Stabilising Explainability Fragility in Cybersecurity AI: The Impact and Mitigation of Multicollinearity in Public Benchmark Datasets

This paper investigates a unexplored yet impactful vulnerability in AI explainability used in intrusion detection IDS: multicollinearity-induced instability. Despite extensive reliance on post-hoc explainability tools such as SHAP or LIME, the impact of correlated features on explanation robustne...

Practical Countermeasure against Attacks Exploiting Detection Efficiency Mismatch in Quantum Key Distribution

We demonstrate a practical countermeasure against a well-known class of attacks on quantum key distribution QKD systems that exploit detection efficiency mismatch, where the receiver's detectors do not exhibit identical responses to incoming photons across all degrees of freedom. This class of...

Measuring Security without Fooling Ourselves: Why Benchmarking Agents Is Hard

The benchmarks used to evaluate AI agents in security-critical roles suffer from crucial weaknesses. Building on recent empirical evidence, we characterize three core challenges that undermine security evaluations: benchmark vulnerabilities, temporal staleness, and runtime uncertainty. We then...

Innovations in Cardless Artificial Intelligence Banking: A Comprehensive Framework for Cyber Secure and Fraud Mitigation Using Machine Learning Algorithms

The advent of cardless artificial intelligence AI banking heralds a paradigm shift in the financial landscape, offering users unprecedented security and convenience. This paper outlines a comprehensive framework designed to enhance cybersecurity, introduce auto-generated virtual cards, and mitiga...

Security of LLM-Generated Code: A Comparative Analysis

The majority of software developers use or are planning to use Artificial Intelligence AI tools in their development processes. Their top reasons include improving productivity and faster learning. In fact, Large Language Model LLM-generated code is currently in production, including in major tec...

Blind Spots in the Guard: How Domain-Camouflaged Injection Attacks Evade Detection in Multi-Agent LLM Systems

Injection detectors deployed to protect LLM agents are calibrated on static, template-based payloads that announce themselves as override directives. We identify a systematic blind spot: when payloads are generated to mimic the domain vocabulary and authority structures of the target document, wh...

Beyond Zero: Enterprise Security for the AI Era

The rise of autonomous AI agents and the accelerating velocity of corporate data access are stretching the application-centric model of zero trust security to its breaking point. This paper introduces Beyond Zero, a new security paradigm designed for the AI era. The Beyond Zero architecture...

A First Measurement Study on Authentication Security in Real-World Remote MCP Servers

The Model Context Protocol MCP is emerging as a common interface connecting large language models LLMs with external services. Remote deployments are becoming increasingly important as agents connect to user-linked online services, such as social, productivity, and financial services. In such...

UFONet 2.0

UFONet abuses OSI Layer 7-HTTP to create/manage 'zombies' and to conduct different attacks using GET/POST, multi-threading, proxies, origin spoofing methods, cache evasion techniques, etc...

UNAD+: An Explainable Hybrid Framework for Unknown Network Attack Detection

The detection of previously unseen network attacks remains a major challenge for intrusion detection systems. Although supervised learning methods often perform well on known attack classes, they are limited when new attack types are not represented in the training data. Unsupervised methods are...

Prompt Overflow: What the Guardrail Inspects Is Not What the Model Infers

Guardrail models a.k.a. safety checkers are widely deployed to screen user inputs before they reach large language models LLMs, serving as a primary defense against prompt injection attacks. Due to strict context constraints, these models handle overlength prompts through truncation or...

Encrypted Neural Networks without Overflows

Fully homomorphic encryption FHE enables private inference by evaluating neural networks on encrypted data. In this way, we can delegate the computation to a third party server without ever revealing the user's data. Currently, the CKKS scheme is the backbone of most efficient FHE implementations...

