1040 matches found
Prompt Engineering Vs. Fine-Tuning for LLM-Based Vulnerability Detection in Solana and Algorand Smart Contracts
Smart contracts have emerged as key components within decentralized environments, enabling the automation of transactions through self-executing programs. While these innovations offer significant advantages, they also present potential drawbacks if the smart contract code is not carefully design...
MTAttack: Multi-Target Backdoor Attacks against Large Vision-Language Models
Recent advances in Large Visual Language Models LVLMs have demonstrated impressive performance across various vision-language tasks by leveraging large-scale image-text pretraining and instruction tuning. However, the security vulnerabilities of LVLMs have become increasingly concerning,...
How Can We Effectively Use LLMs for Phishing Detection?: Evaluating the Effectiveness of Large Language Model-Based Phishing Detection Models
Large language models LLMs have emerged as a promising phishing detection mechanism, addressing the limitations of traditional deep learning-based detectors, including poor generalization to previously unseen websites and a lack of interpretability. However, LLMs' effectiveness for phishing...
Taught by the Flawed: How Dataset Insecurity Breeds Vulnerable AI Code
AI programming assistants have demonstrated a tendency to generate code containing basic security vulnerabilities. While developers are ultimately responsible for validating and reviewing such outputs, improving the inherent quality of these generated code snippets remains essential. A key...
cosmos-predict2 (>=1.0.6 <=1.0.9), frankenstein-model (>=5.1.6 <=5.3.9) +11 more potentially affected by CVE-2025-23357 via megatron-core (>=0.10.0 <=0.13.1)
megatron-core PYPI version =0.10.0, =1.0.6, =5.1.6, =0.4.0, =1.0.0, =2.0.8, =2.0.8, =1.0.0, =1.0.0, =1.0.0, =1.0.0, =1.0.0, =1.0.0, =2.0.5, =5.0.4 Source cves: CVE-2025-23357 Source advisory: SNYK:PYTHON-MEGATRONCORE-13901364...
Have I Been Pwned Adds 1.96B Accounts From Synthient Credential Data
Have I Been Pwned HIBP, the popular breach notification service, has added another massive dataset to its platform.…...
Introducing Nylon Face Mask Attacks: A Dataset for Evaluating Generalised Face Presentation Attack Detection
Face recognition systems are increasingly deployed across a wide range of applications, including smartphone authentication, access control, and border security. However, these systems remain vulnerable to presentation attacks PAs, which can significantly compromise their reliability. In this wor...
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...
Trustworthiness Calibration Framework for Phishing Email Detection Using Large Language Models
Phishing emails continue to pose a persistent challenge to online communication, exploiting human trust and evading automated filters through realistic language and adaptive tactics. While large language models LLMs such as GPT-4 and LLaMA-3-8B achieve strong accuracy in text classification, thei...
Temporal Analysis Framework for Intrusion Detection Systems: A Novel Taxonomy for Time-Aware Cybersecurity
Most intrusion detection systems still identify attacks only after significant damage has occurred, detecting late-stage tactics rather than early indicators of compromise. This paper introduces a temporal analysis framework and taxonomy for time-aware network intrusion detection. Through a...
1 PoCo: Agentic Proof-Of-Concept Exploit Generation for Smart Contracts
Smart contracts operate in a highly adversarial environment, where vulnerabilities can lead to substantial financial losses. Thus, smart contracts are subject to security audits. In auditing, proof-of-concept PoC exploits play a critical role by demonstrating to the stakeholders that the reported...
Federated Cyber Defense: Privacy-Preserving Ransomware Detection across Distributed Systems
Detecting malware, especially ransomware, is essential to securing today's interconnected ecosystems, including cloud storage, enterprise file-sharing, and database services. Training high-performing artificial intelligence AI detectors requires diverse datasets, which are often distributed acros...
Characterizing Build Compromises through Vulnerability Disclosure Analysis
The software build process transforms source code into deployable artifacts, representing a critical yet vulnerable stage in software development. Build infrastructure security poses unique challenges: the complexity of multi-component systems source code, dependencies, build tools, the difficult...
Android Malware Detection: A Machine Learning Approach
This study examines machine learning techniques like Decision Trees, Support Vector Machines, Logistic Regression, Neural Networks, and ensemble methods to detect Android malware. The study evaluates these models on a dataset of Android applications and analyzes their accuracy, efficiency, and...
A Large Scale Study of AI-Based Binary Function Similarity Detection Techniques for Security Researchers and Practitioners
Binary Function Similarity Detection BFSD is a foundational technique in software security, underpinning a wide range of applications including vulnerability detection, malware analysis. Recent advances in AI-based BFSD tools have led to significant performance improvements. However, existing...
Meta-Learning Based Radio Frequency Fingerprinting for GNSS Spoofing Detection
The rapid development of technology has led to an increase in the number of devices that rely on position, velocity, and time PVT information to perform their functions. As such, the Global Navigation Satellite Systems GNSS have been adopted as one of the most promising solutions to provide PVT...
Mind the Gap: Missing Cyber Threat Coverage in NIDS Datasets for the Energy Sector
Network Intrusion Detection Systems NIDS developed using publicly available datasets predominantly focus on enterprise environments, raising concerns about their effectiveness for converged Information Technology IT and Operational Technology OT in energy infrastructures. This study evaluates the...
MH-1M: A 1.34 Million-Sample Comprehensive Multi-Feature Android Malware Dataset for Machine Learning, Deep Learning, Large Language Models, and Threat Intelligence Research
We present MH-1M, one of the most comprehensive and up-to-date datasets for advanced Android malware research. The dataset comprises 1,340,515 applications, encompassing a wide range of features and extensive metadata. To ensure accurate malware classification, we employ the VirusTotal API,...
Cross-site Scripting (XSS)
Overview ckan is a world’s leading Open Source data portal platform. It powers dozens of Open Data portals around the world, including data.gov, open.canada.ca and europeandataportal.eu but also regional, research and community organizations. It makes easy to publish, share and find data online a...
