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.
23,918 matching stories — announcement — 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.
Belgian prosecutors confirm an intern at SHAPE, NATO's Supreme Headquarters Allied Powers Europe, is under active investigation for spying on behalf of an undisclosed "third country" and for criminal-organization membership — discovered from inside the alliance's principal command center, not stopped at its perimeter.
Why we built Dwight : So what is Dwight, plainly? : Dwight is Collibra’s internal agentic analyst: an AI analyst that queries data for you. You ask a question in plain language, and it figures out the answer the way a human analyst would. The intention was to provide the entire company insights at the speed of AI, grounded in context we actually trust and govern, instead of everyone waiting in a queue for one of a handful of analysts. What was the intent around building Dwight, and…
Adversaries do not need a working quantum computer today to compromise tomorrow's cryptography. They need storage, patience, and a sufficiently long-lived secret. The act that matters has already happened by the time the cryptanalysis is feasible.
Learn how to stream sensor data to an edge AI model over MQTT in C#, using MQTT 5 flow control and manual acknowledgment to set the model's intake rate.
We fixed a local privilege escalation issue in the NetBird client daemon in v0.76.0. Here is what the issue was, who it affected, how we fixed it, and how we handle security reports.
A practical framework for building secure, scalable secrets management.
A tax-season malware campaign is impersonating the Income Tax Department, sending fake penalty notices over WhatsApp. Victims who tap "Download Documents" install malware capable of harvesting OTPs and banking credentials. The advisory also covers a wider ecosystem of refund SMS fraud, cloned e-Filing portals, and fake e-PAN emails targeting Indian taxpayers this season. Authors : Shobhit Mishra
AI cost tracking done right: trace overspend to the request, span, and agent decision that caused it, then enforce budgets before the invoice hits.
AI agents are doing more than just generating code. Increasingly, they are working autonomously on complex coding challenges, touching production APIs, databases, and infrastructure across development environments, often without thorough human review. To perform these operations and access multiple systems, agents rely on developer secrets and non-human identities (NHI). But often, developers lack a secure way to share these secrets, leading to overprivileged, invisible access. The growth in aut
In our last post, we shared how we began to scale our security code review process with SAGE. We discussed how we gathered historical Product Security (ProdSec) review records to create a 1Password-specific ruleset, the three-stage Finder/Critic/Judge pipeline, and the limitations of our v1 implementation. Above all, human ProdSec reviewers still had to bring full context to the findings: where the trust boundaries lie, which directories are sensitive, and whether mitigations exist elsewhere in
Check out GreyNoise's new Head of Adversary Engagement, Mark Mager, on why traditional detection engineering can't keep pace with CVE growth — and the agentic pipeline replacing it.
Part 1 attacked the MCP server itself. This part assumes all of that is patched and breaks in through the identity layer instead — where nothing is a bug you can close, and the server does exactly what it was told by the wrong person. We walk the 2026-07-28 authorization spec and the RFCs behind it, the confused-deputy attack that comes from getting consent wrong, how EMA and ID-JAG move consent to the IdP — and the four gaps that remain open afterwards, where every token is valid and nothing in
We scanned 33,563 MCP server builds and 475,865 AI agent tools. Nearly half raised security concerns, including covert instructions written in plain English.
Moonshot's new open-weight flagship is #1 on WebDev Arena, beating Claude Fable 5 and GPT 5.6 Sol Max in blind human votes. On the Cyber Defense Benchmark it lands #7 of 22 at 33% coverage — the best Kimi yet, but behind open-weight leader GLM 5.2 on coverage, cost, and speed. Why general capability doesn't transfer to defense, and what would close the gap.
AI is accelerating software development and giving attackers machine-speed capabilities. Security teams must continuously test AI-built code, govern agents, and independently validate every finding.
Today, we announced an expanded collaboration to bridge the gap between AI agents and the enterprise context they need, helping organizations build production-ready AI applications and agents using OpenAI models with Elasticsearch.
Learn how to use Fastly Fiddle to test and verify VCL on real infrastructure. This sandbox tool helps both developers and coding agents debug edge configurations.
The distinction that the industry is still debating (AI risk vs. adversarial risk, safety vs. security) stopped mattering the moment the models decided the exam was too hard.Here's what that means in practice.