Market-Analysis-Driven Methodology for Assessing Charging Station Cybersecurity

Modern charging communication standards for electric vehicles include optional security controls such as TLS-based authentication and encryption. However, with tens of thousands of fast charging points deployed in any given country, individually testing each one for security control support is...

angr 9.2.216

angr is an open-source binary analysis platform for Python. It combines both static and dynamic symbolic "concolic" analysis, providing tools to solve a variety of tasks...

FuzzingBrain V2: A Multi-Agent LLM System for Automated Vulnerability Discovery and Reproduction

Software vulnerabilities pose critical security threats, with nearly 50,000 CVEs reported in 2025. While Large Language Models LLMs show promise for automated vulnerability detection, three key challenges remain. First, LLM-generated vulnerability reports suffer from high false positive rates and...

Detecting Offensive Cyber Agents: A Detection-In-Depth Approach

Artificial Intelligence AI agents can now orchestrate cyberattacks. This development is already increasing the speed and scale of cyber attacks, decreasing attack costs, and improving the operational autonomy of cyber capabilities. To defend against these emerging threats, actors must first devel...

Backchaining Loss of Control Mitigations from Mission-Specific Benchmarks in National Security

Affordances and permissions are promising and timely safety levers for mitigating Loss of Control LoC threats in high-stakes deployment contexts, such as national security. Deployers in defense and intelligence could rely on several approaches to identify which affordances and permissions should ...

FreeBSD Security Advisory - FreeBSD-SA-26:20.fusefs

FreeBSD Security Advisory - When a fusefs file system implements extended attributes, the kernel may send a FUSELISTXATTR message to the userspace daemon to retrieve the list of extended attributes for a given file. The FUSE protocol requires the daemon to return a packed list of NUL-terminated...

IronCurtain 0.11.0

IronCurtain is an early-stage research project exploring how to make AI agents safe enough to be genuinely useful. It is a runtime for autonomous AI agents, where security policy is derived from a human-readable constitution. APIs, configuration formats, and architecture may change...

Domijn: The Security of Domain Registrars and the Risk of a Domain Name Takeover

Domain names are key assets for organisation. They anchor an organisation's online presence and reputation, and serve as linking pin for web services and, e.g., email. Consequently, a malicious takeover of a domain can lead to significant damages. Organisations register domain names through...

Detecting Trojaned DNNs Via Spectral Regression Analysis

Modern DNNs are repeatedly fine-tuned to incorporate new data and functionality. This evolutionary workflow introduces a security risk when updated data cannot be fully trusted, as adversaries may implant Trojans during fine-tuning. We present MIST, a Trojan detection approach that analyzes how a...

Profiling User Vulnerability to Phishing through Psychological and Behavioral Factors

Phishing remains one of the most pervasive cybersecurity threats, shifting the focus from technological vulnerabilities to human cognitive and psychological factors. In coherence with the trend of studies on phishing to increasingly focus on human aspects and vulnerable users profiling, this stud...

FreeBSD Security Advisory - FreeBSD-SA-26:24.cap_net

FreeBSD Security Advisory - In the case of the capnet service, when a key present in the old limit was omitted from the new limit, the missing key was treated as "allow any" instead of being rejected...

A Large Language Model Approach to Generating Bypass Rules for Malware Evasion in Analysis Sandbox

Sandbox evasion remains a critical challenge for automated malware analysis, as modern malware employs environment checks to detect analysis platforms and suppress malicious behavior. Existing approaches rely on manually crafted bypass rules that require deep reverse engineering of each evasion...

GenAI-Driven Threat Detection with Microsoft Security Copilot

Defending against today's increasingly sophisticated cyberattacks requires security analysts to continuously translate evolving attacker tradecraft into detection logic. This places defenders in a reactive posture, requiring constantly updated expertise across an increasingly fragmented security...

FreeBSD Security Advisory - FreeBSD-SA-26:23.bsdinstall

FreeBSD Security Advisory - When bsdinstall or bsdconfig are prompted to scan for nearby Wi-Fi networks, they build up a list of network names and use bsddialog1 to prompt the user to select a network. This is implemented using a shell script, and the code which handled network names was not...

