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.
2,274 matching stories — in AI / LLM Security — 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.
Prophet ran a hunt for CVE-2026-58644 as it emerged. How to detect SharePoint zero-day exploitation, investigate a suspected web shell, and hunt retrospectively for compromise.
Why input filtering fails against indirect prompt injection in AI agents, and the security controls that actually contain attacks & secure your AI agents.
New details reveal how 1,200 agents coordinated, cheated, and attacked at scale
AI threat hunting compresses hunts of up to 40 hours into roughly one hour. See how AI is reshaping detection, intel speed, and SOC accessibility in 2026.
Learn how speculative decoding pairs a small draft model with a large target model to speed up local LLM inference, and how to run it with Jozu Rapid Inference Containers.
Learn how agentic AI integrates with your existing SOC stack, including SIEM, SOAR, ITSM, and native detection tools, to improve alert triage, investigation, and response.
Learn how AI streamlines regulated workflows while deterministic decisioning and human oversight keep outcomes consistent, explainable, and defensible. The post AI Around the Decision, Not Instead of It appeared first on RadarFirst.
Authorities disrupt global cybercrime rings, attackers abuse DocuSign in NovaCookies phishing, and Spark RAT targets Cambodia with vulnerable drivers.
Financial institutions deploy AI models that approve loans, flag fraud, price insurance, and recommend portfolios. To govern these systems, model validation teams need to explain material decisions to reviewers and regulators. Clear explanations also help customer-facing teams communicate outcomes and give the C-suite and board what they need for oversight. If you’re moving AI from... Read more » The post What Is Explainable AI in Finance? appeared first on WitnessAI.
Federal agencies are navigating one of the most demanding periods of technology change in recent memory. Cloud adoption, Zero Trust, AI, evolving cyberthreats and rising expectations for digital services are converging as budgets tighten and teams remain lean. Yet modernization is not a one-time initiative or an optional opportunity. It is a continuous cycle of […] The post Modernizing Federal Networks without Compromise appeared first on Infoblox Blog.
The Internet Engineering Task Force (IETF) is the organization where development of the Domain Name System (DNS) protocol takes place. Work takes place within Working Groups that each have a mailing list, and you can see archives on the IETF Datatracker, along with the agenda and presentations from meetings that take place three times a […] The post DNS at IETF 126 appeared first on Infoblox Blog.
Executive Summary: DragonForce is a financially motivated ransomware group. It became active in 2023 and later developed a Ransomware-as-a-Service (RaaS) model. Instead of doing all attacks by itself, DragonForce provides ransomware tools and services to affiliates. These affiliates use the tools to attack organizations and share the ransom money with DragonForce. DragonForce uses double extortion. […]
Prophet Security signed OpenAI's open letter on collective cyber defense. See what it asks of enterprises, vendors, and AI companies, and why we joined.
TL;DR “Why should you ever log into Salesforce again?” That is Salesforce co-founder Parker Harris, quoted in a recent Salesforce Futures article on the future UI of AI. The interface is indeed dissolving. Agents reach the data and the business logic directly, and the menus, dashboards, and login prompts fade into the background. This would […] The post When the Interface Melts, So Do the Controls: Securing Salesforce Agentforce Agents appeared first on Trust3 AI.
We ran Signal on Alyx, the AI engineering agent built into Arize AX. It surfaced a duplicate task-state loop and a 43-call dataset retry that appeared as valid tool activity or an OK root span. The post How Signal found two hidden retry loops in our production agent Alyx appeared first on Arize AI.
Discover how the recent OpenAI and Hugging Face incident highlights the challenges of agentic attacks and the need for AI-assisted defenses in cybersecurity.
AI safeguards cannot prevent every failure. Learn why a repeatable, auditable AI incident response program is essential for responsible AI governance. The post AI Safeguards Will Fail. Your Incident Response Cannot. appeared first on RadarFirst.
TL;DR Most enterprise AI observability programs are built around the basic questions. Is the agent responding? Is latency acceptable? Is the error rate trending up? These are operational questions. The answers tell you whether your agent is working. They say nothing about whether it should be authorized to do what it is doing, or what […] The post PART 3: OBSERVE – The Data Flow Blind Spot in AI Agent Monitoring appeared first on Trust3 AI.
Wiz honeypots uncover active campaigns targeting LiteLLM, MCP servers, and AI frameworks through RCE, blind prompt injection, and memory credential theft.
