510 press releases in English indexed under cybersecurity.
Atos positioned as a Leader in cybersecurity solutions and services in the 2026 ISG Provider Lens™ report for France
Every software build is assembled from open source packages, base images, and libraries, with your code on top. When one of those components is missing or has drifted, the build fails. At agent speed, those failures multiply, and no team can clear them as manual exceptions. Project-by-project registry sprawl makes it worse because retention rules, storage limits, and publish access all live separately inside each project. Project-level design works when a person sets up each registry by hand, but breaks down when agents are running continuously across hundreds of projects. At GitLab Transcend today, we announced GitLab Artifact Central: one organization-level registry that replaces hundreds of project-level ones, so every pull or publish by a human or an agent runs through the same governed door, enabling platform teams to assemble the right software the first time. Here is more on why we developed Artifact Central, and how it can help your team. Set policy once, enforce everywhere In GitLab, retention rules, storage limits, and who can publish all live inside each project’s free package and container registry, configured on its own. GitLab Artifact Central moves that job up one level. Teams assign retention rules, quota settings, and access policies once at the organization level, instead of recreating them in every project underneath it. Every repository is closed by default: Being a member of the organization is the gate, not the grant. Organization membership alone doesn't unlock a single repository until a role grants it. We’ve built four roles specifically for artifacts: Admin, Manager, Contributor, and Viewer. These roles are kept separate from GitLab's existing project roles, so granting someone access to a repository never touches their privileges anywhere else. One URL for publishing, proxying, or both Instead of navigating an internal wiki page explaining what is where, developers point to one URL for everything. GitLab Artifact Central does this through three repository types: Hosted — The private packages and images your teams build and publish. Remote — A proxy in front of an external source, like Docker Hub or Maven Central, with the connection tested before anything depends on it. Virtual — A single endpoint that brings hosted and remote repositories together. GitLab checks the hosted repository first, then falls back to the remote source. The first external pull is cached, so subsequent pulls come directly from GitLab without another trip to the internet. Virtual repositories matter most for teams comparing GitLab with other artifact management solutions. They give developers the familiar single-endpoint experience without requiring them to think about where an artifact lives. Whether it was built internally or pulled from an external registry, developers request it the same way. During the beta period, Artifact Central supports Maven, npm, Docker, and OCI, with more formats to follow. Trace anything back, automatically Here's the part that's hard to replicate outside GitLab. Every artifact that publishes through GitLab Artifact Central carries its build provenance automatically: which pipeline built it, which branch and commit it came from, who triggered the job. Since it is the same platform that ran the build, the registry already knows. Authentication works the same way. Publishing and pulling use CI_JOB_TOKEN, the identity your pipelines already have, for people and agents alike. An agent publishing or pulling through CI pipelines uses that exact same job token, not a bolted-on service account with separate permissions to maintain. With a standalone registry, tracing an artifact back to its source means separately correlating IDs across your CI system and your registry – using a script someone owns and maintains. With Artifact Central, the pipeline, branch, commit, and job are already attached to the artifact itself. Answer 'what did we publish?' in seconds Artifact Central lives in the same platform as your code, merge requests, and pipelines, so artifacts published from CI carry their build provenance: the pipeline that built them, the commit, and who published them. Next, we plan to connect that across your organization through GitLab Orbit, so "which of my running services are affected by this vulnerability?" becomes one question with one answer, instead of a manual search across four or five tools. Pair Artifact Central with Dependency Firewall GitLab Dependency Firewall, a separate GitLab product now in early access for Premium and Ultimate customers, works out of the box with Artifact Central. With Dependency Firewall, you can stop risky packages before they ever reach a build. You add its check to each pipeline using the glab CLI, so coverage is pipeline by pipeline, no matter which package manager your teams use. Next, we plan to enable tighter integration between the two capabilities, so that one policy for your whole organization blocks risky packages by vulnerability, license, or package age the moment they're pulled. Two benefits of the same registry Here's what that looks like from two different desks: a developer shipping code, and the platform team making sure the whole thing holds together. A developer publishing from CI. Your pipeline publishes a Maven artifact using the job token it already has without any new secrets to manage. If that same