FreeBSD Security Advisory - FreeBSD-SA-26:19.file

FreeBSD Security Advisory - A file descriptor can be closed while a thread is blocked in a poll2 or select2 call waiting for that descriptor. Because the blocked thread does not hold a reference to the underlying object, this closure may result in the object being freed while the thread remains...

FreeBSD Security Advisory - FreeBSD-SA-26:18.setcred

FreeBSD Security Advisory - The setcred2 system call is only available to privileged users. However, before the privilege level of the caller is checked, the user-supplied list of supplementary groups is copied into a fixed-size kernel stack buffer without first validating its length. If the...

FreeBSD Security Advisory - FreeBSD-SA-26:21.ptrace

FreeBSD Security Advisory - ptracePTSCREMOTE failed to properly validate parameters for the syscall2 and syscall2 meta-system calls. As a result, a user with the ability to debug a process may trigger arbitrary code execution in the kernel, even if the target process has no special privileges...

HIDBench: Benchmarking Large Language Models for Host-Based Intrusion Detection

Recent benchmark efforts have advanced the evaluation of large language models LLMs in cybersecurity, including tasks such as penetration testing and vulnerability identification. However, a critical cybersecurity task, namely intrusion detection from system logs, remains unexplored. In this work...

VIPER-MCP: Detecting and Exploiting Taint-Style Vulnerabilities in Model Context Protocol Servers

Model Context Protocol MCP has emerged as a standard interface for connecting LLM agents to external tools. Because MCP servers expose privileged operations such as shell execution, network access, and file-system manipulation to agent-driven invocation, implementation flaws in tool handlers can...

FreeBSD Security Advisory - FreeBSD-SA-26:22.libcasper

FreeBSD Security Advisory - libcasper3 communicates with helper processes via UNIX domain sockets, and uses the select2 system call to wait for data to become available. However, it does not verify that its socket descriptor fits within select2's descriptor set size limit of FDSETSIZE 1024...

Wireshark Analyzer 4.6.6

Wireshark is a GTK+-based network protocol analyzer that lets you capture and interactively browse the contents of network frames. The goal of the project is to create a commercial-quality analyzer for Unix and Win32 and to give Wireshark features that are missing from closed-source sniffers. Thi...

Quality and Security Signals in AI-Generated Python Refactoring Pull Requests

As AI agents increasingly contribute to code development and maintenance, there is still limited empirical evidence on the quality and risk characteristics of their changes in real-world projects, particularly for refactoring-oriented contributions. It remains unclear how agent-authored refactori...

Auditing Apple'S DifferentialPrivacy.Framework: Implementation Bugs, Misconfigurations, and Practical Risks

Since 2016, Apple has claimed that device analytics collected to improve user experience are protected by differential privacy DP. Apple's DifferentialPrivacy.framework is deployed across its operating systems and handles sensitive signals such as Safari domains, keyboard events, photo attributes...

DASM: Domain-Aware Sharpness Minimization for Multi-Domain Voice Stream Steganalysis

The growing use of information hiding in network streaming media for covert communication poses a significant security threat, necessitating the development of robust detection technologies. However, existing steganalysis methods for network voice streams mostly rely on data distributions in...

SAGE: Scalable Automatic Gating Ensemble for Confident Negative Harvesting in Fraud Detection

Music streaming fraud, where bad actors artificially inflate stream counts to manipulate chart rankings and royalty payments, poses a significant threat to streaming services and legitimate content creators. Traditional fraud detection approaches struggle with a critical challenge: many legitimat...

Taking Cryptography out of the Data Path Via Near-Memory Processing in DRAM

Cryptographic algorithms such as AES-128 and SHA-256 are fundamental to ensuring data security and integrity. Although these algorithms are computationally efficient, their performance is often constrained by the processor-centric architectures e.g., CPUs, GPUs, primarily due to the memory...

