Topological Attribution Distance (TAD): Revealing Segment-Level RAG Influence on LLM Output Geometry for Incident Log Analysis

Large Language Models LLMs are increasingly being deployed in cybersecurity operations to assist cybersecurity analysts with rapid decision-making against emerging threats. However, there is a main criteria that must be met when using LLMs in cybersecurity, that is, trust in the generated outputs...

Authorization Before Context: A Model-Neutral Audience Boundary against Cross-Audience Memory Leakage in Agentic Systems

A personal language agent learns a fact from one audience and may later place it in the prompt it assembles for another. This memory-to-context step is an attack surface: ambiguous or inconsistent channels, cross-audience prying, and poisoned memory can each cause the system to assemble context...

DSPrompt: Dynamic Soft Prompt Defense against M-RAG Corruption

Multimodal Retrieval Augmented Generation M-RAG is increasingly vulnerable to adversarial attacks where malicious data are crafted to produce embeddings that align with benign entries in the vector space, deceiving retrieval and inducing harmful outputs. Existing defenses primarily operate at que...

Microsoft SharePoint Server SecurityContextToken Deserialization Remote Code Execution

Microsoft SharePoint Server contains an unauthenticated deserialization vulnerability in the /trust/default.aspx WS-Federation endpoint that can allow remote code execution through a crafted SecurityContextToken cookie. This proof of concept uses a BinaryFormatter TypeConfuseDelegate payload...

A Deployment-Oriented and Resource-Efficient Neuro-Symbolic Framework for Explainable DDoS Detection in Operational Technology Networks

Operational technology OT environments, including programmable logic controllers PLCs, industrial control systems ICS, and supervisory control and data acquisition SCADA systems, are increasingly targeted by distributed denial-of-service DDoS attacks. This paper presents a neuro-symbolic framewor...

Budibase 3.31.4 Authentication Bypass / Remote Code Execution

Budibase versions through 3.31.4 contain an authentication and authorization bypass vulnerability that allows an unauthenticated remote attacker to access protected API endpoints by placing a webhook route pattern in the request query string. This proof of concept first verifies the bypass agains...

A Calibrated and Explainable Bimodal Machine Learning Framework for Hybrid Intrusion Detection

Modern communication systems face critical gaps in detecting unknown attacks and rare threat classes due to extreme data imbalance and black-box decision logic. We propose a bimodal framework of calibrated and explainable machine learning ML for network security, unifying known-class precision wi...

openSUSE Security Advisory - openSUSE-SU-2026:11527-1

openSUSE Security Advisory - These are all security issues fixed in the sccache-0.17.01-2.1 package on the GA media of openSUSE Tumbleweed...

LLMs for Zero-Shot Threat Detection Via Structured Risk Indicators

We propose a two-stage large language model LLM framework for zero-shot detection of insider threats and advanced persistent threats APTs from heterogeneous security logs. The framework models user activity as chronological timelines and incorporates retrieval-augmented generation RAG to provide...

PHP BCMath 8.5.8 Remote Code Execution

PHP BCMath versions 8.4.0 through 8.4.23 and 8.5.0 through 8.5.8 contain an out-of-bounds write vulnerability in bcstr2num. The issue can be leveraged from an existing PHP code execution context to corrupt Zend heap metadata, establish arbitrary memory access, resolve native PHP function handlers...

Digital Twin-Based Intrusion Detection for Vehicle Powertrain CAN Bus Systems

Existing automotive intrusion detection systems IDSs for the Controller Area Network CAN largely target discrepancies in message timing, frequency, or sequencing and cannot detect attacks that preserve these properties while manipulating the payload. Digital twins DTs have been used to emulate CA...

Securing AI-Generated Code: A Just-In-Time Vulnerability Detection and Remediation Pipeline

AI-assisted development tools generate vulnerable code at significant rates, yet few automated mechanisms exist to detect, enrich, fix, and verify security issues at development velocity, particularly ones that ground remediation in real-world threat context. This paper presents an automated...

