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Cybersécurité

Cisco Patches Nine Crosswork and Secure Workload Flaws, Five Scoring CVSS 10.0

Cisco has published another round of security updates for Crosswork platforms and Secure Workload Software as part of a continued comprehensive internal security review. Four of the security vulnerabilities affect Crosswork Data Gateway, Crosswork Network Controller, and Crosswork Planning, regardless of the device configuration. A brief description of each of the flaws is…

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Cybersécurité

GitLab CVE-2026-19478 Comes Under Active Exploitation Within Days of Disclosure

A newly disclosed security flaw in GitLab has come under active exploitation within days of public disclosure, according to watchTowr. The vulnerability in question is CVE-2026-19478 (CVSS score: 9.4), a case of code injection that allows an unauthenticated attacker to modify or delete publicly accessible GitLab projects and rewrite their data under certain conditions without…

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Cybersécurité

Microsoft Entra ID Flaw (CVSS 10.0) Exploited in Wild, Allows Remote Code Execution

Microsoft on Thursday warned of a maximum-severity security flaw in Entra ID that it said has been exploited in the wild, but noted that no customer action is required. The vulnerability, tracked as CVE-2026-69836 (CVSS score: 10.0), is a case of remote code execution impacting the tech giant's cloud-based identity and access management service. It was previously called Azure…

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Intelligence Artificielle

Represented but Ignored: A Causal Account of Prosodic Underuse in Audio-Language Models

arXiv:2608.19211v1 Announce Type: new Abstract: Human speech is richly expressive, with prosody carrying linguistic and emotional information beyond the lexical content. A capable large audio-language model (audio-LLM) should therefore support expressive speech understanding, not only transcribing what was said but also interpreting how it was said. Yet behavioral evaluations…

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Intelligence Artificielle

When Irrelevant Text Matters: Affine Margin Shifts in Multimodal Large Language Models

arXiv:2608.19208v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are frequently exposed to auxiliary textual context, the impact of which on visually grounded tasks remains underexplored. In this paper, we investigate the influence of task-irrelevant context by formulating it as a controlled intervention within a binary visual judgment framework. By…

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Intelligence Artificielle

Compliance, Capability, and Conflict: Benchmarking Multimodal LLMs under System Messages

arXiv:2608.19207v1 Announce Type: new Abstract: Production deployments of Multimodal Large Language Models (MLLMs) increasingly rely on system messages to govern model behavior. Yet existing benchmarks either evaluate constraints in text only or embed them into the user turn, leaving system-message adherence in multimodal contexts largely unmeasured; they also leave open…

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