor’s design. It includes capabilities like encryption, replication, erasure coding, identity and access controls, immutability, lifecycle management, and operational observability, which are important for mission-critical deployments that must meet compliance and data protection requirements.

AIStor is positioned as a platform that unifies diverse data workloads — from unstructured storage for application data to structured table storage for analytics, as well as AI training and inference datasets — within a consistent object-native architecture. It supports multi-tenant environments and can be deployed across on-premises, cloud, and hybrid infrastructure.