developer needs an internal package alongside something from Maven Central, they point at one virtual repo URL and let GitLab Artifact Central sort out where each one actually lives. A platform team setting policy once. Instead of configuring rules across 100s of separate projects, an admin sets storage quotas and repository access rules at the organization level, one time — and every repository underneath inherits it. When someone asks how much the company is storing, and where, there's one dashboard with the answer. Migrating your artifacts Most companies aren't starting from zero, and switching cold from an existing registry isn't realistic. With GitLab Artifact Central, you can add your existing repos as remotes behind a virtual repo, so developers point at one URL and artifacts move over only when a build actually asks for one. There is no need for bulk copies, weekend migration windows, or moving petabytes of data across your network. Your old registry remains the system of record. When you're ready, you convert that remote to a hosted repo on Artifact Central. Your migration is safer and gradual. Try Artifact Central, free in beta GitLab Artifact Central is available today in beta for GitLab.com, with availability on GitLab Self-Managed planned for later this month. There's no billing during the beta, and nothing to purchase. We're tracking usage to shape pricing ahead of general availability, and we'll share details then. Help us continue to build GitLab Artifact Central None of this would be where it is without our design partners, who've been running Artifact Central with real workflows for weeks. Their feedback already shaped what's shipping today, and your feedback will shape what comes next. No invitation is required to participate in the beta of Artifact Central, just sign up on our website and a member of our team will be in touch to help enable it for your account. If you don’t have a GitLab account yet, you can also sign up for the beta, and a member of our team will reach out. We can't wait to see what you build. Watch the replay of our Transcend event to see demos of new platform capabilities and explore what it takes to carry the speed of agentic AI across the full software lifecycle.
Attackers disguise malicious packages as ones you trust. In June 2026, GitLab researchers found five malicious PyPI packages, four of them typosquats of Flask, Requests, and NumPy, that run at install time and steal CI/CD credentials. Additionally, AI coding agents now add open source dependencies on their own, often unreviewed, so developers don't have oversight into what packages may contaminate your build. Once a malicious or vulnerable package enters your build, its code may run with the same access in your CI pipeline, and it can then reach any system your pipelines touch. GitLab Dependency Firewall, introduced today at Transcend in early access, can block packages that match your policy, including malicious, vulnerable, and non-compliant packages, before they reach your build. Built-in governance stops risk before install, so your team doesn’t have to trace, remove, or rebuild what a policy blocks. Developers and their agents can keep pulling the dependencies they need without waiting on a manual security review, and packages that satisfy your policy requirements become part of your official build. Block malicious packages without breaking your build Without a policy at the point of install, a bad package goes into the build first and gets caught later. Software composition analysis (SCA) scans what you've already pulled in, so by the time it flags a malicious package, a high-severity vulnerability, or a license your legal team won't accept, the dependency is installed and may have shipped in an artifact. Tracing where it went, pulling it out, and rebuilding turns a routine pipeline run into unplanned work for your engineering team. With Dependency Firewall, you decide what's allowed into your builds before it's installed, by defining policies for: Malicious status — packages flagged in GitLab's malware advisory database Vulnerability severity — the severity you set (critical, high, medium, or low) and the number of findings you allow at that level, including zero License type — the licenses you allow or deny, listed by full name, and how to handle packages whose license can't be determined Package age — the minimum age a package must reach before it can enter a build, so a version published minutes ago can't go straight in before anyone has vetted it Rolling out enforcement does not have to put delivery at risk. Start in warn mode, where the firewall records what a policy would catch, but lets the build continue. It leaves an audit event, a dashboard entry, and a line in the CI summary, so you can analyze whether or not to block the build. Once you trust the policies, switch to block mode, which stops the pipeline on a match and gives the reason. When someone has a real need to get an approved package through, a logged bypass lets a designated user or token proceed, on the record. Set policy once, or tailor it by team A firewall that enforces only at the registry gives everyone the same policy, but that rarely fits how teams actually work. A payments service and an internal prototype carry very different risk, and your policy should treat them differently. With Dependency Firewall, you set one policy at the top-level group and every project beneath it inherits the same rules. When a team needs something different, you can set a policy for that