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Hi there, this is your daily ☕️ Cyberpresso.
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In today's Cyberpresso:
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🏥 Polish health software breach hits 19M 🔓 WordPress plugin flaw exposes 600K sites 🛡️ CISA: Patch exploited AI flaw now 🖥️ Exploit code hits Microsoft SCCM flaw 🔒 GitLab patches critical flaw that let attackers delete public projects Plus: 💡 4 strategies & tactics, 🎁 5 other news you might like, 🧰 6 tools, and 📚 5 papers.
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🏥 Polish health software breach hits 19M
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- Polish authorities are investigating a cyberattack on healthcare software provider MyDr that may have exposed data belonging to nearly 19 million people and more than 12,000 medical facilities across the country.
- MyDr said it identified and removed the cause of the incident but disclosed no details about the vulnerability or how attackers broke in; officials say hackers obtained unauthorized access to historical data held in MyDr systems through April 2024.
- MyDr's software connects providers to P1, Poland's nationwide health platform for electronic prescriptions and referrals; as a precaution the e-Health Center is replacing digital certificates, though authorities found no evidence the certificates were stolen or misused.
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🔓 WordPress plugin flaw exposes 600K sites
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A flaw in WordPress's Forminator form plugin lets attackers upload malicious files and hijack sites, so update to version 1.56.2 immediately.
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🛡️ CISA: Patch exploited AI flaw now
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- CISA is ordering federal agencies to patch an actively exploited code-injection flaw in Ray, the open-source AI framework maintained by Anyscale that distributes machine-learning workloads across clusters, or stop running the software by August 20.
- The bug, CVE-2025-62593, lets an attacker who has never logged in make a vulnerable Ray deployment run commands of their choosing, and unusually it can be reached through an ordinary web browser like Firefox or Safari rather than direct network access.
- Anyscale has fixed the issue in Ray version 2.52.0, leaving operators on earlier releases exposed; CISA lists any ransomware use as "unknown," so the immediate risk is unauthorised code execution on clusters holding proprietary models, training data, and cloud credentials.
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🖥️ Exploit code hits Microsoft SCCM flaw
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- Working proof-of-concept exploit code is now public for a critical remote code execution flaw (CVE-2026-47301) in Microsoft Configuration Manager (SCCM), letting a low-privileged domain user gain SYSTEM-level control of a Primary Site Server.
- The exploit chain, published by researcher Omri Baso, uses a malicious CAB file with path-traversal sequences to write attacker DLLs into the Configuration Manager bin\X64 directory, which the elevated SMS_EXECUTIVE service then loads via DLL proxying.
- Attackers must first identify the Primary Site Server, inferable from Full Control or GenericAll permissions on the System Management container; defenders should apply Microsoft's update and watch for changes to the RID 500 Administrator account and suspicious DLLs.
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🔒 GitLab patches critical flaw that let attackers delete public projects
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- GitLab has patched a critical flaw in its GraphQL interface, tracked as CVE-2026-19478, that lets unauthenticated attackers remotely modify or delete public projects and user data on Community Edition and Enterprise Edition installations.
- Rated critical (CVSS 9.4), the code injection bug abuses a GraphQL directive so that, under specific conditions, a remote attacker with no account or user interaction can perform unauthorized actions against public GitLab resources over the network.
- Fixed versions 19.2.4, 19.1.6, 19.0.8, and 18.11.11 shipped August 17, 2026; GitLab.com and Dedicated are already patched, and admins should upgrade self-managed instances and review audit logs for deleted projects or suspicious GraphQL activity.
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Other
news & articles you might like
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Geekom admits to shipping malware-laced network drivers for AMD mini PCs — company responds with guidance, removes malicious package
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Octagon android Bot uses hidden VNC and accessibility overlays to steal crypto wallet credentials
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C2Looper v2 uses GitHub repositories as full Command-and-Control infrastructure.
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Operation ASTERIX: Anatomy of a crypto fraud pipeline
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VMware syslog path traversal Becomes root RCE, persistent SSH access and ESXi ransomware
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🛠️ Trending tools
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Kastra: a runtime authorization layer that enforces policies on AI agents before actions execute, blocking unauthorized tool use and data exposure across major frameworks.
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Perfai Security: an automated tool that scans AI-generated apps from Replit, Lovable, Cursor, and Claude Code for access control vulnerabilities, fixing them with a single prompt.
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Constellation Gate AI: routes AI agent traffic through a gateway that blocks prompt injections, scans for secrets, logs audit trails, and cuts token costs 20-40% via compression and caching.
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TailMux: lets you connect to multiple Tailscale tailnets simultaneously on macOS and Linux by running isolated embedded nodes per profile, routing by hostname without switching accounts or VMs.
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Lunen.ai: an AI automation tool that logs every action taken and requires approval on risky steps, giving teams usability without sacrificing oversight.
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qsa.sh: scans your server's public IP with naabu, nmap, and nuclei to reveal open ports, service versions, and known CVEs in about 30 seconds, no signup required.
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📚 Trending research papers
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AI agent "skills" can be secretly tweaked so their normal network traffic patterns leak private user information to an eavesdropper, even though the tweaks pass existing AI security audits.
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Retrieval poisoning defense retrains only a tiny sliver of a search system's encoder, under 1% extra parameters, so poisoned lookalike content gets filtered out before it ever reaches the chatbot's answer, with no added per-query slowdown.
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DeepSeek's AI assistant can be tricked by hidden instructions buried in files or text, with attacks succeeding up to ~26% of the time, showing untrusted content needs stronger checks before it reaches sensitive actions.
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AI-built network attack simulations matched traditional training methods with a 94.5% success rate at finding security holes, while running about 25,000 to 50,000 times faster.
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Next-gen network security flags malicious traffic in live 6G-style test networks while cutting the data needed to spot attacks by 80%, and pinpoints exactly which traffic traits give hackers away.
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