I2P 2.12.0

I2P is an anonymizing network, offering a simple layer that identity-sensitive applications can use to securely communicate. All data is wrapped with several layers of encryption, and the network is both distributed and dynamic, with no trusted parties. This is the source code release version...

OWASP CRS Arbitrary File Upload

A vulnerability was identified in OWASP CRS where whitespace padding in filenames can bypass file upload extension checks, allowing uploads of dangerous files such as .php, .phar, .jsp, and .jspx. This has been addressed in versions 3.3.9, 4.25.x LTS, and 4.8.x...

Security Awareness in LLM Agents: The NDAI Zone Case

NDAI zones let inventor and investor agents negotiate inside a Trusted Execution Environment TEE where any disclosed information is deleted if no deal is reached. This makes full IP disclosure the rational strategy for the inventor's agent. Leveraging this infrastructure, however, requires agents...

Agent Privilege Separation in OpenClaw: A Structural Defense against Prompt Injection

Prompt injection remains one of the most practical attack vectors against LLM-integrated applications. We replicate the Microsoft LLMail-Inject benchmark Greshake et al., 2024 against current generation models running inside OpenClaw, an open source multitool agent platform. Our proposed defense...

AttriGuard: Defeating Indirect Prompt Injection in LLM Agents Via Causal Attribution of Tool Invocations

LLM agents are highly vulnerable to Indirect Prompt Injection IPI, where adversaries embed malicious directives in untrusted tool outputs to hijack execution. Most existing defenses treat IPI as an input-level semantic discrimination problem, which often fails to generalize to unseen payloads. We...

TraceGuard: Process-Guided Firewall against Reasoning Backdoors in Large Language Models

The deployment of Large Reasoning Models LRMs in high-stakes decision-making pipelines has introduced a novel and opaque attack surface: reasoning backdoors. In these attacks, the model's intermediate Chain-of-Thought CoT is manipulated to provide a linguistically plausible but logically fallacio...

BeyondTrust RS 25.3.1 PRA/RS Mass Scanner

This Metasploit module is a safe auxiliary scanner for the Metasploit Framework designed to identify potentially vulnerable deployments of BeyondTrust Privileged Remote Access and BeyondTrust Remote Support that are susceptible to CVE-2026-1731...

Zabbix Agent Binaries Path Abuse Scanner

This scanner performs automated static analysis of Zabbix Agent binaries to detect hardcoded OpenSSL configuration paths that may enable provider or engine abuse. It identifies embedded OPENSSLDIR, ENGINESDIR, and MODULESDIR values, extracts OpenSSL version information, and checks for dynamic...

CVE-Factory: Scaling Expert-Level Agentic Tasks for Code Security Vulnerability

CVE-Factory is a Multi-Agent system for fully automated, end-to-end CVE reproduction. Given CVE records, the system automatically researches details, generates test cases, builds Docker environments, and validates that each vulnerability can be both exploited and patched. The pipeline transforms...

StackWarp: Breaking AMD SEV-SNP Integrity via Deterministic Stack-Pointer Manipulation through the CPU's Stack Engine

In this paper, the authors present StackWarp, a software-based architectural attack exploiting the stack engine on AMD Zen CPUs to modify the stack pointer within an SEV-SNP guest, fully breaking integrity...

Zer0n: An AI-Assisted Vulnerability Discovery and Blockchain-Backed Integrity Framework

As vulnerability research increasingly adopts generative AI, a critical reliance on opaque model outputs has emerged, creating a "trust gap" in security automation. We address this by introducing Zer0n, a framework that anchors the reasoning capabilities of Large Language Models LLMs to the...

ALFA: A Safe-By-Design Approach to Mitigate Quishing Attacks Launched Via Fancy QR Codes

Phishing with Quick Response QR codes is termed as Quishing. The attackers exploit this method to manipulate individuals into revealing their confidential data. Recently, we see the colorful and fancy representations of QR codes, the 2D matrix of QR codes which does not reflect a typical mixture ...

Penetration Testing of Agentic AI: A Comparative Security Analysis across Models and Frameworks

Agentic AI introduces security vulnerabilities that traditional LLM safeguards fail to address. Although recent work by Unit 42 at Palo Alto Networks demonstrated that ChatGPT-4o successfully executes attacks as an agent that it refuses in chat mode, there is no comparative analysis in multiple...

A Practical Framework for Evaluating Medical AI Security: Reproducible Assessment of Jailbreaking and Privacy Vulnerabilities across Clinical Specialties

Medical Large Language Models LLMs are increasingly deployed for clinical decision support across diverse specialties, yet systematic evaluation of their robustness to adversarial misuse and privacy leakage remains inaccessible to most researchers. Existing security benchmarks require GPU cluster...

A Novel Trust-Based DDoS Cyberattack Detection Model for Smart Business Environments

As the frequency and complexity of Distributed Denial-of-Service DDoS attacks continue to increase, the level of threats posed to Smart Internet of Things SIoT business environments have also increased. These environments generally have several interconnected SIoT systems and devices that are...