CUSTOS: Toward Forensic-Ready Zero Trust at the Capture-Containment Boundary

Zero Trust ZT replaces implicit trust with continuous verification, but mutual TLS, ephemeral workloads, identity-centric control, and automated remediation reduce payload visibility, weaken IP-based attribution, and shrink the window for acquiring volatile evidence. We propose CUSTOS, a...

SUSE Security Advisory - SUSE-SU-2026:3628-1

SUSE Security Advisory - This update for texlive fixes the following issues. NULL pointer dereference in texk/web2c/pdftexdir/writet1.c. NULL pointer dereference in texk/web2c/pdftexdir/tounicode.c. Use-after-free in synctexparser.c in TeX Live...

Expanding Access, Exposing Risk: A Short Study of Exposed Starlink Hosts

In this very short paper, we present a measurement-driven analysis of the security characteristics of Starlink-connected hosts and uncover several concerning trends. We find that Starlink hosts are more likely to run outdated or vulnerable operating systems and network protocols than non-Starlink...

Citrix NetScaler ADC 13.1 SAML Heap Overflow / Remote Code Execution

Citrix NetScaler ADC and NetScaler Gateway versions prior to 14.1-72.61 and 13.1-63.18 contain a heap overflow vulnerability that can allow an unauthenticated remote attacker to execute arbitrary code when the appliance is configured to use SAML as a service provider or identity provider. This...

Python StateMachine 3.1.2 Remote Code Execution

Python StateMachine 3.1.2 contains a code injection vulnerability in its SCXML processing functionality. The included proof of concept demonstrates code execution by writing a harmless marker file when the malicious SCXML datamodel expression is evaluated...

openSUSE Security Advisory - openSUSE-SU-2026:11524-1

openSUSE Security Advisory - These are all security issues fixed in the python313-pysaml2-7.5.4-1.1 package on the GA media of openSUSE Tumbleweed...

Fastjson 1.2.83 Remote Code Execution

Fastjson versions 1.2.68 through 1.2.83 contain a remote code execution vulnerability that can allow an attacker to cause a vulnerable application to load attacker-controlled Java classes. This proof of concept generates a malicious JAR containing a reverse shell payload, serves the JAR over HTTP...

Proving the Utility of Large Language Models in Cybersecurity Simulations: A Comprehensive Examination

Cyber threats continue to escalate in both frequency and sophistication, necessitating more adaptive and scalable defense strategies. This paper explores how Large Language Models LLMs can bolster cybersecurity simulations by automating the creation of synthetic environments and identifying laten...

Debian Security Advisory 6445-1

Debian Linux Security Advisory 6445-1 - Multiple security vulnerabilities were discovered in Ironic, the OpenStack component to management and provision of baremetal servers, which could result in bypass of administrative access/API restrictions, information disclosure or the execution of arbitra...

Probing the Prefill: Detecting Code Vulnerabilities Via Latent Activations

LLM-based code generation is now embedded in mission-critical pipelines, but defenses against vulnerable output remain post-hoc -- static analyzers, fine-tuned classifiers, or an LLM judge that screen completed code, ignoring the generating model's own internal state. We test a narrower, directly...

MindsDB Minds Platform Cowork Unauthenticated Remote Code Execution

MindsDB Minds Platform Cowork contains an unauthenticated remote code execution vulnerability in the Cowork server API where unauthenticated settings modification can be combined with the Anton agent scratchpad functionality to execute arbitrary Python code without sandboxing. This proof of conce...

When Time Meets Space: Entropy Integration and Dynamic Threshold for Adaptive DDoS Detection in SDN

Entropy-based Distributed Denial of Service DDoS detection in Software-Defined Networking SDN commonly relies on spatial traffic distributions and static or loosely adaptive thresholds, making it vulnerable to legitimate traffic fluctuations in Internet of Things IoT environments. This paper...

