OpenSSH 10.5p1

OpenSSH is the premier connectivity tool for remote login with the SSH protocol. It encrypts all traffic to eliminate eavesdropping, connection hijacking, and other attacks. In addition, OpenSSH provides a large suite of secure tunneling capabilities, several authentication methods, and...

When Agents Talk: Honeytokens under Shared Memory

During a 2026 cyber-capability evaluation, short-lived AI agents turned a shared package repository into persistent memory, passing exploit findings to later agents and rebuilding the channel after it was removed. The broader evaluation culminated in an intrusion into Hugging Face. This episode...

Benchmarking Cyberattack Detection in Electric Vehicle Charging Infrastructure with Benign User Updates

Cyberattack detection in electric vehicle charging infrastructure is complicated by legitimate post-activation revisions to requested energy and departure time. Charging manipulation attacks can exploit the same interface and variables; therefore, detecting a request change alone does not establi...

Security Tests As Executable Specifications for LLM Code Generation: Benefits, Trade-Offs, and Coverage Limits

Large language models LLMs can generate functionally useful code that remains vulnerable, while security-focused interventions may break intended behavior. We investigate security tests as executable specifications both before generation and during iterative repair. We develop SecTDD, a controlle...

Beyond Detection Accuracy: Measuring Explanation Cost, Stability, and Utility for Resource-Aware IoT Intrusion Detection

Machine-learning intrusion-detection studies commonly emphasize predictive accuracy while treating explanation generation as a computationally free post-processing step. This study jointly evaluates predictive effectiveness, explanation cost, local explanation stability, and selective explanation...

Governing the KV Cache: Preventing Timing Side-Channel Leakage in Multi-Tenant LLM Inference

The key-value KV cache is the primary throughput optimization in modern large language model LLM inference, enabling prefix reuse across requests. In multi-tenant deployments this cache is shared across tenants, creating a timing side channel: an adversarial tenant can reconstruct another tenant'...

Intelligent Wiretap Code Design: Exploiting Wireless Endogenous Security Via Information Theory and Deep Learning Integration

Recent advancements in wireless endogenous security have explored leveraging the inherent randomness of wireless channels to enhance communication security, providing an effective alternative to traditional encryption methods. This paper proposes a wiretap coding scheme within the semantic...

Generative AI for Encrypted Traffic Analysis: Synthetic Dataset Generation and Classifier Evaluation

Network traffic analysis faces significant challenges with encrypted communications, primarily due to limited visibility into packet contents and the inherent imbalance in available datasets, particularly for anomalous traffic patterns. This paper addresses these challenges by exploring Generativ...

Nimux 1.0.5

Nimux is a native command surface for authorized security assessments. It combines network enumeration, credential validation, Active Directory operations, Kerberos workflows, remote execution, file movement, secrets collection, DCSync, GPO operations, database clients, and SOCKS routing into one...

Memoir: Learning, Verifying, and Evolving False-Positive Memories for Static Application Security Testing Tools

Static Application Security Testing SAST tools have become indispensable in modern secure software devel- opment. However, these tools often generate false-positive FP alerts, imposing substantial manual inspection costs and reducing the trust from developers. Existing FP reduction methods still...

Measuring the Wrong Thing: Internal Harmfulness Scores Anti-Rank Successful Jailbreaks

Internal safety scores judge a prompt before any text is generated, and they are validated by how well they separate harmful prompts from benign ones. That separation is then read as evidence that the score will also catch the attacks that succeed. Harmful intent is a property of the prompt...

Generating Attacks for LLMs with GFlowNets

The rapid advancement of Large Language Models LLMs has facilitated their ubiquitous integration into various domains, leading to widespread adoption. However, this escalating trend has introduced significant security vulnerabilities, necessitating the identification and mitigation of flaws arisi...

Nuclei 3.11.1

Nuclei is a modern, high-performance vulnerability scanner that leverages simple YAML-based templates. It empowers you to design custom vulnerability detection scenarios that mimic real-world conditions, leading to zero false positives...

You Are Not My Teammate: Behavioral Fingerprint-Based Detection of Suspicious Account Misuse

Online games have been continuously affected by cyber threats such as game bots and gold farming. Game bots, which are automated programs that play on behalf of human users, significantly accelerate character progression and reduce the engagement of legitimate players, potentially leading to user...

STAIR: Effective Incident Response Using an End-To-End Agentic Planning Framework

Incident response planning is critical for restoring compromised software systems after cyberattacks. Common practice relies on expert-driven playbooks that encode fixed response procedures, but these static workflows struggle to adapt to evolving incident states, changing recovery objectives, an...

A Bird'S-Eye View on Security Considerations in RFCs

Request for comments RFCs are Internet standards, memorandums, and related technical documents about core Internet protocols made via and released by the Internet Engineering Task Force IETF. In the early 1990s each RFC was required to have a section for security considerations. The present work...

