Athena: Vulnerability-Affected Library Identification Via Knowledge Graph Completion

A single vulnerability in a widely used library can cascade through millions of dependent applications, yet more than half of vulnerability database entries contain missing or incorrect affected-library information. Existing automated approaches neglect the relational structure of vulnerability...

From Silicon to Boot Code: Extending Automated Program Repair to Firmware-Layer Security Workarounds

Automated program repair APR research has been constrained to design time. Current techniques localize and fix bugs in RTL or HLS designs before a chip reaches production. Once a hardware vulnerability surfaces post-silicon, the patch must be manually generated: existing automation addresses patc...

Johnny Still Receives Spam SMS: Assessing the Robustness of SMS Spam Detection

SMS spam detection systems often achieve high accuracy in controlled environments but struggle against adversarial attacks and increasingly sophisticated spam tactics in real-world deployments. In this paper, we evaluate the robustness of SMS anti-spam systems that end users actually rely on,...

Hearing the Whispers: Black-Box Membership Inference Attacks on Finetuned TTS Models

Text-to-Speech TTS foundation models are increasingly fine-tuned on private datasets to synthesize highly personalized voices, introducing severe privacy risks by exposing both biometric identities and sensitive speech content. Existing black-box membership inference attacks MIAs follow a two-sta...

JENGA: Exploiting Counter-Based RowHammer Countermeasures to Break Real-Time Predictability

Safety-critical real-time systems must satisfy multiple dependability requirements, notably time predictability and security. In such systems, tasks must complete within bounded and known execution times, typically characterised through Worst-Case Execution Time WCET analysis. At the same time,...

Ranked by the Matcher: A Reproducibility Audit of Knowledge Graph Extraction from Threat Reports

Security teams and researchers choose knowledge-graph extraction tooling for threat reports on the strength of published triple-F1 scores, yet those scores depend on how predicted triples are matched to gold annotations. We could reimplement the stated matching rule for only five of twelve...

Towards Behavior Tree-Guided Vulnerability Detection with Lightweight LLMs

Large Language Models LLMs are increasingly used for software vulnerability detection, but their performance depends on how source code is represented in the input. Most prompting approaches use source code in its original form, while some works propose the use of structured representations...

Effective Interventions against AI-Enhanced Scams

In 2025, scams were responsible for an estimated $442 billion in direct losses globally. In the United States, reported losses increased by nearly 400% between 2020 and 2025. Though AI in scamming is a relatively new phenomenon, its use significantly changes the economics of scams as well as the...

HiveTraceGuard-Pro: A Compact Generative Guardrail for Prompt Injection, Jailbreaks, and Adversarial Obfuscation

Production LLMs must handle inputs that attempt to override system instructions, bypass safety policies or elicit harmful responses. A common mitigation is a separate guardrail model. Existing reports, however, provide little evidence on Russian prompt injection or Russian surface obfuscation. We...

Smart Contracts Claimed Vulnerable by the CVE Database, with Labels and Source Locations

The Common Vulnerabilities and Exposures CVE database catalogs vulnerability claims in hard- and software, among them those pertaining to blockchain programs a.k.a. smart contracts. We present CVE-Smart-Contracts, a curated dataset of CVE records up to July 2026 referring to Ethereum smart...

Using LLMs to Elicit Security Requirements for Service-Oriented Cyber Ranges

Cyber ranges are complex environments comprising many interacting components and stakeholders with different security concerns. The Service-Oriented Cyber Range SOR is no exception, particularly when it comes to training scenarios targeting critical infrastructure. Security concerns are translate...

VPID: An Integrated Framework for Vulnerability Prioritization and Intrusion Detection in Enterprise Networks

Small enterprises face increasingly serious threats to their internal networks but often lack the financial resources, computing capacity, and specialist staff required to deploy resource intensive security platforms. This paper designs and implements VPID, a lightweight framework for vulnerabili...