Financial services businesses are embracing AI at a rapid pace. However, while AI is the greatest opportunity the industry has ever seen, it is also the greatest risk. And this risk has very little to do with the technology itself. The real danger is leadership expectation. The less leaders understand AI, the more they expect from it. That gap, between belief and reality, is where systems break, teams burn out, and resilience collapses. This is the stress fracture running through financial servi
Netcraft built its name on one thing done exceptionally well: finding phishing sites and getting them taken down. Decades of registrar relationships and a 33-minute median takedown time back that reputation up. So why do teams search for Netcraft alternatives at all? Usually because their problem outgrew the tool. Phishing is no longer a standalone […] The post Netcraft Alternatives: 6 Strong Competitors to Weigh in 2026 appeared first on Bolster AI.
An AI agent control plane governs identity, tool calls, and audit trails fleet-wide. Here's what production teams learned building one in 2026. The post The AI Agent Control Plane: What Production Governance Actually Requires in 2026 appeared first on Obot AI.
Your sensitive files live across multiple clouds. Here is why single-platform security fails at the boundary, and what actually works.
Industrial AI entwickelt sich zur Grundlage einer neuen Generation intelligenter und regulierungskonformer Lieferketten. In Kombination mit vertrauenswürdigen digitalen Identitäten und dem Digitalen Produktpass (DPP) entstehen automatisierte Prozesse, die Produktdaten sicher, nachvollziehbar und über den gesamten Lebenszyklus hinweg nutzbar machen.
Air-gapped servers no longer equal sovereignty. See why AI agent security, not geography, now defines control across defense infrastructure worldwide.
A benchmark test at OpenAI went looking for a way out of its sandbox in mid-July, found one, and ended...
Recon, stolen credentials, hidden C2, and rebuild-or-patch. Four Hugging Face breach decisions that show whether you can catch an attack in progress. Category: News
Security data compounds 35 to 50% a year while SOC headcount stays flat. Part 1 of our Agentic SecOps series on why hiring can't close the gap.
Agentic SecOps is a model where AI agents do the SOC's everyday work, onboarding, search, detection, and investigation, with a human approving what matters.
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As enterprises deploy AI agents, an entirely new security ecosystem is emerging. AI discovery platforms, MCP gateways, workforce AI governance platforms, automation platforms, and runtime authorization solutions all promise to secure AI agents—but they solve fundamentally different problems. Understanding where each category fits is becoming just as important as choosing the right products. The post Understanding the AI Agent Security Ecosystem: Roles, Responsibilities, and Where Runtime Authori
Yesterday, Cyera announced the acquisition of Oasis Security for a reported $1 billion. The cybersecurity world is taking note of the valuation — and it should. At an estimated $10–20M in ARR, this deal was priced at 50–100x revenue, topping Google's acquisition of Wiz (46x) and Okta's acquisition of Auth0 (43x).
If you work in security, compliance, or procurement, you’ve probably lived on both sides of the vendor risk table without even labeling it that way. Some days, you’re evaluating a vendor before signing a contract. On other days, you’re the one being evaluated, filling out a security questionnaire because a customer wants proof you can be trusted. These are two different jobs. Most platforms ... Read more The post Assess vs Answer: Which Side of Vendor Risk Are You On? appeared
Streamline your SAR filing process with Unit21's SAR Agent. Generate evidence-grounded, defensible narratives automatically while maintaining human accountability.
Detect and stop zero-day prompt injections in real time. Learn how SPIRE by Alice safeguards generative AI with semantic threat detection.
LLM compliance and GenAI regulatory requirements for enterprise teams — covering the EU AI Act, NIST AI RMF, and ISO 42001, and what your posture needs now.
Why generative AI reflects harmful stereotypes, the real-world risks of biased systems, and how teams can mitigate them with practical tools and strategies.
This datasheet illustrates how ZeroLock blocks attacks like the one against Fairlife's Nutanix systems. The post Stopping the Fairlife Playbook on ESXi appeared first on Vali Cyber.
What Is AI Governance?  AI governance best practices require a comprehensive framework focused on accountability, transparency, risk management, and human oversight. Organizations should build centralized standards with federated execution, classifying models by risk, requiring human-in-the-loop interventions for sensitive decisions, and continuously auditing systems for bias, security vulnerabilities, and data privacy compliance. Effective AI governance requires […] The post AI Gover
Risks range from geopolitics, quantum computing, and skills shortages to AI threats