Conversational Versus Dashboard Explainable AI for UAV Intrusion Detection: An Empirical Study of Operator Trust and Reliance

Machine learning-based Intrusion Detection Systems IDS have demonstrated superior performance in securing Unmanned Aerial Vehicle UAV networks. However, the 'black-box' nature of these models, combined with the high dimensionality of multimodal cyber-physical data, poses significant...

Never Stop Speaking: A Denial-Of-Service Attack on End-To-End Speech Language Models

Many studies have shown that specially crafted inputs can induce large language models LLMs to generate excessively long outputs, resulting in significant computational overhead and resource consumption. While most existing denial-of-service DoS attacks target text-only LLMs, end-to-end E2E speec...

Joern 4.0.600

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...

From Prompt Injection to Web Exploitation: Revisiting Classic Vulnerabilities in LLM-Integrated Applications

Large Language Models are increasingly integrated into web applications through chatbots, tool-calling pipelines, and agentic workflows. In these systems, user input may influence not only generated text, but also backend actions such as database queries, HTTP requests, file operations, template...

Stealing Reasoning Traces from Proprietary LLM APIs

Leading large language model providers now conceal their models' step-by-step reasoning, or chain-of-thought, to protect intellectual property and limit information leakage. Rather than storing these traces server-side, providers return them to the client as blocks of encrypted text, which the...

Pass-The-Passkey Family of Attacks

Research on passkey security uncovered three practically exploitable zero-day vulnerabilities in Windows 11 and Microsoft Entra ID. Two of them form a replay chain: Windows writes complete WebAuthn assertions to the event log for device-bound and hybrid authenticators, while Microsoft Entra ID...

ColluSkill: Adversarial Cross-Skill Composition for Evading Agent Skill Scanners

Agent skills are emerging as an important attack surface in LLM-based agent systems. Through an empirical study of existing skill scanners, we find that current defenses mainly inspect individual skills, leaving risks from cross-skill composition insufficiently examined. This creates a practical...

Diversity Matters: Distributional Feature Coverage Sample Selection for Data-Efficient Backdoor Attacks

Backdoor attacks compromise training data so that a model retains clean accuracy but predicts an attacker-chosen target on triggered inputs. At very low poisoning rates, only a few samples convey the trigger--target association, making poison-sample selection critical. Existing methods typically...

From Noise to Meaning: Meaningful Secret Sharing with Tamper Detection for Facial Recognition

Popularity of AI-based face recognition system directly demands protection of sensitive biometric data used for training. Visual secret sharing is an interesting idea, as it splits facial images into secret shares that look random and spread across many institutions. However, these shares look li...

Security and Privacy Taxonomy Generation from Mobile App Reviews

Mobile app reviews are a rich, continuously renewing source of how users experience privacy and security, yet existing taxonomies of these concerns are hand-crafted and cannot keep pace with the evolving nature of the data. Automating taxonomy construction is the natural response, but scalability...

A Combined Feature-Based Framework for Disguise and Spoofing Detection in Face Recognition Systems

Face recognition systems face two distinct, commonly-separated failure modes: spoofing, where an impostor presents a photograph or video of an authorized user, and disguise, where a legitimate user is rejected because their appearance differs from their enrolled template due to accessories, facia...

Not an A11y: How Android Accessibility Exposes Mobile AI Agents to Indirect Prompt Injection

The rise of autonomous AI agents represents a major paradigm shift in how users interact with mobile devices. Frameworks such as MobileRun and Mobile-Use can autonomously navigate Android applications and execute complex multi-step tasks. To interpret user interfaces, these frameworks rely...

SLAC: Access-Driven CPU-To-GPU Side-Channel Attacks Via System-Level Cache on Apple Silicon

Modern heterogeneous System-on-Chip designs integrate CPU cores and a GPU that share a last-level cache LLC or system-level cache SLC. This sharing exposes a new cross-domain attack surface, and existing attacks on integrated platforms either exploit coarse-grained cache-occupancy contention or...

Telemetry and Concealment in Self-Adapting Generative AI: Logging Architecture, Adversarial Model Hiding, and the Limits of Detection

Model risk management MRM guidance assumes a static model lifecycle, in which models are developed, independently validated, and implemented without further autonomous modification. Continually self-adapting generative AI systems --- models that update their own weights during production deployme...

Repeated-Game Security for Restaking-Based Verifiable Inference

Restaking-based protocols enable verifiable LLM inference without the high proving cost of zkML or the hardware trust assumptions of TEEs. Their security is commonly justified by a one-round slashing condition: a rational provider should not cheat when the expected penalty exceeds the cost saving...