Assessing Attack Surfaces in Generative Search Engines through Publisher Attributes: A Case Study in Political Domains

We characterize the attack surface of generative search engines GSEs against poisoning attacks in the political domain, from the perspectives of citation selection and personalization. GSEs integrate web search and answer generation with user preferences and backgrounds using large language model...

Proof-Of-Execution Memory: Defending LLM Agents against Forged-Reasoning Attacks by Verifying What Actually Happened

LLM agents are stateless and rely on external memory to carry context between steps. Because agents treat that memory as trustworthy, an adversary who can write to it can steer their behavior. The FARMA attack does this with no malicious command: it inserts fabricated entries into the agent's...

Bounded Agents: Delegation Security for Multi-Agent AI Systems

LLM-based agents can act on behalf of a user to access cloud services, call tools, or invoke agents. At session start, the agent's permissions are set but remain static, and each request is evaluated independently, without considering prior actions. Within its permissions, an agent may act contra...

Breaking and Defending LLM-Powered Social Media Bot Detection Systems

The rise of social media bots poses a persistent threat, enabling misinformation, opinion manipulation, and the erosion of trust in online platforms. To combat this, machine learning systems have been developed to detect and limit bot activity, but attackers continuously adapt through techniques...

Benchmarking Identity-Sensitive LLM Outputs for Surveillance and Security Robots

Large language models LLMs are increasingly used to generate textual robot design specifications, interaction policies, and risk assessments during early-stage robot development. Such outputs may influence how surveillance and security robots are conceptualized, documented, and ultimately...

Beyond Direct Access: Resource Hijacking in LLM Agents

Large language model agents are increasingly connected to high-value resources such as computing infrastructure, credentials, usage budgets, identities, private knowledge, communication channels, and organizational workflows. Existing agent security research mainly studies attacks on instructions...

Beyond Single-Vulnerability Evaluation: Closing the Engineering Decision Gap between C Retrofits and Native Safety

While decades of research have produced numerous retrofitted memory-safety protections for C, these mechanisms are almost exclusively evaluated in isolation, targeting specific vulnerability classes. This siloed evaluation paradigm leaves practitioners without a clear understanding of the...

SAEFUZZ: Smart Contract Vulnerability Detection through Statically Guided Evolutionary Fuzzing

The effectiveness of smart contract fuzzing depends strongly on whether generated transactions reach deep, state-dependent execution paths. Existing fuzzers often generate highly random call sequences, wasting executions on semantically invalid or low-value states and leaving vulnerabilities that...

Bit-Flip Attacks on Vision-Language-Action Models: Action-Decoding Architecture Shapes the Vulnerability

Quantized Vision-Language-Action VLA models expose a weight-fault surface: Rowhammer-style faults can corrupt deployed INT8 bits. We present the first bit-flip attack on a VLA: a few gradient-selected flips reduce closed-loop success to $0%$, while hundreds of random flips are harmless. Across...

Hierarchical Agentic Incident Response with Digital-Twin-Validated Attack Inference

Network incident response remains slow and labor-intensive as the defender must infer multi-stage attacks from partial observations and translate recovery decisions into reliable system commands. Decision-theoretic planners provide principled optimization but typically rely on abstract states and...

WeSCE: A Benchmark for Measuring Security Drift in LLM-Driven Code Editing

In this work, we introduce WeSCE, a benchmark for quantifying security drift in code editing under weak-security constraints, where tasks specify only functional objectives without explicit security requirements. WeSCE consists of 400 executable programs derived from real-world code, covering...

Pre-Model Representation Failures in GNN-Based Smart Contract Vulnerability Detection

This paper is a failure analysis of the representation layer underlying GNN-based smart contract vulnerability detectors. These systems convert source code into graphs before any learning takes place; if the graph fails to capture the code's semantics, no model improvement can compensate. We...

Finding Vulnerabilities Via LLM-Augmented Semantics-Aware Type-Checking

Vulnerability detection via static analysis traditionally relies on security experts encoding insecure coding patterns into algorithmic rules. However, this approach often focuses on syntactic patterns and overlooks deeper semantic information in the code, such as the meanings of variable and...

