35635 matches found
Exploit for Reliance on Untrusted Inputs in a Security Decision in Microsoft
🏛️CTT -Microsoft Office OLE Manifold BYPASS CVE-2026-21509 Stan...
Linux Kernel Security Vulnerabilities
The Linux kernel is the kernel used by the Linux operating system developed by the Linux Foundation in the United States. There is a security vulnerability in the Linux kernel, which stems from the failure to release references to ICU devices during detection processes. This vulnerability may lea...
Linux Kernel Security Vulnerabilities
The Linux kernel is the core of the open-source operating system Linux, developed by the Linux Foundation in the United States. There is a security vulnerability in the Linux kernel, which stems from the lack of proper conflict detection when recording inode references. This vulnerability may lea...
Okara: Detection and Attribution of TLS Man-In-The-Middle Vulnerabilities in Android Apps with Foundation Models
Transport Layer Security TLS is fundamental to secure online communication, yet vulnerabilities in certificate validation that enable Man-in-the-Middle MitM attacks remain a pervasive threat in Android apps. Existing detection tools are hampered by low-coverage UI interaction, costly...
RPP: A Certified Poisoned-Sample Detection Framework for Backdoor Attacks under Dataset Imbalance
Deep neural networks are highly susceptible to backdoor attacks, yet most defense methods to date rely on balanced data, overlooking the pervasive class imbalance in real-world scenarios that can amplify backdoor threats. This paper presents the first in-depth investigation of how the dataset...
Optimal Transport-Guided Adversarial Attacks on Graph Neural Network-Based Bot Detection
The rise of bot accounts on social media poses significant risks to public discourse. To address this threat, modern bot detectors increasingly rely on Graph Neural Networks GNNs. However, the effectiveness of these GNN-based detectors in real-world settings remains poorly understood. In practice...
Secure Integrated Sensing and Communication against Communication and Sensing Eavesdropping
Sensing privacy and communication confidentiality play fundamentally different but interconnected roles in adversarial wireless environments. Capturing this interplay within a single physical-layer framework is particularly challenging in integrated sensing and communication ISAC systems, where t...
The Semantic Trap: Do Fine-Tuned LLMs Learn Vulnerability Root Cause or Just Functional Pattern?
LLMs demonstrate promising performance in software vulnerability detection after fine-tuning. However, it remains unclear whether these gains reflect a genuine understanding of vulnerability root causes or merely an exploitation of functional patterns. In this paper, we identify a critical failur...
Semantic-Aware Advanced Persistent Threat Detection Using Autoencoders on LLM-Encoded System Logs
Advanced Persistent Threats APTs are among the most challenging cyberattacks to detect. They are carried out by highly skilled attackers who carefully study their targets and operate in a stealthy, long-term manner. Because APTs exhibit "low-and-slow" behavior, traditional statistical methods and...
PIDSMaker: Building and Evaluating Provenance-Based Intrusion Detection Systems
Recent provenance-based intrusion detection systems PIDSs have demonstrated strong potential for detecting advanced persistent threats APTs by applying machine learning to system provenance graphs. However, evaluating and comparing PIDSs remains difficult: prior work uses inconsistent preprocessi...
Turning threat reports into detection insights with AI
Security teams routinely need to transform unstructured threat knowledge, such as incident narratives, red team breach-path writeups, threat actor profiles, and public reports into concrete defensive action. The early stages of that work are often the slowest. These include extracting tactics,...
Turning threat reports into detection insights with AI
Security teams routinely need to transform unstructured threat knowledge, such as incident narratives, red team breach-path writeups, threat actor profiles, and public reports into concrete defensive action. The early stages of that work are often the slowest. These include extracting tactics,...
Survey of 100+ Energy Systems Reveals Critical OT Cybersecurity Gaps
A study by OMICRON has revealed widespread cybersecurity gaps in the operational technology OT networks of substations, power plants, and control centers worldwide. Drawing on data from more than 100 installations, the analysis highlights recurring technical, organizational, and functional issues...
3 Decisions CISOs Need to Make to Prevent Downtime Risk in 2026
Beyond the direct impact of cyberattacks, enterprises suffer from a secondary but potentially even more costly risk: operational downtime, any amount of which translates into very real damage. That's why for CISOs, it's key to prioritize decisions that reduce dwell time and protect their company...
KiloView Encoder Series (Update A)
RISK EVALUATION Successful exploitation of this vulnerability could allow an unauthenticated attacker to create or delete administrator accounts, granting full administrative control. 2. RECOMMENDED PRACTICES CISA recommends users take defensive measures to minimize the risk of exploitation of...
ReasoningBomb: A Stealthy Denial-Of-Service Attack by Inducing Pathologically Long Reasoning in Large Reasoning Models
Large reasoning models LRMs extend large language models with explicit multi-step reasoning traces, but this capability introduces a new class of prompt-induced inference-time denial-of-service PI-DoS attacks that exploit the high computational cost of reasoning. We first formalize inference cost...
The vulnerability of the DCERPC protocol implementation in the Suricata intrusion detection and prevention system allows a perpetrator to cause a service failure.
The vulnerability of the DCERPC protocol implementation in the Suricata intrusion detection and prevention system is related to the unlimited distribution of resources. Exploiting this vulnerability could allow a malicious actor to cause service interruptions...
QCL-IDS: Quantum Continual Learning for Intrusion Detection with Fidelity-Anchored Stability and Generative Replay
Continual intrusion detection must absorb newly emerging attack stages while retaining legacy detection capability under strict operational constraints, including bounded compute and qubit budgets and privacy rules that preclude long-term storage of raw telemetry. We propose QCL-IDS, a...