group or project. You can also enforce policy at the registry, so every pull is checked, not just pulls from a pipeline. Rules live as code in a security policy project, so they are reviewed and changed through a merge request like the rest of your configuration. They inherit from the top-level group down to each project, and where rules overlap the strictest one applies. A critical service can be held above the organization's baseline, and no project drops below it. Check a package before you pull it in A developer, or an agent working on their behalf, usually finds out a package is not allowed only when the pipeline fails. That costs a build cycle and breaks concentration, right when the work is moving. You get the answer from GitLab Dependency Firewall before you add a dependency, in the place you already work, allowing you to pick a package that passes the first time. Using GitLab CLI within the terminal or within a script, a command line check can identify if a package will pass or be blocked by your policy, without requiring developers to open a separate console. It covers common package managers such as npm, pip, Poetry, Maven, Gradle, and Bundler, with more coming soon. See and prove every decision A security leader has to be able to prove what a control is doing during an audit. A control that blocks quietly, with no record, does not answer the auditor’s question and does not build trust with the teams it governs. You get one view of what the firewall has allowed, warned against, and blocked, with an immutable record of each decision you can hand to an auditor. A Dependency Firewall dashboard shows activity and outcomes across the projects in scope. Every warn, block, and bypass writes an audit event that records the rule that matched, the policy behind it, and the package involved. Get early access to GitLab Dependency Firewall You can stop malicious, vulnerable, and non-compliant packages before they reach a build. It is compatible with GitLab Artifact Central and external registries from Sonatype Nexus Repository and JFrog Artifactory, and does not require standing up a separate tool next to your GitLab deployment. Dependency Firewall is now in early access for GitLab.com and GitLab Self-Managed customers in the Premium or Ultimate tier. Request early access today!
At Transcend, we made over a dozen announcements across all four layers of our architecture for agentic software engineering: agent orchestration, data and context, DevOps workflows, and governance and security. Watch the replay, or read on for what shipped and how to turn on the new capabilities. At a glance What we launchedRelease statusWhat it does Goal-driven flows (/goal)GA this monthCarry a change through review, tests, scans, and approvals without waiting between stages of the software lifecycle. Custom FlowsGAChain agents together to match the process your teams already follow for software delivery. GitLab for SlackGA this monthStart an agentic flow from the channels where your teams already work. MCP ServerGA this monthSecurely connect AI tools and applications into GitLab workflows under the same policy. Open weight modelsGAGet comparable performance on lower-cost workloads with GitLab-hosted GLM 5.3, Kimi K3, and MiniMax 3 models. GitLab OrbitGA next monthGive your agents the right knowledge requiring 45x fewer retries with a context graph of your software lifecycle. Duo Agent Platform Impact AnalyticsEarly accessMeasure the cost and impact of your AI investment, by team, task, and model. Credit and usage controlsGASet caps at the subscription, group, and user level and get alerts on AI spend. GitLab Artifact CentralBetaGive every package and container one governed home, next to source and CI. GitLab Dependency FirewallEarly accessSet rules that block, quarantine, or warn on risky packages before they reach your build. GitLab Secrets ManagerGA this monthScope build-time secrets to the job and revoke them with one click. GitLab Security StandardAvailable todayHarden your software factory in five stages and let your agents earn autonomy. New flows with Claude Mythos 5 and 5.1GA next monthFind and remediate vulnerabilities on GitLab Duo Agent Platform with new security flows. Agent orchestration across the software lifecycle Today, each step in your agentic workflow still waits for a person to approve it before the next one starts. Goal-driven flows take a stated objective and run it end to end, through review, tests, security scans, and approvals from the Duo CLI, headless mode, or Agentic Chat. Custom Flows let you chain agents together to match the process your team already follows. GitLab for Slack starts a flow from the channel where the conversation is already happening. The MCP Server enables external AI applications and coding agents to securely access your GitLab instance under the same policy your own agents follow. GitLab-hosted open-weight models, including GLM 5.3, Kimi K3, and MiniMax 3, give you a lower-cost option when a workload doesn't need a frontier model. At similar task-completion rates, some open weight pairings deliver up to 8x more model calls per GitLab Credit than their frontier counterparts. Data and context to power human and agent reasoning Every agent task starts by re-deriving the same context, which drives up retries and token use. And without coherent visibility into AI costs and ROI, there's no way to tell whether your investment is paying off. GitLab Orbit, the context graph of your entire software lifecycle increases agent accuracy with up