Apple Security Advisory 08-06-2026-2

Apple Security Advisory 08-06-2026-2 - macOS Sequoia 15.7.9 addresses addresses an authentication bypass issue on Screen Sharing...

Structural Leakage in Graph Encryption: Attacks and Defenses

Graph encryption schemes GES enable secure outsourcing of graph data while supporting efficient queries. This report provides a comprehensive analysis of structural leakage in GES for single-pair shortest path SPSP queries, integrating findings from two recent works. First, we analyze PathGES, a...

MazeRunner: Nonlinear Task and Clue Orchestration for LLM-Driven Black-Box Automated Penetration Testing

Penetration testing is essential yet resource-intensive. Although large language models LLMs show promise for automating security auditing, existing agents mainly execute end-to-end workflows in simplified linear scenarios. Real-world black-box testing is fundamentally nonlinear: the attack graph...

Extracting and Verifying Illicit Bitcoin Addresses from Underground Forum Discussions

Existing labeled Bitcoin datasets are largely derived from community-reported abuse, blockchain heuristics, incident-specific collections, or proprietary labeling processes. Their construction methods are rarely publicly reproducible and often provide limited evidence that an address was directly...

Trust without Boundaries: An Architectural Analysis of Satellite Flight Software

As spacecraft become more software-driven and interconnected, onboard flight software is an increasingly important security boundary. Popular flight software architectures often treat onboard components as trusted peers, simplifying integration while limiting internal isolation and access control...

STINER: Automated Extraction of Strategic Cyber Threat Intelligence from X

Strategic Cyber Threat Intelligence CTI focuses on high-level insights, such as identifying targeted industries, attributing attacks to specific ransomware groups, and assessing the scale of data loss. Today, X formerly Twitter has become the fastest source for this intelligence, often hosting...

A Hybrid LLM-Based Framework for Automated Security Annotation Generation in Business Process Models

The modelling and analysis of secure business processes require the incorporation of security annotations into process models. Although BPMN extensions, including SecBPMN2, exist for this purpose, the derivation of accurate and complete security annotations from natural-language specifications...

Apple Security Advisory 08-06-2026-3

Apple Security Advisory 08-06-2026-3 - macOS Sonoma 14.8.9 addresses an authentication bypass issue on Screen Sharing...

BGA: A Noise-Immune Neural Distillation Framework for Malicious Signature Extraction in High-Entropy Encrypted Flows

To mitigate attention dilution in high-entropy TLS 1.3 flows, we propose BGA, a noise-immune neural distillation framework for encrypted threat intelligence.The methodology first employs Analysis of Variance ANOVA to decouple high-discriminatory control-plane features - specifically industrial...

Workspace Topology As an Attack Vector in Agentic Coding Assistants

Agentic coding assistants are finding widespread use, not just in new code development but in quickly ingesting and leveraging third-party code. This opens up a risk of malicious code being ingested as these coding tools operate with broad filesystem access inside developer workspaces. In this...

Characterizing the Variance Envelope: A Multi-Dimensional Analysis of Spectre Telemetry across Architectures and Workloads

Hardware attacks like Spectre exploit built-in processor vulnerabilities, leaving anomalous footprints in Hardware Performance Counter HPC metrics. While machine learning can detect these footprints in controlled settings, static models fail in the real world when confronted with background syste...

The Ack3 H1 2026 DeFi Incident Dataset: Audit Scope across 135 Security Incidents

Smart-contract audits cover defined artifacts at a specific time, but the label audited is often treated as project-wide assurance. We analyze audit history and incident-path scope across 135 DeFi security incidents using the H1 2026 DeFi Incident Dataset published by cybersecurity company ack3...

Metabase 0.63.4 SQL Injection Checker

A vulnerability checker for an unauthenticated SQL injection vulnerability in Metabase versions 0.58.0 through 0.63.4. The vulnerability affects the password reset functionality and can allow a remote unauthenticated attacker to execute arbitrary SQL against the Metabase application database,...