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Cybersécurité

E4del and PINHOLE RATs Turn FTP Banners Into Dead Drops for Malware Commands

Cybersecurity researchers are calling attention to a new campaign that employs FTP banners as dead drop resolvers (DDRs) to deliver two previously unreported remote access trojans (RATs) tracked as E4del and PINHOLE. While threat actors are known to abuse legitimate services to point to additional command-and-control (C2) infrastructure and blend in with regular network…

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Cybersécurité

Frontier AI: Vulnerability Management's Systemic Revolution

Vulnerability management has been a staple of security programs since the dawn of the cybersecurity discipline. The symbiotic relationship between vulnerability and patch management teams has also existed for that time and has gone through waves of contention and thankfulness. While this relationship required thoughtful care and feeding from both sides, both sides were aiming…

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Cybersécurité

Police arrests dozens of suspects in global cybercrime crackdown

Law enforcement agencies from 22 countries helped identify 263 suspects and arrested 58 individuals linked to cybercrime networks coordinated by African crime groups. [...]

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Cybersécurité

Attackers Target miniOrange SAML Flaws That Can Grant WordPress Admin Access

Bad actors are attempting to exploit two severe unauthenticated authentication bypasses in the Xecurify miniOrange SAML 2.0 Single Sign On plugin that make it possible for an attacker to sign in as any WordPress user, including administrators. The vulnerabilities, as disclosed by Patchstack, are listed below - CVE-2026-61979 (CVSS score: 8.1) - An unauthenticated…

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Cybersécurité

Actively Exploited Oracle WebLogic Flaw Lets Unauthenticated Attackers Access Critical Data

The U.S. Cybersecurity and Infrastructure Security Agency (CISA) on Monday added a maximum-severity security flaw impacting Oracle HTTP Server and Oracle WebLogic Server to its Known Exploited Vulnerabilities (KEV) catalog, citing evidence of active exploitation. The vulnerability, tracked as CVE-2026-21962 (CVSS score: 10.0), allows an unauthenticated attacker with network…

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Intelligence Artificielle

Mitigating Bias in Large Vision-Language Models via Counterfactual Ensemble Decoding

arXiv:2608.21415v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) have achieved remarkable performance across a wide range of tasks; however, they often inherit social biases from their training data, resulting in biased behavior when processing portraits from different social groups. Existing debiasing approaches typically compare token probabilities…

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