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...

SecTracer: A Framework for Uncovering the Root Causes of Network Intrusions Via Security Provenance

Modern enterprise networks comprise diverse and heterogeneous systems that support a wide range of services, making it challenging for administrators to track and analyze sophisticated attacks such as advanced persistent threats APTs, which often exploit multiple vectors. To address this challeng...

Quantifying the Risk of Transferred Black Box Attacks

Neural networks have become pervasive across various applications, including security-related products. However, their widespread adoption has heightened concerns regarding vulnerability to adversarial attacks. With emerging regulations and standards emphasizing security, organizations must...

Adapting Large Language Models to Emerging Cybersecurity Using Retrieval Augmented Generation

Security applications are increasingly relying on large language models LLMs for cyber threat detection; however, their opaque reasoning often limits trust, particularly in decisions that require domain-specific cybersecurity knowledge. Because security threats evolve rapidly, LLMs must not only...

SIRAJ: Diverse and Efficient Red-Teaming for LLM Agents Via Distilled Structured Reasoning

The ability of LLM agents to plan and invoke tools exposes them to new safety risks, making a comprehensive red-teaming system crucial for discovering vulnerabilities and ensuring their safe deployment. We present SIRAJ: a generic red-teaming framework for arbitrary black-box LLM agents. We emplo...

Wazuh 4.14.0

Wazuh is a free and open source security platform that unifies XDR and SIEM capabilities. It protects workloads across on-premises, virtualized, containerized, and cloud-based environments. This is the source code release...

Enhancing Security in Deep Reinforcement Learning: A Comprehensive Survey on Adversarial Attacks and Defenses

With the wide application of deep reinforcement learning DRL techniques in complex fields such as autonomous driving, intelligent manufacturing, and smart healthcare, how to improve its security and robustness in dynamic and changeable environments has become a core issue in current research...

Active Honeypot Guardrail System: Probing and Confirming Multi-Turn LLM Jailbreaks

Large language models LLMs are increasingly vulnerable to multi-turn jailbreak attacks, where adversaries iteratively elicit harmful behaviors that bypass single-turn safety filters. Existing defenses predominantly rely on passive rejection, which either fails against adaptive attackers or overly...

SpyChain: Multi-Vector Supply Chain Attacks on Small Satellite Systems

Small satellites are integral to scientific, commercial, and defense missions, but reliance on commercial off-the-shelf COTS hardware broadens their attack surface. Although supply chain threats are well studied in other cyber-physical domains, their feasibility and stealth in space systems remai...

Large Language Models for Security Operations Centers: a Comprehensive Survey

Large Language Models LLMs have emerged as powerful tools capable of understanding and generating human-like text, offering transformative potential across diverse domains. The Security Operations Center SOC, responsible for safeguarding digital infrastructure, represents one of these domains. SO...

Breaking to Build: a Threat Model of Prompt-Based Attacks for Securing LLMs

The proliferation of Large Language Models LLMs has introduced critical security challenges, where adversarial actors can manipulate input prompts to cause significant harm and circumvent safety alignments. These prompt-based attacks exploit vulnerabilities in a model's design, training, and...

CISA: 2025 Minimum Elements for a Software Bill of Materials (SBOM)

CISA is requesting public comment on its updated guidance on Software Bill of Materials SBOM to reflect the current state of maturity in software transparency and supply chain security. Building on the 2021 NTIA SBOM Minimum Elements, this update aims to help agencies and organizations to manage...

Attack Graph Generation on HPC Clusters

Attack graphs AGs are graphical tools to analyze the security of computer networks. By connecting the exploitation of individual vulnerabilities, AGs expose possible multi-step attacks against target networks, allowing system administrators to take preventive measures to enhance their network's...

MalFlows: Context-Aware Fusion of Heterogeneous Flow Semantics for Android Malware Detection

Static analysis, a fundamental technique in Android app examination, enables the extraction of control flows, data flows, and inter-component communications ICCs, all of which are essential for malware detection. However, existing methods struggle to leverage the semantic complementarity across...

Gandia Integra Total 4.4.2236.1 SQL Injection

Gandia Integra Total versions 2.1.2217.3 through 4.4.2236.1 suffer from a remote SQL injection vulnerability...

Can Large Language Models Automate the Refinement of Cellular Network Specifications?

Cellular networks serve billions of users globally, yet concerns about reliability and security persist due to weaknesses in 3GPP standards. However, traditional analysis methods, including manual inspection and automated tools, struggle with increasingly expanding cellular network specifications...

Organizational Adaptation to Generative AI in Cybersecurity: a Systematic Review

Cybersecurity organizations are adapting to GenAI integration through modified frameworks and hybrid operational processes, with success influenced by existing security maturity, regulatory requirements, and investments in human capital and infrastructure. This qualitative research employs...

