Function Name Is All You Need to Detect Blockchain Application Attacks

Blockchain application attacks, targeting business logic bugs in decentralized applications dApps, have been an increasing concern to their developers and users, causing significant financial loss. Existing attack detectors either rely on handcrafted rules for detection, or need difficult-to-obta...

BlueSTAR: Tiered Agentic Architecture for Autonomous Cyber Defense

Cyber attacks are increasingly automated, narrowing the time available for human analysts to detect, reason about, and respond to intrusions. Large language models LLMs offer a promising foundation for autonomous cyber defense because they can correlate heterogeneous evidence and reason about...

Accountability in Certificate Transparency and Variants

Certificate Transparency CT aims to reduce the trust required in Certificate Authorities CAs within the TLS certificate ecosystem. It is supported by all major browsers. The protocol obliges all CAs to record the certificates they issue in a public log, which itself is monitored for compliance an...

TOR Virtual Network Tunneling Tool 0.4.9.12

Tor is a network of virtual tunnels that allows people and groups to improve their privacy and security on the Internet. It also enables software developers to create new communication tools with built-in privacy features. It provides the foundation for a range of applications that allow...

IServ Schoolserver User Enumeration

IServ Schoolserver suffers from a user enumeration vulnerability. The vendor does not feel this is an issue...

Deep-Fake CAPTCHA: Mitigating Next-Generation Social Engineering Attacks

This paper presents DF-CAPTCHA, an active defense against real-time deepfake impersonation in voice and video calls. Instead of passively searching for artifacts, DF-CAPTCHA prompts the caller to perform simple challenge-response tasks that are easy for humans but difficult for current real-time...

Temporal and Multimodal Deep Learning for Cyberattack Detection in LEO Satellite Systems

The growing reliance on Low-Earth Orbit LEO satellite communication systems has increased the need for intelligent methods capable of detecting cyberattacks across complex and dynamic space environments. Unlike conventional network intrusion detection, satellite systems generate heterogeneous...

Meme Coin Factories: Uncovering Large-Scale Manipulations on Pump.Fun

Once complex, creating and deploying a new cryptocurrency has become trivial. Coin launchpads now allow users to generate a new coin with merely a few clicks, at a minimal cost. Launchpad popularity has grown in tandem with the rise of "meme coins," which usually do not offer any novel...

Ensembling LLMs for AI-Augmented Cybersecurity Software Requirements Generation

Translating high-level controls from security standards into concrete, system-specific requirements is central to cybersecurity requirements engineering. Large language models LLMs can accelerate this labor-intensive, recall-sensitive task, but any single run is unreliable: it misses valid...

AutoTrans: AI-Assisted Automatic Translation of Security Assertions for RISC-V Processors

Reusing a set of verified security assertions across RISC-V processor targets remains one of the most expensive bottlenecks in hardware security verification. Manual translation takes hours per assertion. Raw LLM translation is fast but unreliable, introducing signal hallucination, where the mode...

An Empirical Analysis of ReDoS Vulnerabilities and ReDoS Detection Tools

ReDoS vulnerabilities are a type of denial of service software weakness that occurs when a regex is used to validate user-supplied input. In some cases, the regex matching process can take exponential time, leading to a denial of service. In this study, we examine and compare the effectiveness of...

CISA: Critical Manufacturing Sector Profile

This resource provides a graphical overview of the components and main segments of the Critical Manufacturing Sector...

CISA: Commercial Facilities Sector Profile

This resource provides a graphical overview of the components and main segments of the Commercial Facilities Sector...

Module-Lattice-Based Digital Signature Algorithm Utility 20260908

This is mldsa, a module-lattice-based digital signature algorithm utility for generating keypairs, signing and verifying files and data. It has an alter ego, mlsignify, implementing the same command line switches as signify1. The mldsa and mlsignify utilities are based on the libmldsa3 library,...

Big Enough to Break Out: Tracking the Rising Capability of LLM Penetration-Testing Agents

Large language model LLM agents are increasingly applied to penetration testing, but we still know little about what they can do or how they fail. We compare two PentestGPT-based systems: a legacy human-in-the-loop system running the open-weight Kimi K2.5, and a newer autonomous system running...

No-Box Vulnerability Analysis: Description-Only Detection of Indirect Prompt Injection Vulnerabilities in MCP Servers

Conventional vulnerability analysis relies on either system access or dynamic interaction, all of which may be unavailable to third-party analysts auditing closed-source, remotely hosted, critical in situ systems, or commercially gated software. Therefore, we propose a new paradigm of no-box...

DriftNet: A Dual-Head Trajectory Transformer for Detecting and Localizing Prompt Injection in LLM Agents

When an indirect prompt injection succeeds against an LLM agent, the compromise is visible in the agent's own behavior: a benign prefix of tool calls, a poisoned observation, and a suffix of actions that serve the attacker. An operator needs three facts: where the attack entered, which steps it...

Empirical Evaluation of Data Poisoning Attacks in Supervised Learning

Data poisoning corrupts training data to degrade a model or to plant attacker-controlled behavior. This study evaluates two representative training-time attacks, label flipping and backdoor poisoning, on MNIST and Fashion-MNIST with three baseline classifiers: Logistic Regression, Linear SVM, and...