Barriers to Using Static Application Security Testing (SAST) Tools: A Literature Review

Developers face a challenging problem with no clear solution. Modern software breaches can wreak havoc on businesses and individuals alike. With code vulnerabilities being a leading cause, securing applications must be a priority for developers. Static Application Security Testing SAST has the...

A SoK for SoCs: Reading the TI Leaves on AI for Cyber Threat Intelligence Generation and Sharing

Cyber Threat Intelligence CTI is essential for defending mission-critical infrastructure, yet the process of transforming raw attack evidence into shareable CTI remains fragmented and understudied. We conduct a literature survey of academic papers, organizing the CTI lifecycle into three stages:...

PhantomCall: Evading ML Malware Detectors Via Function Call Graph Perturbation

Prior adversarial attacks on Windows PE malware detectors target raw bytes, PE headers, or intra-function control-flow graphs, leaving the function call graph FCG unexplored as an attack surface. Yet the FCG structure is an important feature in graph-based malware detectors. We present Phan-...

Hidden Services Protocol for Mixnets

Mix networks mixnets provide network-level privacy by routing each communication packet through a sequence of intermediaries, called mixnodes, that randomly delay and cryptographically transform packets before forwarding them, making it difficult for observers to link mixnet entries to exits. Whi...

Safer Dependencies 0.6.1

safer-dependencies is a security layer for Claude Code: it sits between Claude and your manifest files and runs its security checks automatically: vulnerable installs are denied before they run, and a risky version written to a manifest is corrected on disk right after the write. It detects and...

Adversarial Vulnerabilities of Neural Biomarker Identification Systems

There is growing interest in the proposed use of EEG signals as biometric credentials, but thus far there has been little research on the reliability and security of such biometrics. Prior adversarial tests have focused on deep-learning classifiers and assumed attackers have full access to the...

AKRASIA: Stealthy Backdoor Attack on Reasoning-Based Code LLMs

We present AKRASIA, a stealthy, inference-time backdoor attack against reasoning-based Code LLMs. AKRASIA aims to achieve a backdoor target e.g., malicious code execution in reasoning LLMs while evading automated defenses and human inspection. To achieve this, AKRASIA probes the victim LLM to...

Libgcrypt 1.12.3

Libgcrypt is a general-purpose cryptographic library based on the code from GnuPG. It provides functions for all cryptographic building blocks: symmetric ciphers AES, DES, Blowfish, CAST5, Twofish, and Arcfour, hash algorithms MD4, MD5, RIPE-MD160, SHA-1, and TIGER-192, MACs HMAC for all hash...

Windows Time Provider Persistence

This Metasploit module establishes persistence by registering a malicious Time Provider DLL under HKLM\SYSTEM\CurrentControlSet\Services\W32Time\TimeProviders. When the W32Time service starts or restarts, the configured payload DLL is executed...

Dovecot Resource Consumption / Access Control

OX Dovecot has been patched to address uncontrolled resource consumption, use-after-free, out-of-bounds read, improper access control, and improper authentication vulnerabilities...

CISA: CISA Vulnerability Review Fiscal Years 2024 and 2025

The CISA Vulnerability Review provides organizations with critical insights into the root causes of insecure software and practical steps they can take to address these flaws to prevent exploitation. Analyzing CISA and open source data from fiscal years 2024 and 2025, the review establishes a...

Towards Operator-Empowered Vulnerability Hotfixing for 5G Radio Access Networks

Cellular protocol vulnerabilities can remain exploitable for months or years while standards bodies, vendors, and mobile network operators MNOs coordinate permanent fixes. We present Buckler, a framework that enables an MNO to deploy temporary, local, and reversible hotfixes in its radio access...

The Fragility of Jailbreak Robustness across Operational States

Existing jailbreak evaluations typically characterize robustness using a single attack success rate ASR measured in a default configuration the vanilla state. However, user-LLM interactions can induce diverse operational states beyond the vanilla state. In this work, we find that jailbreak...