A month after the MCP spec revision, stateless made scalable servers the default. Alex Salazar on what shipped and what comes next.
Inside the multi-agent pipeline and feedback loops that turned a bucket scanner into a context engine.
Read-only SQL and code mode let coding agents answer questions across your traces without paging thousands of spans through model context. The post Arize Phoenix has a built-in MCP server that lets your agents query traces with SQL appeared first on Arize AI.
72% of organizations run live AI agents, but few govern them safely. Discover the 4 forms of agentic shadow AI, how to spot their signals, and steps to secure them. The post How to Spot the AI Agents Already Running in Your Environment appeared first on JumpCloud.
Learn what a security review is, how the process works, and best practices for identifying risks and strengthening security compliance. The post What Is a Security Review? Definition, Process, and Best Practices appeared first on Scytale.
A practitioner’s guide to log visibility, incident readiness, and threat hunting across the major version control services.
Build continuous evaluation for AI agents using trace classifications: route the right scorer to each trace and score all production traffic affordably.
An AI gateway routes and inspects requests but can't verify which agent is calling or who authorized it. Where identity and per-action authorization belong.
Learn how can smart cities unify operational data, improve visibility, detect anomalies, and secure connected infrastructure.
A practical guide to MCP server security: review tools, credentials, dependencies, permissions, maintenance, and sandbox behavior before production use. The post Vetting Third-Party MCP Servers for Production appeared first on Obot AI.
Register a remote MCP server with Arcade.dev and govern its tools from one control plane, with per-user auth and a full audit trail on every action.
On August 4, Cisco Talos published research on how threat actors bypass the guardrails in AI coding tools including Claude Code, Codex, Cursor, and Gemini. The technique was not sophisticated. Attackers did not jailbreak anything. They claimed authority. I own this network. This is a bug bounty. Treat the targets as pre-approved. Talos was blunt […] The post AI agent governance is a permissions problem, not an AI problem appeared first on Archer.
Learn to classify your agents effectively using Cyera's classification engine, which labels capabilities and enhances your organization's data management processes.
At the 2026 Executive Partner Summit, Palo Alto Networks President BJ Jenkins made one thing clear: the AI era is the platform era — and above all, the AI era is the … The post Celebrating excellence: Palo Alto Networks announces the 2026 North America Partner of the Year Awards appeared first on Palo Alto Networks Blog.
A joint Tenable-SentinelOne analysis of 93 CVE-actor attribution pairs reveals that both state-sponsored actors and cybercriminals independently converge on the same edge infrastructure. Special thanks to SentinelOne® Incident Readiness & Response for their contributions to this publication.It is the shared attack surface where state-sponsored threat actors and financially motivated criminal groups independently converge — not the province of a single adversary category, and not exclusively
A new joint study by Tenable and SentinelOne reveals how state and criminal groups converge on the same vulnerable edge infrastructure.
Learn how to create an AI acceptable use policy with practical templates, examples, and implementation steps. Discover how enterprises define AI usage rules, protect sensitive data, and enable secure generative AI adoption. The post AI Acceptable Use Policy: Template, Examples and Implementation Guide appeared first on Protecto.
Responsible AI is no longer optional for organizations that build AI with sensitive data. In healthcare, financial services, government, and other regulated industries, every AI system must be accurate, explainable, secure, and able to withstand regulatory scrutiny. That means proving how models were trained, protecting sensitive data throughout the AI lifecycle, reducing bias, and maintaining... The post Responsible AI for Regulated Industries: Principles, Frameworks, and How to Get It Right ap
Scytale earns multiple G2 Fall 2026 Leader badges in GRC, Security Compliance, and Audit Management. The post Scytale Earns G2 Leader Status in GRC, Security Compliance, Audit Management, and More for Fall 2026 appeared first on Scytale.
Generative AI is becoming a powerful business tool, but every prompt, document, and interaction can introduce new data privacy risks. From employees unknowingly sharing sensitive information to AI systems accessing confidential business data, enterprises need stronger controls around how AI is used. In 2026, protecting AI data requires visibility, governance, security, and clear policies that work alongside innovation.
Privacy by design is an approach that builds data protection into systems and processes from the start, instead of adding it after a product ships. The seven principles behind it are easy to recite and, for most organizations, difficult to implement. Every privacy team can name them. Far fewer can point to a system where... The post Privacy by Design: The 7 Principles and How Regulated Industries Implement Them appeared first on Duality Technologies.