813 matches found
CVE-2026-20849
Reliance on untrusted inputs in a security decision in Windows Kerberos allows an authorized attacker to elevate privileges over a network...
Windows Kerberos Elevation of Privilege Vulnerability
Reliance on untrusted inputs in a security decision in Windows Kerberos allows an authorized attacker to elevate privileges over a network...
ZkRansomware: Proof-Of-Data Recoverability and Multi-Round Game Theoretic Modeling of Ransomware Decisions
Ransomware is still one of the most serious cybersecurity threats. Victims often pay but fail to regain access to their data, while also facing the danger of losing data privacy. These uncertainties heavily shape the attacker-victim dynamics in decision-making. In this paper, we introduce and...
CVE-2008-7320
GNOME Seahorse through 3.30 allows physically proximate attackers to read plaintext passwords by using the quickAllow dialog at an unattended workstation, if the keyring is unlocked. NOTE: this is disputed by a software maintainer because the behavior represents a design decision...
CVE-2025-1551
IBM Operational Decision Manager 8.11.0.1, 8.11.1.0, 8.12.0.1, and 9.0.0.1 is vulnerable to cross-site scripting. This vulnerability allows an unauthenticated attacker to embed arbitrary JavaScript code in the Web UI thus altering the intended functionality potentially leading to credentials...
CVE-2025-1126
A Reliance on Untrusted Inputs in a Security Decision vulnerability has been identified in the Lexmark Print Management Client...
Decision-Aware Trust Signal Alignment for SOC Alert Triage
Detection systems that utilize machine learning are progressively implemented at Security Operations Centers SOCs to help an analyst to filter through high volumes of security alerts. Practically, such systems tend to reveal probabilistic results or confidence scores which are ill-calibrated and...
Cyberscurity Threats and Defense Mechanisms in IoT Network
The rapid proliferation of Internet of Things IoT technologies, projected to exceed 30 billion interconnected devices by 2030, has significantly escalated the complexity of cybersecurity challenges. This survey aims to provide a comprehensive analysis of vulnerabilities, threats, and defense...
CVE-2025-15176 Open5GS PFCP Session Establishment Request rule-match.c ogs_pfcp_pdr_rule_find_by_packet assertion
A flaw has been found in Open5GS up to 2.7.5. This affects the function decodeipv6header/ogspfcppdrrulefindbypacket of the file lib/pfcp/rule-match.c of the component PFCP Session Establishment Request Handler. Executing a manipulation can lead to reachable assertion. It is possible to launch the...
PentestEval: Benchmarking LLM-Based Penetration Testing with Modular and Stage-Level Design
Penetration testing is essential for assessing and strengthening system security against real-world threats, yet traditional workflows remain highly manual, expertise-intensive, and difficult to scale. Although recent advances in Large Language Models LLMs offer promising opportunities for...
PYSEC-2025-111
An issue was discovered in allauth-django before 65.13.0. Both Okta and NetIQ were using preferredusername as the identifier for third-party provider accounts. That value may be mutable and should therefore be avoided for authorization decisions. The providers are now using sub instead...
CVE-2025-65431
An issue was discovered in allauth-django before 65.13.0. Both Okta and NetIQ were using preferredusername as the identifier for third-party provider accounts. That value may be mutable and should therefore be avoided for authorization decisions. The providers are now using sub instead...
CVE-2025-65431
The django-allauth library (specifically versions before 65.13.0 ) is vulnerable to Improper Authentication (CWE-287). The root cause is the use of the mutable preferred_username attribute as the identifier for third-party Okta and NetIQ provider accounts. Because this value can be changed by a u...
Diverse LLMs Vs. Vulnerabilities: Who Detects and Fixes Them Better?
Large Language Models LLMs are increasingly being studied for Software Vulnerability Detection SVD and Repair SVR. Individual LLMs have demonstrated code understanding abilities, but they frequently struggle when identifying complex vulnerabilities and generating fixes. This study presents...
Security Bulletin: IBM Operational Decision Manager for Oct 2025 - Multiple CVEs addressed
Summary IBM Operational Decision Manager is vulnerable to multiple remote code execution and denial of service attacks in third party and open source used in the product for various functions. See full list below. The vulnerabilities have been addressed. Vulnerability Details CVEID:CVE-2025-22233...
Think Fast: Real-Time IoT Intrusion Reasoning Using IDS and LLMs at the Edge Gateway
As the number of connected IoT devices continues to grow, securing these systems against cyber threats remains a major challenge, especially in environments with limited computational and energy resources. This paper presents an edge-centric Intrusion Detection System IDS framework that integrate...
Security Bulletin: Multiple Vulnerabilities in IBM Decision Optimization for Cloud Pak for Data (CVE-2025-57350, CVE-2025-53057 and CVE-2025-53066)
Summary Multiple Vulnerabilities were addressed in IBM Decision Optimization for Cloud Pak for Data version 5.3.0 Vulnerability Details CVEID:CVE-2025-57350 DESCRIPTION: The csvtojson package, a tool for converting CSV data to JSON with customizable parsing capabilities, contains a prototype...
Adaptive Dual-Layer Web Application Firewall (ADL-WAF) Leveraging Machine Learning for Enhanced Anomaly and Threat Detection
Web Application Firewalls are crucial for protecting web applications against a wide range of cyber threats. Traditional Web Application Firewalls often struggle to effectively distinguish between malicious and legitimate traffic, leading to limited efficacy in threat detection. To overcome these...
Binary and Multiclass Cyberattack Classification on GeNIS Dataset
The integration of Artificial Intelligence AI in Network Intrusion Detection Systems NIDS is a promising approach to tackle the increasing sophistication of cyberattacks. However, since Machine Learning ML and Deep Learning DL models rely heavily on the quality of their training data, the lack of...