Auditing Anonymous AI Models: A Four-Stage Protocol for Black-Box Identity Verification

The 2025--2026 AI market has seen a wave of stealth releases: frontier models launched anonymously on developer platforms under codenames. For their users, identity determines data-handling terms, supply-chain risk, and capability expectations. No validated methodology exists for black-box identi...

Boot Verification Program Persistence

This Metasploit module establishes persistence by configuring the BootVerificationProgram registry key. It uploads a payload executable and modifies the ImagePath value under HKLM\SYSTEM\CurrentControlSet\Control\BootVerificationProgram. The payload is executed by the Service Control Manager earl...

AIDE 0.19.4

AIDE Advanced Intrusion Detection Environment is a free replacement for Tripwiretm. It generates a database that can be used to check the integrity of files on server. It uses regular expressions for determining which files get added to the database. You can use several message digest algorithms ...

Denx U-Boot 2026.01-rc4 Integer Overflow

Denx U-Boot versions 2026.01-rc4 and below suffer from multiple integer overflow vulnerabilities...

Explainable Artificial Intelligence for Industrial Cybersecurity: A Review of Methods, Operational Integration, and Research Challenges

The increasing digitalization of industrial infrastructure and the convergence of information technology IT and operational technology OT have expanded the cyberattack surface of industrial systems. To address the growing complexity of cyber threats, artificial intelligence AI and machine learnin...

SoK: When Safe Agents Fail Together: The Security of Multi Agent LLM Systems

Safe agents can fail together. Multi-agent LLM systems MAS move information, state, decisions, and authority across principal boundaries, creating failures that local checks may miss. Without an execution-level view, a multi-agent setting can easily be mistaken for evidence of a genuinely...

Using Hyper-V Sockets for Real-Time Data Extraction from a Malware Analysis Sandbox

We present how Hyper-V sockets can be used as a real-time communication channel for a malware analysis sandbox. We show that, compared to WinSock TCP sockets, Hyper-V sockets are not subject to TCP/IP-layer blocking and are not enumerated by common TCP connection listing tools. We compare the...

NeuroGraph: An AI Graph-Driven Neuro-Symbolic Framework for Explainable Threat Reasoning in Advanced Manufacturing

The growing complexity of cyber-physical attack surfaces in advanced manufacturing has made cyber threat intelligence analysis increasingly difficult. Although large language models and retrieval-augmented generation have improved CTI workflows, text-based approaches remain vulnerable to...

Beyond the Payload: How User Invocation Shapes Coding Agent Vulnerability to Repository Poisoning

Coding agents are increasingly used for software engineering tasks, including bootstrapping projects from third-party repositories whose integrity cannot be assumed. Prior work on repository poisoning largely focuses on attacker-controlled injection and disguise, but developers also shape risk...

Hidden Threat in Synthetic Data: Covert Targeted Bias Injection through Benign Text

Synthetic data is increasingly used to train large language models LLMs, yet its security implications remain poorly understood. Prior work on subliminal learning suggests that models can inherit behavioral traits from seemingly unrelated training data. In this work, we investigate whether such...

ECLIPSE: Self-Evolving Stealthy Prompt Injection Attack against Long-Horizon Agentic Systems

Recently, large language model LLM agents, such as Codex, Claude Code, and OpenClaw, have become capable of planning and executing long-horizon tasks through repeated tool calls. This capability also creates new opportunities for prompt injection. Existing attacks either place the malicious...

EvoFlint: An Evolutionary Atlas of Multi-Turn LLM Vulnerabilities

Frontier language models that refuse harmful single-turn prompts often comply when the same intent is reached gradually over many turns, making multi-turn attacks one of the least understood failure modes of large language models. Most automated red-teaming methods treat this as a generation...

Same Request, Different Boundary: Evaluating Cybersecurity Assistance across Conversational Contexts

Large Language Models LLMs can solve complex problems, but their misuse in high-risk domains can lead to severe consequences. Model providers therefore restrict assistance for potentially harmful requests. Refusing all cybersecurity requests would therefore harm legitimate users. Providers need a...

