A Cryptographic Perspective on Mitigation Vs. Detection in Machine Learning

In this paper, we initiate a cryptographically inspired theoretical study of detection versus mitigation of adversarial inputs produced by attackers of Machine Learning algorithms during inference time. We formally define defense by detection DbD and defense by mitigation DbM. Our definitions com...

SoK: a Survey of Mixing Techniques and Mixers for Cryptocurrencies

Blockchain technologies have overturned the digital finance industry by introducing a decentralized pseudonymous means of monetary transfer. The pseudonymous nature introduced privacy concerns, enabling various deanonymization techniques, which in turn spurred development of stronger...

The Dark Side of Digital Twins: Adversarial Attacks on AI-Driven Water Forecasting

Digital twins DTs are improving water distribution systems by using real-time data, analytics, and prediction models to optimize operations. This paper presents a DT platform designed for a Spanish water supply network, utilizing Long Short-Term Memory LSTM networks to predict water consumption...

Smart Water Security with AI and Blockchain-Enhanced Digital Twins

Water distribution systems in rural areas face serious challenges such as a lack of real-time monitoring, vulnerability to cyberattacks, and unreliable data handling. This paper presents an integrated framework that combines LoRaWAN-based data acquisition, a machine learning-driven Intrusion...

Security Bug Report Prediction within and across Projects: a Comparative Study of BERT and Random Forest

Early detection of security bug reports SBRs is crucial for preventing vulnerabilities and ensuring system reliability. While machine learning models have been developed for SBR prediction, their predictive performance still has room for improvement. In this study, we conduct a comprehensive...

A Virtual Cybersecurity Department for Securing Digital Twins in Water Distribution Systems

Digital twins DTs help improve real-time monitoring and decision-making in water distribution systems. However, their connectivity makes them easy targets for cyberattacks such as scanning, denial-of-service DoS, and unauthorized access. Small and medium-sized enterprises SMEs that manage these...

Phishing URL Detection Using Bi-LSTM

Phishing attacks threaten online users, often leading to data breaches, financial losses, and identity theft. Traditional phishing detection systems struggle with high false positive rates and are usually limited by the types of attacks they can identify. This paper proposes a deep learning-based...

Leveraging LLM to Strengthen ML-Based Cross-Site Scripting Detection

According to the Open Web Application Security Project OWASP, Cross-Site Scripting XSS is a critical security vulnerability. Despite decades of research, XSS remains among the top 10 security vulnerabilities. Researchers have proposed various techniques to protect systems from XSS attacks, with...

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...

Fast and Robust Speckle Pattern Authentication by Scale Invariant Feature Transform Algorithm in Physical Unclonable Functions

Nowadays, due to the growing phenomenon of forgery in many fields, the interest in developing new anti-counterfeiting device and cryptography keys, based on the Physical Unclonable Functions PUFs paradigm, is widely increased. PUFs are physical hardware with an intrinsic, irreproducible disorder...

SA2FE: a Secure, Anonymous, Auditable, and Fair Edge Computing Service Offloading Framework

The inclusion of pervasive computing devices in a democratized edge computing ecosystem can significantly expand the capability and coverage of near-end computing for large-scale applications. However, offloading user tasks to heterogeneous and decentralized edge devices comes with the dual risk ...

Llama-3.1-FoundationAI-SecurityLLM-Base-8B Technical Report

As transformer-based large language models LLMs increasingly permeate society, they have revolutionized domains such as software engineering, creative writing, and digital arts. However, their adoption in cybersecurity remains limited due to challenges like scarcity of specialized training data a...

Prefill-Based Jailbreak: a Novel Approach of Bypassing LLM Safety Boundary

Large Language Models LLMs are designed to generate helpful and safe content. However, adversarial attacks, commonly referred to as jailbreak, can bypass their safety protocols, prompting LLMs to generate harmful content or reveal sensitive data. Consequently, investigating jailbreak methodologie...

Hybrid Privacy Policy-Code Consistency Check Using Knowledge Graphs and LLMs

The increasing concern in user privacy misuse has accelerated research into checking consistencies between smartphone apps' declared privacy policies and their actual behaviors. Recent advances in Large Language Models LLMs have introduced promising techniques for semantic comparison, but these...

Prompt Injection Attack to Tool Selection in LLM Agents

Whitepaper called Prompt Injection Attack To Tool Selection In LLM Agents...

IWCC 2025 Call for Papers

The 14th International Workshop on Cyber Crime, or IWCC, 2025 call for papers has been announced. It will be held this year in conjunction with the 20th International Conference on Availability, Reliability and Security ARES 2025. It will take place August 11th through the 14th, 2025 in Ghent,...

