Funding rounds, leadership changes, incidents, new capabilities and announcements across the vendors in this catalog — collected automatically from vendors' own public feeds. Product release versions are on their own page, so the landing feed here never reads as one vendor's changelog.Where this comes fromEvery item links to the vendor's own published source: a GitHub release feed, a changelog, a status page, an SEC filing or a company blog. Nothing here is written or editorially reviewed by 0-Doubt, and nothing is a recommendation — it is machine-collected public record, labelled the same way as all other baseline content on the platform. Coverage is uneven by design: a vendor that publishes no public feed will not appear, and that absence is not a judgement about the vendor.
1,465 matching stories — announcement, in Cloud-Native Application Protection (CNAPP) — showing up to 3 per vendorPer-vendor capWhile browsing, no single vendor may fill more than three slots on any one page, so a vendor with a chatty release cadence cannot buy the page you are looking at. That means a page can render fewer stories than the count above. Searching a headline or naming a vendor turns the cap off, because then you have asked to see everything that matches.
AI agents are changing the cloud security boundary, connecting models, tools, identities, data, and production workflows. This blog explains why prompt-level safety is not enough, and how AWS-native controls like Bedrock Guardrails, IAM, SCPs, permission boundaries, and AgentCore policies can create preventive guardrails that stop unsafe cloud actions before they reach production. The post Securing AI Workloads in AWS: A Preventive Guardrails Guide (2026) appeared first on Blast Security Preempt
Why solving data challenges for the disconnected operator is the key to unlocking mission-critical AI. The post From the Tactical Edge to AI Advantage: The Case for a Unified Data Fabric in Defense Organizations first appeared on CTERA.
Why solving data challenges for the disconnected operator is the key to unlocking mission-critical AI. The post From the Tactical Edge to AI Advantage: The Case for a Unified Data Fabric in Defense Organizations first appeared on CTERA.
As a global business, where do you run services and hold data? Well, this used to be a relatively simple... The post Securing the Fragmentation of the Modern Enterprise: The Data Hosting Conundrum appeared first on Skyhigh Security.
Developers want less time reading docs and more time shipping. Brivo and Eagle Eye Networks APIs are now AI-Native, rolling out the llms.txt standard across all video and access documentation… The post Build Faster: Brivo API Documentation is Now AI-Native first appeared on Brivo.
AI workflows are forcing enterprises to rethink decades of assumptions about storage and file services The post I Thought Hybrid Cloud Storage Was a Solved Problem. GenAI Proves It Is Not. first appeared on CTERA.
AI adoption is accelerating faster than most healthcare organizations can securely govern it. For healthcare IT, InfoSec, and engineering leaders, the urgency is palpable. Your smartest people want to drive... The post How to Secure AI Workloads in Healthcare Cloud Environments appeared first on ClearDATA.
We recently published an exploit chain for the Google Pixel 9 that demonstrated it was possible to go from a zero-click context to root on Android in just two exploits. The Dolby 0-click vulnerability existed across all of Android, until it was patched in January 2026. While we had an exploit chain for the Pixel 9, we wanted to see if it was possible to write a similar exploit chain for Pixel 10. Updating the Dolby Exploit Altering our exploit for CVE-2025-54957 was fairly straightforward. The m
Key Takeaways AI security architecture determines whether AI can reason or only retrieve. Without a unified data model, security AI is forced to guess across fragmented systems. Verifiable security AI starts at the data layer. A unified ontology enables transparent investigations backed by raw evidence, not probabilistic answers. Structural design, not model choice, is the real differentiator. Platforms built on unified architecture deliver faster, provable investigations that teams can trust. W
As AI systems move from experimentation into production, the way infrastructure is deployed and governed is fundamentally changing. Traditional cloud security models were built around human-operated environments where infrastructure changes happened relatively slowly and predictably. Agentic AI changes that dynamic entirely.
TL;DR AI-driven attacks on containerized environments are no longer theoretical. Frontier models can find vulnerabilities in hardened systems in hours and chain them into working exploits before your team has finished triaging the alert. When an attack moves that fast, the time your security program depends on between discovery and exploitation no longer exists. This …
AI coding tools are making developers faster — but faster development also requires better visibility, stronger review workflows, and more reliable remediation. This is a practical governance guide for teams adopting Codex, Claude Code, Cursor, Windsurf, and other AI coding agents.
Security compliance is not a moment in time; it is a sustained commitment. Today, we are proud to announce that... The post Skyhigh Security Achieves SOC 2 Type II Compliance for the Complete SSE Cloud Platform appeared first on Skyhigh Security.
Claude Mythos proved that every organization should assume vulnerabilities will be found and breaches can happen. But the attack chain only starts there. The real cloud security test is how far your environment lets an attacker go. As AI accelerates attack-path discovery, the answer is not faster response alone. It is a hardened, secure-by-design cloud architecture that blocks the attacker’s next move before it succeeds. The post The Mythos Lesson: Why Your Cloud Must Defend Itself appeared firs
A malicious release of the lightning PyPI package ships a credential-stealing Bun payload that runs on import. Snyk has a live advisory. Here's what's in the package, what to rotate, and how the payload pattern connects to the Mini Shai-Hulud npm campaign one day earlier.
A new npm supply chain attack self-branded "Mini Shai-Hulud" compromised four SAP-ecosystem packages on April 29, 2026. Snyk has live advisories. Here's the technical breakdown, IOCs, and what to do.
Bridge the gap to autonomous fixes. Snyk and Atlassian integrate to transform Jira security tickets into precision fixes using Snyk Studio AI, eliminating context switching and resolving vulnerabilities in minutes.
Detection alone cannot keep up with AI-speed development. AI-native remediation is the next layer — helping teams fix, validate, and track vulnerabilities in AI-generated code at every stage of the SDLC.
Anthropic’s Mythos marks a turning point: AI can now autonomously turn disclosed vulnerabilities into real-world exploit chains in hours, collapsing the window defenders once relied on. For security teams, “hard to exploit” and “no known exploit” are no longer meaningful comfort signals. The new defense standard is continuous, adversarial validation that proves what can actually be exploited in your environment. The post AI-Driven Exploit Generation: What Mythos Means for Cyber Defense appeared
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A single data breach can disrupt patient care, damage trust, and trigger massive compliance penalties. Healthcare organizations face relentless cyber threats that specifically target highly sensitive patient data. Defending against... The post Healthcare Ransomware Prevention: Essential Strategies to Secure Your Cloud Infrastructure appeared first on ClearDATA.