to 45x fewer retries, effectively reducing cost for agentic workflows with up to 4.5x fewer token use. During its beta period, Orbit has been used by more than 3,500 organizations, running over 280,000 queries. Duo Agent Platform Impact Analytics shows the cost and impact of your AI investment by team, task, and model. Credit and usage controls let you set caps at the subscription, group, or user level, with alerts at 50%, 80%, and 100% of spend, and an automatic pause once you hit the cap you set. DevOps infrastructure at agent scale Most of what ships isn't code your team wrote, it's assembled from open source packages, base images, and libraries pulled in from everywhere. When every team runs its own registry, there's no single place to confirm what you actually published or shipped. Back in June, during Transcend London, we introduced our next-gen source code management solution helping you achieve machine scale with your coding agents. The next machine-scale problem goes to the step after code, when you’re creating a build. GitLab Artifact Central replaces a separate registry per team with one place to publish and pull from, built next to your source code and CI pipelines. It publishes and pulls Maven, npm, and Docker, and OCI packages directly from CI pipelines, with PyPI and NuGet coming at GA. Artifact Central uses the same identity and permissions as your source code, with virtual repos, native CI/CD authentication, and full build provenance. Early results show roughly 50% lower total cost of ownership compared to alternative tooling. Governance and security with centralized enforcement Agents pull in package components to your build at machine speed, making it impossible to manually secure what you ship. When that gap exists, you risk shipping security vulnerabilities into production rather than catching them before they impact customers, and you have to answer for it. GitLab Dependency Firewall, now in early access, sets rules on package age, vulnerability severity, malicious package detection, and license compliance, with actions to block, quarantine, or warn, enforced on the registries you already use. It works directly with GitLab Artifact Central, and is compatible with JFrog Artifactory and Sonatype Nexus Repository. With a greater number of builds, another risk emerges: agents inheriting build-time secrets from local dev environments that nobody secured, and using them across CI pipelines. GitLab Secrets Manager gives each build-time secret one home, scoped to the job that needs it, with one-click revocation for a leaked credential and up to 50% savings compared to hosting a separate vault. The same AI models that let agents write and ship code at machine speed also make existing weaknesses faster and cheaper to discover, connect, and exploit. The GitLab Security Standard lays out five stages for assessing and hardening your agentic software development: authorizing every actor's access, isolating workspaces and their inputs, verifying the checks that judge the work, releasing exactly what was verified, and responding fast when something looks wrong, all built on a foundation of policy, audit, and ownership. Read the full standard for the complete breakdown. Coming soon, Anthropic’s Claude Mythos 5 and 5.1 will power new GitLab Duo Agent Platform security flows, helping organizations with approved environments find and fix vulnerabilities faster than attackers can discover and exploit them. How to buy with GitLab Flex Agentic software engineering makes headcount, credit burn, and new capabilities hard to predict six months out. GitLab Flex is one annual commitment that covers new GitLab capabilities as they ship, without re-procurement. It lets teams reshape seat and AI spend via GitLab Credits on a monthly basis as their needs change. Where to start Turn on GitLab Duo Agent Platform: Existing customers start today with credits already in their subscription, and every new GitLab trial includes 30-day access. To increase the efficiency of your agents, turn on GitLab Orbit beta for GitLab.com. Adopt the GitLab Security Standard: GitLab Ultimate is available as a free trial. A Secrets Manager trial is available to Ultimate and Premium customers. GitLab Artifact Central is open in beta, and you can request early access to Dependency Firewall. Get more from every dollar with GitLab Flex: One annual commitment for new GitLab innovations without re-procurement - with the ability to reshape your spend for seats and GitLab Credits month to month. If you're migrating from GitHub, do it on your own terms with dedicated migration tools, custom migration services, and an exclusive offer to get one year of GitLab free when signing up for a three-year contract. And if you're ready to start building, join "Life after code: the path to production at the speed of imagination," our three-week hackathon in partnership with Anthropic and Google Cloud. Wherever you start, you're choosing the same destination: the foundation for a governed software factory where agents accelerate the work and every change stays trusted. We can’t wait to see what you build next.
The token debuts at $0.10 on Uniswap. It is backed by $1 million in locked liquidity. A scheduled 50% burn will reduce its supply to 25 million. The token debuts at $0.10 on Uniswap. It is backed by $1 million in locked liquidity. A scheduled 50% burn will reduce its supply to 25 million.
Murphy Law Firm investigates claims on behalf of everyone whose information was exposed in the Aldrich data breach.