SAP NetWeaver Visual Composer Metadata Uploader CVE-2025-31324 Scanner

This tool checks to see if the SAP NetWeaver Visual Composer Metadata Uploader component is vulnerable to CVE-2025-31324 and if there are known webshells in the system...

American Fuzzy Lop plus plus 4.32c

Google's American Fuzzy Lop is a brute-force fuzzer coupled with an exceedingly simple but rock-solid instrumentation-guided genetic algorithm. afl++ is a superior fork to Google's afl. It has more speed, more and better mutations, more and better instrumentation, custom module support, etc...

Stegano 1.0.0

Stegano is a basic Python Steganography module. Stegano implements two methods of hiding: using the red portion of a pixel to hide ASCII messages, and using the Least Significant Bit LSB technique. It is possible to use a more advanced LSB method based on integers sets. The sets Sieve of...

A Case Study on the Use of Representativeness Bias As a Defense against Adversarial Cyber Threats

Cyberspace is an ever-evolving battleground involving adversaries seeking to circumvent existing safeguards and defenders aiming to stay one step ahead by predicting and mitigating the next threat. Existing mitigation strategies have focused primarily on solutions that consider software or hardwa...

From Paper Trails to Trust on Tracks: Adding Public Transparency to Railways Via Zk-SNARKs

Railways provide a critical service and operate under strict regulatory frameworks for implementing changes or upgrades. Despite their impact on the public, these frameworks do not define means or mechanisms for transparency towards the public, leading to reduced trust and complex tracking...

Craft CMS 4.x / 5.x Remote Code Execution

Craft CMS proof of concept remote code execution exploit. Versions affected are 3.0.0-RC1 to before 3.9.15, 4.0.0-RC1 to before 4.14.15, and 5.0.0-RC1 to before 5.6.17...

Rational Points and Zeta Functions of Humbert Surfaces with Square Discriminant

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Evaluating Organization Security: User Stories of European Union NIS2 Directive

The NIS2 directive requires EU Member States to ensure a consistently high level of cybersecurity by setting risk-management measures for essential and important entities. Evaluations are necessary to assess whether the required security level is met. This involves understanding the needs and goa...

On the Prevalence and Usage of Commit Signing on GitHub: a Longitudinal and Cross-Domain Study

GitHub is one of the most widely used public code development platform. However, the code hosted publicly on the platform is vulnerable to commit spoofing that allows an adversary to introduce malicious code or commits into the repository by spoofing the commit metadata to indicate that the code...

Detecting Speculative Data Flow Vulnerabilities Using Weakest Precondition Reasoning

Speculative execution is a hardware optimisation technique where a processor, while waiting on the completion of a computation required for an instruction, continues to execute later instructions based on a predicted value of the pending computation. It came to the forefront of security research ...

FCGHunter: Towards Evaluating Robustness of Graph-Based Android Malware Detection

Graph-based detection methods leveraging Function Call Graphs FCGs have shown promise for Android malware detection AMD due to their semantic insights. However, the deployment of malware detectors in dynamic and hostile environments raises significant concerns about their robustness. While recent...

JailbreaksOverTime: Detecting Jailbreak Attacks under Distribution Shift

Safety and security remain critical concerns in AI deployment. Despite safety training through reinforcement learning with human feedback RLHF 32, language models remain vulnerable to jailbreak attacks that bypass safety guardrails. Universal jailbreaks - prefixes that can circumvent alignment fo...

Provably Secure Public-Key Steganography Based on Admissible Encoding

The technique of hiding secret messages within seemingly harmless covertext to evade examination by censors with rigorous security proofs is known as provably secure steganography PSS. PSS evolves from symmetric key steganography to public-key steganography, functioning without the requirement of...

SAGA: a Security Architecture for Governing AI Agentic Systems

Large Language Model LLM-based agents increasingly interact, collaborate, and delegate tasks to one another autonomously with minimal human interaction. Industry guidelines for agentic system governance emphasize the need for users to maintain comprehensive control over their agents, mitigating...

Comparative Analysis of AI-Driven Security Approaches in DevSecOps: Challenges, Solutions, and Future Directions

The integration of security within DevOps, known as DevSecOps, has gained traction in modern software development to address security vulnerabilities while maintaining agility. Artificial Intelligence AI and Machine Learning ML have been increasingly leveraged to enhance security automation, thre...

GTSD: Generative Text Steganography Based on Diffusion Model

With the rapid development of deep learning, existing generative text steganography methods based on autoregressive models have achieved success. However, these autoregressive steganography approaches have certain limitations. Firstly, existing methods require encoding candidate words according t...

