Machine Learning-Based Cyber Defense for Cloud Infrastructure: An Adaptive Deep Q-Network Architecture for Intelligent Intrusion Detection and Automated Threat Mitigation

With the increasing complexity of cyber assaults in cloud environments, adaptable security solutions are needed that can support real-time detection and autonomous response. In this paper, we propose a reinforcement learning-based dynamic cyber defense framework. We deploy a Deep Q-Network DQN to...

cyberange

网络安全渗透测试学习与训练靶场，包含Web漏洞靶场、渗透工具脚本、攻防手册等。内含：邻里圈靶场16+隐藏漏洞，含SQL注入/XSS/命令注入/文件上传/路径遍历等、零依赖渗透脚本、全工具链渗透脚本、PHP/CGI木马、反向Shell、密码破解工具、蜜罐防御系统、Metasploit精简版、Hacker OS一键构建脚本，以及DVWA攻防手册、Kali工具手册、recon-ng手册等学习文档。适合网络安全入门学习和CTF备赛参考。...

CVE-2026-39452

Protection mechanism failure for some IntelR Transfer Learning Tool before version v0.7 within Ring 3: User Applications may allow an escalation of privilege. Unprivileged software adversary with an unauthenticated user combined with a low complexity attack may enable escalation of privilege. Thi...

CVE-2026-39452

Protection mechanism failure for some IntelR Transfer Learning Tool before version v0.7 within Ring 3: User Applications may allow an escalation of privilege. Unprivileged software adversary with an unauthenticated user combined with a low complexity attack may enable escalation of privilege. Thi...

EUVD-2026-56533

Protection mechanism failure for some IntelR Transfer Learning Tool before version v0.7 within Ring 3: User Applications may allow an escalation of privilege. Unprivileged software adversary with an unauthenticated user combined with a low complexity attack may enable escalation of privilege. Thi...

CVE-2026-39452

Protection mechanism failure for some IntelR Transfer Learning Tool before version v0.7 within Ring 3: User Applications may allow an escalation of privilege. Unprivileged software adversary with an unauthenticated user combined with a low complexity attack may enable escalation of privilege. Thi...

CVE-2026-39452

CVE-2026-39452 is a protection mechanism failure in Intel® Transfer Learning Tool (all versions before v0.7) within Ring 3: User Applications that may allow escalation of privilege by an unauthenticated, unprivileged remote attacker via a low-complexity network attack. However, the CVSS 4.0 vecto...

CVE-2026-39452

Protection mechanism failure for some IntelR Transfer Learning Tool before version v0.7 within Ring 3: User Applications may allow an escalation of privilege. Unprivileged software adversary with an unauthenticated user combined with a low complexity attack may enable escalation of privilege. Thi...

CVE-2026-39452

Protection mechanism failure for some IntelR Transfer Learning Tool before version v0.7 within Ring 3: User Applications may allow an escalation of privilege. Unprivileged software adversary with an unauthenticated user combined with a low complexity attack may enable escalation of privilege. Thi...

CVE-2026-39452: Protection Mechanism Failure

Protection mechanism failure for some IntelR Transfer Learning Tool before version v0.7 within Ring 3: User Applications may allow an escalation of privilege. Unprivileged software adversary with an unauthenticated user combined with a low complexity attack may enable escalation of privilege. Thi...

ntel® Transfer Learning Tool Software Advisory

Summary: A potential security vulnerability for some Intel® Transfer Learning Tool software may allow escalation of privilege. Intel is not releasing updates to mitigate this potential vulnerability and has issued a Product Discontinuation Notice for the Intel® Transfer Learning Tool software...

Hardware Aware Automated Machine Learning Software Advisory

Summary: A potential security vulnerability for some Hardware Aware Automated Machine Learning software may allow escalation of privilege. Intel is releasing software updates to mitigate this potential vulnerability. Vulnerability Details: CVEID: CVE-2026-34175 Description: Uncontrolled search pa...

Dueling Deep Q-Learning for Intrusion Detection

Intrusion detection systems IDS and automated systems for detecting and reporting cyber threats, are commonly handled via supervised machine learning methods. Though effective, these models struggle to effectively adapt to new attack types. This study proposes a novel approach by employing a...

Cross-Corpus Evaluation of Generalizable Vulnerability Detection in IoT Firmware

IoT firmware vulnerability detection remains challenging due to heterogeneous firmware ecosystems, resource-constrained platforms, and limitations in existing benchmarks. Many datasets are synthetic or general-purpose and lack human-verified, contamination-screened annotations, limiting evidence ...

PT-2026-70343

Name of the Vulnerable Software and Affected Versions IntelR Transfer Learning Tool versions prior to v0.7 Description A protection mechanism failure within Ring 3 the least privileged level of the CPU architecture where user applications run may allow an unauthenticated, unprivileged software...

fastnn (0.4.0), few-shot-learning-nlp (>=0.0.5, <=1.0.4) +9 more potentially affected by CVE-2026-69112 via accelerate (0.24.1)

accelerate PYPI version 0.24.1 is affected by a known vulnerability. The following packages have a transitive dependency on accelerate and may be impacted: - fastnn 0.4.0 - few-shot-learning-nlp =0.0.5, =0.0.1a5, =3.4.0, =0.1.8, =0.2.25, =0.1.0, =0.1.2, =0.7.0, =0.10.0 Source cves: CVE-2026-69112...

Python Now Has a Post-Quantum Encryption Library

This is good: Post-quantum cryptography is now one pip-install away for the entire Python ecosystem. With funding from the Sovereign Tech Agency, we implemented support for ML-KEM, the NIST-standard key-establishment primitive, and ML-DSA, the NIST-standard digital-signature primitive, in...

Intelligent Wiretap Code Design: Exploiting Wireless Endogenous Security Via Information Theory and Deep Learning Integration

Recent advancements in wireless endogenous security have explored leveraging the inherent randomness of wireless channels to enhance communication security, providing an effective alternative to traditional encryption methods. This paper proposes a wiretap coding scheme within the semantic...

Diversity Matters: Distributional Feature Coverage Sample Selection for Data-Efficient Backdoor Attacks

Backdoor attacks compromise training data so that a model retains clean accuracy but predicts an attacker-chosen target on triggered inputs. At very low poisoning rates, only a few samples convey the trigger--target association, making poison-sample selection critical. Existing methods typically...

CVE-2026-12261

A flaw was found in the nltk.downloader component of NLTK. This vulnerability allows for cross-package resource and model poisoning. The downloader extracts package archives into shared namespaces and only validates package integrity after extraction. This design flaw enables one package to...