Plano, Texas Monday Oct 5, 2026 @ 8:30 AM Eastern — Verge Technologies Inc. today announced featured speakers for the Cloud Convergence Summit, a free virtual event on October 8 and 9, 2026, from noon to 5 PM Central each day. The summit targets CIOs, cloud architects, and tech founders managing three or more cloud providers, aiming to unify them into one estate, minimizing downtime and operational friction. Cloud convergence is the idea that an enterprise should run on every cloud it needs and still feel like it runs on one. Many large enterprises unintentionally adopted multi-cloud environments. They arrived there by accident, and the result is separate consoles, separate policies and databases that are hard to move or protect. Speakers tackle cloud convergence challenges from their industry's front lines. Featured speakers and their connection to cloud convergence Malur Narayan, CEO & Co-Founder, XTRIUM. Leveraging Cloud Infrastructure for Critical Materials Decisions: AI to Mitigate Supply Disruptions. Supply chain decisions depend on data spread across systems and clouds. Narayan shows how a unified cloud foundation turns that data into earlier warnings. Jimmy Jobe, CEO & Co-Founder, Verge Technologies. Opening Keynote: The Cloud Convergence Model (Thursday, October 8, 12:00 PM CT). The model for managing every database and every cloud as one virtual data center. Matt LeBaron, Founder & CEO, Pocketbook. Fireside chat: Cloud Sprawl Is a Procurement Problem: What to Fix Before Your Next Renewal. The cost side of convergence: what scattered cloud contracts and tools really cost, and what to fix before renewal. Jacqueline Suttin, CEO & Founder, MagenTrust. Human in the Loop: Closing the Zero Trust Gap in Agentic AI for Government. The security side of convergence: how human verification stays in the loop as database operations become autonomous. MagenTrust and Verge announced an integration on July 15, 2026. Prasad Jaladi, Founder & Chief Facilitator, Suraksha. The Dual Mandate for Enterprise Architecture. The architecture side of convergence: designing one coherent enterprise estate across many platforms. Click here for all Speakers Additional speakers are being confirmed and will be announced to registrants first. What attendees will learn From swivel-chair management to one pane: how enterprises running four to seven cloud providers are replacing separate consoles with a single management plane. Downtime as a design choice: how operators are working to take planned outages off the table and cut disaster recovery time for the database layer. Multi-cloud by design, not by accident: building a cloud estate that is intentionally resilient and cost-aware. Explore autonomous management in the AI era: Self-healing, predictive infrastructure readies enterprises for expanding AI workloads. Attendees can also request a sandbox of Verge's SentientDB on their own stack after the event. Event details Dates: Thursday, October 8 and Friday, October 9, 2026 Time: 12:00 PM to 5:00 PM Central, both days Format: Virtual, live with Q&A in every session Cost: Free. Recordings to all registrants within 48 hours. Register: https://summit.vergetech.cloud/ (also https://luma.com/9zydgx4h) Sponsorship opportunities: Email Contact About Verge Technologies Verge Technologies Inc. builds SentientDB, an AI-driven platform that lets enterprises manage databases across cloud providers, regions and environments as if they were in one virtual data center. Learn more at https://www.vergetech.cloud. Media and speaker inquiries Email Contact Email Contact
New collaboration combines Zscaler Autonomous Application Shield with Lightwell from IBM and Red Hat to help organizations reduce exposure between vulnerability disclosure and patch deployment through inline protection and validated remediation New collaboration combines Zscaler Autonomous Application Shield with Lightwell from IBM and Red Hat to help organizations reduce exposure between vulnerability disclosure and patch deployment through inline protection and validated remediation
Edelson Lechtzin LLP, a national class action law firm, is investigating data privacy claims arising from the Man Group data breach.
National class action law firm offers free, confidential case evaluations to individuals whose personal, financial, and health information may have been exposed in the Millstone Medical Outsourcing data breach. NEWTOWN, Pa., Oct. 2, 2026 -- Edelson Lechtzin LLP, a national...
National class action law firm offers free, confidential case evaluations to investors and others whose personal and financial information may have been exposed in the CAZ Investments LP data breach. NEWTOWN, Pa., Oct. 2, 2026 -- Edelson Lechtzin LLP, a national class action...
National class action law firm offers free, confidential case evaluations to household employers and household employees whose personal information may have been exposed in the Poppins Payroll data breach. NEWTOWN, Pa., Oct. 2, 2026 -- Edelson Lechtzin LLP, a national class...