PrivAudit: A Dual-Lens Auditing Framework for Website Privacy Practices under the CCPA

Five years after the enforcement of the California Consumer Privacy Act CCPA, understanding how website privacy practices evolve at scale in response to regulation remains a key challenge for both researchers and regulators. Prior work and regulatory efforts have focused on manual and case-specif...

AgentAudit: An Open, Extensible Framework for Full-Lifecycle Trust Evaluation of AI Agents

Existing evaluation frameworks mostly assess only one part of AI agents, such as task completion AgentBench or security robustness AgentDojo, ASB, rather than the complete pipeline of planning, tool selection, tool execution, memory and reasoning. Failures can occur at any stage, yet existing...

Learning Intrusion Response Strategies for OT Systems

Cyberattacks against Operational Technology OT systems, which monitor and control industrial processes, pose an increasing threat to essential societal services. For this reason, developing automated intrusion response strategies is highly important. In this paper, we present a formal model of an...

Wicked Problem, Parsimonious Solution: Securing Electric Vehicle Charging Station Software

Electric vehicle charging infrastructure presents a suite of novel cyber-physical threats. Among this infrastructure, charging stations are the most vulnerable elements. The software in the charging station supply equipment is particularly vulnerable. Currently, the software is an attack surface...

Private Communication Via Zero-Private-Capacity Quantum Channels

Private communication over a noisy quantum channel requires reliable transmission to the receiver and secrecy from the environment. Whether two channels with zero private capacity can jointly enable private communication is a longstanding open problem in quantum information theory. Here we resolv...

Understanding the Security Boundary of Obfuscation-Based On-Device LLM Protection

Trusted Execution Environments TEEs offer a promising mechanism for safeguarding the intellectual property of on-device Large Language Models LLMs. To overcome the inherent computational bottlenecks of TEEs, existing TEE-Shielded LLM Partition TSLP methods apply efficient obfuscation schemes to...

What Makes Adversarial Examples Transfer across Deepfake Detectors?

Deepfake detectors remain vulnerable to transfer-based black-box attacks, in which adversarial examples are generated on a source surrogate model and transferred to a target model, unknown to the attacker. Yet how source--target compatibility shapes attack success remains poorly understood. Prior...

CodeQL 2.27.0

Discover vulnerabilities across a codebase with CodeQL, an industry-leading semantic code analysis engine. CodeQL lets you query code as though it were data. Write a query to find all variants of a vulnerability, eradicating it forever. Then share your query to help others do the same...

Architecting the Secure AI-SOC: A Neurosymbolic Framework for Pipeline Integrity and Threat Mitigation

The integration of Large Language Models LLMs into Security Operations Centers SOCs streamlines threat intelligence but introduces critical vulnerabilities, notably indirect prompt injection via log poisoning. Adversaries exploit this vector to execute multistep "promptware'' kill chains by...

CARTS: Contextual Autoregressive Rank Transcoding Steganography for Full-Capacity Keyed Text Encoding

Autoregressive language models can be used to transform a payload text into a stegotext of identical token length by preserving per-position rank information across contexts - a methodology we formalize as Contextual Autoregressive Rank Transcoding Steganography CARTS. While the Calgacus...

cPanel EmailTrack CVE-2026-67401 Scanner / Mitigation

This toolkit provides detection and mitigation utilities for CVE-2026-67401, a SQL injection vulnerability affecting the cPanel and WHM EmailTrack functionality. The included scanner checks the installed cPanel version and package integrity, searches system and database logs for suspicious...

Quantifying IIoT Sensor Node Criticality by Fusing Its Data Criticality and Security Vulnerability

The integration of the Industrial Internet of Things IIoT into manufacturing has transformed industrial operations by optimising production management and ensuring product quality through smart industrial sensors that regulate processes based on real-time data. However, these sensor nodes are...

Joern 4.0.624

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...

Towards Tackling Application Logic Flaws through Autonomous Formal-Logic Modeling and Automated Reasoning

Logic flaws pose significant challenges in the design and implementation of modern, semantically rich systems and applications, impacting security, privacy, and trust. These flaws are inherently tied to business-specific semantics and threat models, making their discovery and reasoning difficult...

HermiCache: Enclave-Aware Cache Replacement for Trusted Execution Environments

Trusted Execution Environments TEEs protect enclave memory from untrusted software but remain vulnerable to cache-based side-channel attacks due to shared microarchitectural resources. Existing countermeasures use techniques such as cache partitioning or randomization: these solutions are not ide...

Towards Scalable and Cost-Efficient Vulnerability Detection: A Study on Automatic Query Generation

Static analysis remains a cornerstone of software security, yet the effectiveness of tools such as CodeQL is often limited by the substantial manual effort required to develop high-coverage query suites. While large language models LLMs have emerged as a potential solution for automated code...

CS-Guard: Benchmarking LLM Guardrails for Code Generation Security

Large language models LLMs have been ex- ploited to generate malware, but the effective- ness of guardrails for code generation secu- rity remains unclear. We introduce CS-Guard, the first benchmark to systematically evalu- ate guardrails for code generation security. It covers 1 text-to-code...