Impacket 0.13.1

Impacket is a collection of Python classes for working with network protocols. Impacket is focused on providing low-level programmatic access to the packets and, for some protocols e.g. SMB1-3 and MSRPC, the protocol implementation itself. Packets can be constructed from scratch, as well as parse...

Joern 4.0.542

Joern is the bug hunter's workbench. With this tool, you can uncover attack surface, sloppy coding practices, and variants of known vulnerabilities using an interactive code analysis shell. Joern supports C, C++, LLVM bitcode, x86 binaries via Ghidra, JVM bytecode via Soot, and Javascript...

A Hybrid Cluster-Based Classification Model for Anomaly Detection in Unbalanced IoT Networks

Detecting anomalies in Internet of Things IoT networks is a critical security challenge, often hampered by highly imbalanced and diverse network traffic datasets. Standard classifiers struggle to perform well across all traffic types. This paper proposes a hybrid detection model to address this...

Fifty Shades of Darknet

The Invisible Internet Project I2P is a peer-to-peer anonymous overlay network whose architecture includes a structurally distinct sublayer not characterized in existing security literature. We term this sublayer the Exclusive Network: nodes here host operational services and draw on I2P's routin...

Refusal Evaluation in Coding LLMs and Code Agents: A Systematic Review of Thirteen Malicious-Code Prompt Corpora (2023-2025)

The evaluation of large language model refusal on malicious-coding tasks now spans at least thirteen publicly released prompt corpora AdvBench, the CyberSecEval family, RMCBench, RedCode, MCGMark, JailbreakBench, CySecBench, MalwareBench, CIRCLE, MOCHA, ASTRA, Scam2Prompt / Innoc2Scam-bench, and...

Awakening the Hydra: Stabilizing Multi-Concept Backdoor Injection in Text-To-Image Diffusion Models

Text-to-image diffusion models are increasingly developed through open-source reuse and repeated downstream fine-tuning, where reused checkpoints are difficult to verify and thus more susceptible to hidden backdoor behaviors. In such ecosystems, a single pretrained model may be sequentially adapt...

Set Shaping Theory As a Complementary Payload-Shaping Layer for Steganography

This paper studies the use of Set Shaping Theory SST as a reversible payload-shaping layer for least significant bit LSB image steganography. The proposal is not intended to replace existing steganographic methods or to compete with them as a new embedding scheme. Instead, SST is positioned as a...

SCARA: A Semantics-Constrained Autonomous Remediation Agent for Opaque Industrial Software Vulnerabilities

Critical-infrastructure operators are increasingly expected to assess and remediate vulnerabilities in deployed industrial software. However, much of this software exists as opaque industrial software OIS, including stripped firmware, proprietary protocol handlers, and compiled control logic...

Hunting Vulnerability Variants in AI Infra: Measurement and Reference-Driven Detection

AI infra has become a shared execution layer for model training, deployment, and agent orchestration. Because many projects reimplement similar model-centric workflows, a vulnerability disclosed in one repository can recur as a variant in another repository with a related design. Yet the prevalen...

Suricata IDPE 8.0.5

Suricata is a network intrusion detection and prevention engine developed by the Open Information Security Foundation and its supporting vendors. The engine is multi-threaded and has native IPv6 support. It's capable of loading existing Snort rules and signatures and supports the Barnyard and...

XAI FL-IDS: A Federated Learning and SHAP-Based Explainable Framework for Distributed Intrusion Detection Systems

An Intrusion Detection System IDS is vital in cybersecurity, detecting unauthorized activity across networks. With attacks on network layers increasing, stronger IDSs are needed. Yet most IDSs rely on centralized detection, forcing IoT nodes to ship data to a server, adding overhead and offering ...

Detecting Data Exfiltration through I2P Anonymity Networks: A Two-Phase Machine Learning Approach

The Invisible Internet Project I2P provides strong anonymity through garlic routing and distributed network architecture, making it attractive for legitimate privacy needs. Nevertheless, the same properties can be exploited by malicious actors to steal sensitive information from corporate network...