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A vulnerability was found in Linux Kernel up to 6.12.17/6.13.5. It has been rated as critical. This issue affects some unknown processing of the component bnxt_re. The manipulation leads to null pointer dereference. The identification of this vulnerability is CVE-2025-21901. The attack can only be initiated within the local network. There is no exploit available. It is recommended to upgrade the affected component.

A vulnerability was found in Linux Kernel up to 6.12.17/6.13.5. It has been declared as critical. This vulnerability affects the function close of the component NFSv4. The manipulation leads to deadlock. This vulnerability was named CVE-2025-21900. The attack can only be done within the local network. There is no exploit available. It is recommended to upgrade the affected component.

A vulnerability was found in Linux Kernel up to 6.1.129/6.6.80/6.12.17/6.13.5. It has been classified as problematic. This affects the function event_trigger_write of the component tracing. The manipulation leads to incorrect regular expression. This vulnerability is uniquely identified as CVE-2025-21899. The attack needs to be approached within the local network. There is no exploit available. It is recommended to upgrade the affected component.

A vulnerability was found in Linux Kernel up to 6.13.5 and classified as critical. Affected by this issue is the function function_stat_show of the component ftrace. The manipulation leads to divide by zero. This vulnerability is handled as CVE-2025-21898. Access to the local network is required for this attack to succeed. There is no exploit available. It is recommended to upgrade the affected component.

A vulnerability has been found in Linux Kernel up to 6.12.17/6.13.5 and classified as critical. Affected by this vulnerability is the function pick_task_scx of the component sched_ext. The manipulation leads to deadlock. This vulnerability is known as CVE-2025-21897. Access to the local network is required for this attack. There is no exploit available. It is recommended to upgrade the affected component.

A vulnerability, which was classified as critical, was found in Linux Kernel up to 6.6.80/6.12.17/6.13.5. Affected is the function perf_event_swap_task_ctx_data. The manipulation leads to excessive iteration. This vulnerability is traded as CVE-2025-21895. The attack needs to be initiated within the local network. There is no exploit available. It is recommended to upgrade the affected component.

A vulnerability, which was classified as problematic, has been found in Linux Kernel up to 6.12.18/6.13.6. This issue affects the function vma_modify of the component mm. The manipulation leads to allocation of resources. The identification of this vulnerability is CVE-2025-21932. The attack needs to be done within the local network. There is no exploit available. It is recommended to upgrade the affected component.

A vulnerability classified as problematic was found in Linux Kernel up to 6.12.18/6.13.6. This vulnerability affects unknown code in the library /include/linux/swapops.h of the component memory_hotplug. The manipulation leads to state issue. This vulnerability was named CVE-2025-21931. The attack can only be initiated within the local network. There is no exploit available. It is recommended to upgrade the affected component.

Layer 7 DDoS attacks are stealthy, potent, and often more dangerous than massive traffic floods. Learn why these “baby rattlesnakes” are so hard to stop.

The post The Baby Rattlesnake of Cyberattacks: Why Layer 7 DDoS Can Be More Dangerous Than Larger Threats appeared first on Security Boulevard.

模板补全（Template Completion）定义模板补全是一种针对大语言模型的黑盒越狱攻击方法。攻击者通过预定义一个看似无害的“模板框架”，将恶意问题嵌入其中，利用大模型对上下文模板的“逻辑补全”惯性，诱导模型生成违规内容。核心原理上下文误导：大模型（如ChatGPT）具有强大的上下文学习（In-context Learning）能力，会优先遵循输入文本的模板结构和隐含逻辑。攻击者通过设计特

Банки ищут способ отследить недобросовестных клиентов.

Новый метод объединяет отжиг Фаулера–Нордгейма с импульсной динамикой для задач Изинга

Autorité de la concurrence, France's antitrust watchdog, has fined Apple €150 million ($162 million) for using the App Tracking Transparency privacy framework to abuse its dominant market position in mobile app advertising on its devices. [...]

Возможно, это самое важное открытие для будущих покорителей Красной планеты.

Dark Storm Team Targeted the Website of FBI

为了在竞争激烈的 AI 领域保持竞争优势，Google DeepMind 采取了推迟发表 AI 论文的策略。诺奖得主 Sir Demis Hassabis 领导的团队引入了更严格的审查程序和更多的官僚主义，增加了 AI 论文的发表难度。该团队最不愿意发表的是可能会被竞争对手利用的论文，或者凸显 Google Gemini AI 模型相比其它模型处于劣势的文章。Google 研究人员在 2017 年发表了 Transformers 论文，奠定了今天流行的大模型的基础，但它也将最初的领先优势让给了 OpenAI 等竞争对手。为了防止再次发生类似的事件，DeepMind 对具有战略意义的论文实施六个月的出版禁令。一位前研究员表示，如果不能发表论文，对研究员而言这是职业生涯的“杀手”。