MemSentry: A Framework for Detecting Persistent Memory Poisoning in Agentic AI

Agentic AI systems with persistent memory introduce a distinct attack surface known as memory poisoning, in which adversarially crafted content is stored in long-term memory and subsequently influences future agent behavior. Such attacks can suppress security alerts, facilitate privilege...

ACEA: An Adversarial Co-Evolution Arena for Head-To-Head Red-Team and Blue-Team LLM Testing

Automated red-team attacks and blue-team defenses for large language models LLMs are advancing quickly. However, attackers and defenders are built and tested in isolation, and the resulting scores are hard to trust. To tackle this, we present ACEA Adversarial Co-Evolution Arena, a platform that...

Windows Malware Detector As a Compound AI System: Trade-Offs in Accuracy, Efficiency, and Adversarial Robustness

Industrial Windows malware detectors are commonly described as Compound AI Systems composed of multiple heterogeneous components, including rule-based mechanisms as well as machine-learning-based static and dynamic analyses. However, due to industrial secrecy and limited public disclosure, the...

Navigating the Latent Manifold: Proactive Concept Drift Adaptation for Resilient NIDS

Network intrusion detection systems NIDS are critical for cybersecurity, safeguarding services and data from potential attacks. However, existing AI-based NIDS often assume static data distributions and fail to handle concept drift, leading to degraded performance and increased false positives in...

Evidence-Grounded Retrieval for Investigation Hunt Lead Generation from CTI Reports

Threat hunting increasingly depends on converting unstructured knowledge e.g., Cyber Threat Intelligence reports into actionable hunt leads: concise, investigable hypotheses grounded in observable artifacts and adversary techniques. Producing such leads manually is a tedious and hard-to-scale tas...

Towards Standardized Evaluation of GPU Memory Safety with GMSBench

As GPUs become increasingly integral to high-performance computing and machine learning, ensuring memory safety in GPU programs has become crucial for reliable and secure execution. However, evaluating GPU memory safety techniques remains challenging due to the lack of comprehensive and...

LLMSec-AV: A Vulnerability Taxonomy and LLM-Driven Software Weakness Discovery Framework for Autonomous Vehicles

Automated vehicles rely on millions of lines of safety-critical software, yet general-purpose analyzers do not understand which code can affect vehicle motion. This study asks whether large language models LLMs with explicit automated-vehicle AV security knowledge improve weakness detection beyon...

Cascading Gradient Inversion Via LT-Code Inspired Peeling in Federated Learning

Federated learning shares model updates rather than raw data, yet these updates can be inverted to reconstruct the clients' training data. Analytic reconstruction attacks, which invert a gradient in closed form, degrade as the batch grows: prior single-round attacks recover only about half of a...

Flounder 0.4.0

Flounder turns modern coding agents into an end-to-end security audit system. Give it an authorized target boundary - a repository, source tree, package, deployed clue, or prior run - and the agent can prepare the workspace, read the code and supporting material, map the attack surface, dig into...

CISA: Logging Reference Architecture Updated

The Cybersecurity and Infrastructure Security Agency CISA developed the Logging Reference Architecture LRA in alignment with Office of Management and Budget Memorandum M-26-14: Ensuring Effective and Efficient Agency Logging and Network Visibility to Defend Against Evolving Cyber Threats, which w...

Revoked but Still Authoritative: An Empirical Study of Revocation Enforcement in Agent-Memory Systems

Long-running language-model agents depend on persistent memory. Many agent-memory systems preserve history through soft revocation: a contradicted fact is marked invalid and retained rather than deleted. However, whether that mark is enforced at retrieval time is unexamined. In this paper, we...

Black-Box Red Teaming of Agentic AI: A Taxonomy-Driven Framework for Automated Risk Discovery

Agentic systems are rapidly moving to production, where they read untrusted inputs, call tools with real permissions, and act autonomously, expanding the security surface beyond chat-only models. Yet standard evaluations remain single-turn and fail to capture multi-step agent vulnerabilities. We...

NERVE Attacks: Breaking AI-Powered Brain-Computer Interfaces

The rapid integration of AI into human-centred systems such as Brain-Computer Interfaces BCIs has created a poorly understood attack surface linking neural signals to physical systems. Exploits in this domain threaten cognitive autonomy, mental privacy, and physical safety, from neural data...

HoneyRoute: Honeypot-Model Routing for Adversarial LLM Serving

We introduce HoneyRoute, an inference-serving layer that detects whether an incoming request is malicious and, if so, routes it to a dedicated honeypot model, shielding production while the adversary's interaction is continuously harvested for intelligence. Existing defenses embed traps inside...

Benchmark Scores Are Pipeline-Dependent: A Reliability Audit of Cybersecurity LLM Benchmarks

Large language model LLM benchmarks are often treated as fixed datasets with stable scores, yet their outcomes depend on configurable evaluation pipelines. We audit eight cybersecurity benchmarks across 10 proprietary, open-weight, and cybersecurity-specialized LLMs. By modeling benchmarks as...