ChipletQuake: On-Die Digital Impedance Sensing for Chiplet and Interposer Verification

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A Study on Mixup-Inspired Augmentation Methods for Software Vulnerability Detection

Various deep learning DL methods have recently been utilized to detect software vulnerabilities. Real-world software vulnerability datasets are rare and hard to acquire, as there is no simple metric for classifying vulnerability. Such datasets are heavily imbalanced, and none of the current...

T2VShield: Model-Agnostic Jailbreak Defense for Text-To-Video Models

The rapid development of generative artificial intelligence has made text to video models essential for building future multimodal world simulators. However, these models remain vulnerable to jailbreak attacks, where specially crafted prompts bypass safety mechanisms and lead to the generation of...

CipherBank: Exploring the Boundary of LLM Reasoning Capabilities through Cryptography Challenges

Large language models LLMs have demonstrated remarkable capabilities, especially the recent advancements in reasoning, such as o1 and o3, pushing the boundaries of AI. Despite these impressive achievements in mathematics and coding, the reasoning abilities of LLMs in domains requiring cryptograph...

Security Vulnerabilities in Quantum Cloud Systems: a Survey on Emerging Threats

Quantum computing is becoming increasingly widespread due to the potential and capabilities to solve complex problems beyond the scope of classical computers. As Quantum Cloud services are adopted by businesses and research groups, they allow for greater progress and application in many fields...

Graph of Attacks: Improved Black-Box and Interpretable Jailbreaks for LLMs

The challenge of ensuring Large Language Models LLMs align with societal standards is of increasing interest, as these models are still prone to adversarial jailbreaks that bypass their safety mechanisms. Identifying these vulnerabilities is crucial for enhancing the robustness of LLMs against su...

SONNI: Secure Oblivious Neural Network Inference

In the standard privacy-preserving Machine learning as-a-service MLaaS model, the client encrypts data using homomorphic encryption and uploads it to a server for computation. The result is then sent back to the client for decryption. It has become more and more common for the computation to be...

Redefining Hybrid Blockchains: a Balanced Architecture

Blockchain technology has completely revolutionized the field of decentralized finance with the emergence of a variety of cryptocurrencies and digital assets. However, widespread adoption of this technology by governments and enterprises has been limited by concerns regarding the technology's...

Differentially Private Quasi-Concave Optimization: Bypassing the Lower Bound and Application to Geometric Problems

Whitepaper called Differentially Private Quasi-Concave Optimization: Bypassing The Lower Bound And Application To Geometric Problems...

Steering the CensorShip: Uncovering Representation Vectors for LLM "Thought" Control

Large language models LLMs have transformed the way we access information. These models are often tuned to refuse to comply with requests that are considered harmful and to produce responses that better align with the preferences of those who control the models. To understand how this "censorship...

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...

issabel-pbx 4.0.0-6 Cross Site Request Forgery

issabel-pbx version 4.0.0-6 proof of concept cross site request forgery exploit that creates a new user...

DeSIA: Attribute Inference Attacks against Limited Fixed Aggregate Statistics

Empirical inference attacks are a popular approach for evaluating the privacy risk of data release mechanisms in practice. While an active attack literature exists to evaluate machine learning models or synthetic data release, we currently lack comparable methods for fixed aggregate statistics, i...

LLMpatronous: Harnessing the Power of LLMs for Vulnerability Detection

Despite the transformative impact of Artificial Intelligence AI across various sectors, cyber security continues to rely on traditional static and dynamic analysis tools, hampered by high false positive rates and superficial code comprehension. While generative AI offers promising automation...

Heavy-Tailed Privacy: the Symmetric Alpha-Stable Privacy Mechanism

With the rapid growth of digital platforms, there is increasing apprehension about how personal data is collected, stored, and used by various entities. These concerns arise from the increasing frequency of data breaches, cyber-attacks, and misuse of personal information for targeted advertising...

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...

Revisiting Data Auditing in Large Vision-Language Models

With the surge of large language models LLMs, Large Vision-Language Models VLMs--which integrate vision encoders with LLMs for accurate visual grounding--have shown great potential in tasks like generalist agents and robotic control. However, VLMs are typically trained on massive web-scraped...

Adversarial Attacks on LLM-As-A-Judge Systems: Insights from Prompt Injections

LLM as judge systems used to assess text quality code correctness and argument strength are vulnerable to prompt injection attacks. We introduce a framework that separates content author attacks from system prompt attacks and evaluate five models Gemma 3.27B Gemma 3.4B Llama 3.2 3B GPT 4 and Clau...