SKALD: Scalable K-Anonymisation for Large Datasets

Data privacy and anonymisation are critical concerns in today's data-driven society, particularly when handling personal and sensitive user data. Regulatory frameworks worldwide recommend privacy-preserving protocols such as k-anonymisation to de-identify releases of tabular data. Available...

A Comprehensive Analysis of Adversarial Attacks against Spam Filters

Deep learning has revolutionized email filtering, which is critical to protect users from cyber threats such as spam, malware, and phishing. However, the increasing sophistication of adversarial attacks poses a significant challenge to the effectiveness of these filters. This study investigates t...

OET: Optimization-Based Prompt Injection Evaluation Toolkit

Large Language Models LLMs have demonstrated remarkable capabilities in natural language understanding and generation, enabling their widespread adoption across various domains. However, their susceptibility to prompt injection attacks poses significant security risks, as adversarial inputs can...

Whispers of Data: Unveiling Label Distributions in Federated Learning through Virtual Client Simulation

Federated Learning enables collaborative training of a global model across multiple geographically dispersed clients without the need for data sharing. However, it is susceptible to inference attacks, particularly label inference attacks. Existing studies on label distribution inference exhibits...

AGATE: Stealthy Black-Box Watermarking for Multimodal Model Copyright Protection

Recent advancement in large-scale Artificial Intelligence AI models offering multimodal services have become foundational in AI systems, making them prime targets for model theft. Existing methods select Out-of-Distribution OoD data as backdoor watermarks and retrain the original model for...

The Dark Side of the Web: Towards Understanding Various Data Sources in Cyber Threat Intelligence

Cyber threats have become increasingly prevalent and sophisticated. Prior work has extracted actionable cyber threat intelligence CTI, such as indicators of compromise, tactics, techniques, and procedures TTPs, or threat feeds from various sources: open source data e.g., social networks, internal...

Bandit on the Hunt: Dynamic Crawling for Cyber Threat Intelligence

Public information contains valuable Cyber Threat Intelligence CTI that is used to prevent future attacks. While standards exist for sharing this information, much appears in non-standardized news articles or blogs. Monitoring online sources for threats is time-consuming and source selection is...

A Collaborative Intrusion Detection System Using Snort IDS Nodes

Intrusion Detection Systems IDSs are integral to safeguarding networks by detecting and responding to threats from malicious traffic or compromised devices. However, standalone IDS deployments often fall short when addressing the increasing complexity and scale of modern cyberattacks. This paper...

Integrating Graph Theoretical Approaches in Cybersecurity Education CSCI-RTED

As cybersecurity threats continue to evolve, the need for advanced tools to analyze and understand complex cyber environments has become increasingly critical. Graph theory offers a powerful framework for modeling relationships within cyber ecosystems, making it highly applicable to cybersecurity...

Application of Deep Reinforcement Learning for Intrusion Detection in Internet of Things: a Systematic Review

The Internet of Things IoT has significantly expanded the digital landscape, interconnecting an unprecedented array of devices, from home appliances to industrial equipment. This growth enhances functionality, e.g., automation, remote monitoring, and control, and introduces substantial security...

Q-FAKER: Query-Free Hard Black-Box Attack Via Controlled Generation

Many adversarial attack approaches are proposed to verify the vulnerability of language models. However, they require numerous queries and the information on the target model. Even black-box attack methods also require the target model's output information. They are not applicable in real-world...

Provable Secure Steganography Based on Adaptive Dynamic Sampling

The security of private communication is increasingly at risk due to widespread surveillance. Steganography, a technique for embedding secret messages within innocuous carriers, enables covert communication over monitored channels. Provably Secure Steganography PSS is state of the art for making...

Secure Transfer Learning: Training Clean Models against Backdoor in (Both) Pre-Trained Encoders and Downstream Datasets

Transfer learning from pre-trained encoders has become essential in modern machine learning, enabling efficient model adaptation across diverse tasks. However, this combination of pre-training and downstream adaptation creates an expanded attack surface, exposing models to sophisticated backdoor...

CVE-2025-29916

Suricata is a network Intrusion Detection System, Intrusion Prevention System and Network Security Monitoring engine. Datasets declared in rules have an option to specify the hashsize to use. This size setting isn't properly limited, so the hash table allocation can be large. Untrusted rules can...

WordPress Datasets Manager 1.5 Shell Upload

WordPress Datasets Manager plugin versions 1.5 and below suffer from a remote shell upload vulnerability...

Cybertron Reshapes AI Security as “Cyber Brain” Grows

Previously exclusive to Trend Vision One customers, select Trend Cybertron models, datasets and agents are now available via open-source. Build advanced security solutions and join us in developing the next generation of AI security technology...

lunary access control error vulnerability (CNVD-2025-07602)

lunary is lunary open source a production toolkit for LLM . An access control error vulnerability exists in lunary, which stems from improper access control on the /v1/datasets endpoint, and can be exploited by an attacker to gain access to unauthorized datasets...

Exploit for CVE-2024-52375

WordPress Datasets Manager 💥 Exploit by: Nxploit Khaled Alen...

CVE-2024-10272 Broken Access Control in lunary-ai/lunary

lunary-ai/lunary is vulnerable to broken access control in the latest version. An attacker can view the content of any dataset without any kind of authorization by sending a GET request to the /v1/datasets endpoint without a valid authorization token...

CVE-2024-10272 Broken Access Control in lunary-ai/lunary

lunary-ai/lunary is vulnerable to broken access control in the latest version. An attacker can view the content of any dataset without any kind of authorization by sending a GET request to the /v1/datasets endpoint without a valid authorization token...