VReaves: Eavesdropping on Virtual Reality App Identity and Activity Via Electromagnetic Side Channels

Virtual reality VR has recently proliferated significantly, consisting of headsets or head-mounted displays HMDs and hand controllers for an embodied and immersive experience. The VR device is usually embedded with different kinds of IoT sensors, such as cameras, microphones, communication sensor...

SAFEx: Analyzing Vulnerabilities of MoE-Based LLMs Via Stable Safety-Critical Expert Identification

Large language models based on Mixture-of-Experts have achieved substantial gains in efficiency and scalability, yet their architectural uniqueness introduces underexplored safety alignment challenges. Existing safety alignment strategies, predominantly designed for dense models, are ill-suited t...

Privacy-Preserving LLM Interaction with Socratic Chain-Of-Thought Reasoning and Homomorphically Encrypted Vector Databases

Large language models LLMs are increasingly used as personal agents, accessing sensitive user data such as calendars, emails, and medical records. Users currently face a trade-off: They can send private records, many of which are stored in remote databases, to powerful but untrusted LLM providers...

Beyond the Protocol: Unveiling Attack Vectors in the Model Context Protocol Ecosystem

The Model Context Protocol MCP is an emerging standard designed to enable seamless interaction between Large Language Model LLM applications and external tools or resources. Within a short period, thousands of MCP services have already been developed and deployed. However, the client-server...

RADEP: a Resilient Adaptive Defense Framework against Model Extraction Attacks

Machine Learning as a Service MLaaS enables users to leverage powerful machine learning models through cloud-based APIs, offering scalability and ease of deployment. However, these services are vulnerable to model extraction attacks, where adversaries repeatedly query the application programming...

MADCAT: Combating Malware Detection under Concept Drift with Test-Time Adaptation

We present MADCAT, a self-supervised approach designed to address the concept drift problem in malware detection. MADCAT employs an encoder-decoder architecture and works by test-time training of the encoder on a small, balanced subset of the test-time data using a self-supervised objective. Duri...

Defining Atomicity (And Integrity) for Snapshots of Storage in Forensic Computing

The acquisition of data from main memory or from hard disk storage is usually one of the first steps in a forensic investigation. We revisit the discussion on quality criteria for "forensically sound" acquisition of such storage and propose a new way to capture the intent to acquire an...

WordPress PDF 2 Post 2.4.0 Shell Upload

WordPress PDF 2 Post plugin versions 2.4.0 and below suffers from a remote shell upload vulnerability via a zip file...

WordPress WP-Advanced-Search 3.3.9.3 Shell Upload

WordPress WP-Advanced-Search plugin versions 3.3.9.3 and below suffer from a remote shell upload vulnerability...

GraphAttack: Exploiting Representational Blindspots in LLM Safety Mechanisms

Large Language Models LLMs have been equipped with safety mechanisms to prevent harmful outputs, but these guardrails can often be bypassed through "jailbreak" prompts. This paper introduces a novel graph-based approach to systematically generate jailbreak prompts through semantic transformations...

GNUnet P2P Framework 0.24.1

GNUnet is a peer-to-peer framework with focus on providing security. All peer-to-peer messages in the network are confidential and authenticated. The framework provides a transport abstraction layer and can currently encapsulate the network traffic in UDP IPv4 and IPv6, TCP IPv4 and IPv6, HTTP, o...

WordPress Processing Projects 1.0.2 Shell Upload

WordPress Processing Projects plugin versions 1.0.2 and below suffer from a remote shell upload vulnerability...

WordPress Elementor Pro Animation Addon 1.6 Missing Authorization

The Animation Addons for Elementor Pro plugin versions 1.6 and below on WordPress suffers from a missing capability check allowing for arbitrary plugin installation...

JEV As a Judge for Agent Trace Security: An Empirical Comparison with Generative LLM Judges

Security evaluation of tool-using agents requires judging actions in context, yet generative judges add latency, explanation overhead, and output-validation failures. We study whether JEV, a typed decision model, offers a useful alternative for retrospective trace classification. We evaluate JEV...

CoSec: Benchmarking Agent Security in Communities

Whitepaper called CoSec: Benchmarking Agent Security In Communities...

Logpresso Log4j2 Scanner 3.0.2

Logpresso Log4j2 Scanner version 3.0.2 scans archives recursively for vulnerable Log4j components, including CVE-2021-44228, and can optionally back up and remove vulnerable classes...

Automating Attack Graph Construction for Agentic Pentesting. Towards Neuro-Symbolic Vulnerability Hunting

Logic attack graphs grounded in scanner output provide explicit and auditable attack path reasoning LLM-based agents lack. Integrating symbolic frameworks such as MulVAL to contemporary security workflows or agentic pipelines, however, requires translating scanner evidence to initial facts, and...

SkillSecurer: Detecting and Patching Prompt-Injection Vulnerabilities in AI Agent Skills

Agent skills extend AI agents with reusable instructions, scripts, and configuration, but are also open to new attacks to influence an agent's decisions and actions. To address these risks, we present SkillSecurer, a fully agentic framework for generating, detecting, localising, and remediating...