Automating Static Code Analysis through CI/CD Pipeline Integration

In the contemporary landscape of software devel-opment, securing sensitive data is paramount to safeguarding organizational reputation, preventing financial losses, and pro-tecting individuals from identity theft. This paper addresses the pervasive challenge of identifying and rectifying security...

A Roadmap to Available ICS Datasets and Testbeds for Cybersecurity Research

Industrial Control Systems ICS are the backbone of many critical infrastructure sectors; however, their growing level of connectivity, long lifespan and integration with the Information Technology IT environment introduces numerous cybersecurity challenges. The merging of Operational Technology O...

HSMLog: Small Language Model-Assisted Hardware Security Module Log Anomaly Detection with Behavioral Analysis

Hardware Security Module HSM logs capture security-critical behavior, but anomalies emerge from relationships across event sequences, keys, object states, sessions, and temporal patterns rather than isolated events. Existing methods separate detection from HSM-specific evidence validation and...

Drishti: AI-Led Human-Directed Vulnerability Auditing for 5G Cores

Candidate generation for open-source vulnerabilities is no longer scarce. AI-assisted code review now produces defect candidates cheaply, and industry programs pair them with expert human triage. The remaining scarcity is validation and impact assessment, and the gap is largest in...

Foundation and Multimodal Large Language Models for Face Presentation and Morph Attack Detection

Face recognition systems are increasingly deployed in security-critical applications, yet they remain vulnerable to presentation and morph attacks. Presentation attack detection PAD and morphing attack detection MAD are therefore essential components of trustworthy face biometrics. Despite...

Building the Truman Show: A TrustZone-Based Framework for Lightweight Out-Of-Band Kernel Security Monitoring

The increasing number of vulnerabilities in operating systems, together with sophisticated kernel-level threats e.g., rootkits, has weakened the effectiveness of traditional in-kernel protection mechanisms. Since these defenses operate at the same privilege level as the kernel, they share the sam...

A Simple Transformer Pipeline for Full-Key Side-Channel Attacks on Uncropped Datasets

Deep learning-based side-channel analysis has historically focused on single-byte targets and manually cropped traces, which risks discarding exploitable leakage. While recent work has proposed specialized architectures and resampling techniques to address this gap, the literature lacks a simple...

SIR: Self-Improving Red-Teaming for Compute Use Agents

Computer use agents CUAs are vision-language models that perceive a screen and act on a real operating system through mouse, keyboard, and terminal, and they are increasingly deployed to automate everyday digital tasks. Because they can be exposed to untrusted content while operating, they are...

A Comprehensive Survey on Linguistic Steganography: Methods, Countermeasures, Evaluation, and Challenges

Linguistic steganography hides secret messages in natural language text. Large language models LLMs have reshaped the field, but a systematic account of how these scattered advances collectively reshape the field in this new era is still missing. We provide one along four axes: 148 steganographic...

Securing Cooperative Sensing in UAV Swarms against Conformity-Driven Byzantine Attacks

In integrated sensing and communication ISAC enabled 6G unmanned aerial vehicle UAV swarm networks, the widely adopted imitation-based conformity cooperation mechanism can be exploited by Byzantine attackers to fabricate false consensus, causing the effective error probability of normal UAVs to...

DisCTI: Who Needs to Know Timely? Automated Sector-Aware Cyber Threat Intelligence Dissemination

The timely dissemination of cyber threat intelligence CTI is critical for organizations to mount swift and effective incident response. When valid CTI is delivered to the right sector at the right time, identical attacks can often be contained or mitigated. However, today's rapidly expanding CTI...

BEACON: Behavior-Anchored Cross-Source Knowledge Graph Construction for Cyber Threat Intelligence

Cyber threat intelligence CTI is foundational to modern cyber defense, yet much of it resides in unstructured reports whose volume and heterogeneity far exceed manual analysis, motivating research on automatically constructing knowledge graphs from CTI reports. However, existing approaches mainly...