SSHafe: A Real-Time SSH Brute Force Attack Detection and Novel Credential Rotation Standard

SSH remains a critical yet heavily targeted protocol for remote system administration, with password-based authentication exposing servers to large-scale brute-force, dictionary, and credential-spray attacks. Existing rule-based defences such as Fail2Ban fail to detect slow, distributed, or...

Understanding Security and Privacy Perceptions of Content Creators Regarding AI Labels of AI-Generated Content

AI labels, typically implemented via underlying tracing mechanisms such as watermarks and metadata, are crucial for protecting Artificial Intelligence-Generated Content AIGC against security threats like disinformation and evasion. However, the perceived devaluation of AI-assisted work discourage...

BASIS: Breach-Aware Selective Prompt Injection Shielding with Prefill Attention Probes

Prompt injection is a critical security threat in large language model LLM applications, where attackers hijack model behavior by embedding malicious instructions in user or external data. Existing detection methods only detect the presence of injection and refuse to respond upon detection,...

Compositional Threat Analysis of Latent Compromise in LLM Agent Systems: The Order 66 Scenario

In the fictional Order 66, catastrophe does not arise from a powerful command alone: a trusted population is preconditioned, a short directive activates the concealed condition, and protective authority turns against the system. This paper translates that mechanism into an origin-neutral security...

What Keeps Agent Skills from Being Reusable? Evidence from 138K SKILL.Md Files

Under the current standard, Agent Skills are SKILL.md files that combine instructions with supporting resources, enabling Large Language Model LLM agents to reuse procedures beyond a single conversation. Yet many public skills appear to originate from a single task, repository, or conversation,...

Defending Retrieval-Augmented Intrusion Detection against Knowledge Poisoning and Prompt Injection

Retrieval-Augmented Generation RAG enables large language models to classify network flows and generate human-readable incident reports by retrieving semantically similar historical traffic from a vector knowledge base. However, the retrieval layer introduces vulnerabilities to knowledge poisonin...

A Blueprint for Collaborative Cybersecurity Operations Centres with Capacity for Shared Situational Awareness, Coordinated Response, and Joint Preparedness

With digital technologies now being part of the fabric of our societies, identifying and managing cybersecurity threats becomes imperative. Within the European Union, several initiatives are underway, aiming to motivate, regulate and eventually orchestrate the establishment of capacity and...

Tracking-Assisted Robust Secure Transmission against a Mobile Eavesdropper in Cell-Free ISAC Networks

In this paper, we propose a tracking-assisted robust secure transmission framework for cell-free integrated sensing and communication ISAC networks that exploits distributed multistatic sensing to recursively track a mobile eavesdropper and quantify the associated position uncertainty. Since robu...

TONTOU: On the Exploitability of Time-of-Neutralization to Time-of-Use Windows

Recently deployed Spectre v2 mitigations neutralize branch predictor state when switching privilege contexts or immediately prior to indirect branch execution, either through domain isolation or sanitization. These defenses assume that subsequent branch predictor behavior remains free from attack...

On a General Theoretical Framework for Radio Frequency Fingerprint-Based Authentication

While radio frequency fingerprint RFF-based wireless device authentication has been widely studied across different datasets and scenarios, there still lacks a fundamental theory to explain why and how RFF can serve as a reliable device identity, significantly hindering the practical application ...

Apple Security Advisory 07-27-2026-2

Apple Security Advisory 07-27-2026-2 - macOS Tahoe 26.6 addresses buffer overflow, bypass, code execution, denial of service, heap corruption, information leakage, integer overflow, out of bounds access, out of bounds read, out of bounds write, spoofing, traversal, and use-after-free...

Apple Security Advisory 07-27-2026-4

Apple Security Advisory 07-27-2026-4 - macOS Sonoma 14.8.8 addresses buffer overflow, bypass, code execution, denial of service, double free, heap corruption, information leakage, integer overflow, out of bounds read, out of bounds write, traversal, and use-after-free vulnerabilities...

Dual-Node NVIDIA DGX Spark over Tailscale: A Remote-Access Testbed for Distributed LLM Training and Cyber-Threat-Intelligence Fine-Tuning

Compact AI systems make local language-model experimentation increasingly accessible, yet practical evidence for multi-node training on desktop-class accelerators remains limited. This report presents a proof-of-concept deployment of distributed NanoChat pretraining across two NVIDIA DGX Spark...

The DCHECK Illusion: Chrome's Trusted Path Policy Creates Vulnerabilities

An analysis of Chrome Mojo IPC finding 296 DCHECK instances across mojo/core/ and mojo/public/cpp/bindings/lib/, at least 15 guarding security-relevant conditions bounds checks, offset validation, handle state with ZERO protection in release builds...

The Anatomy of a Prompt Injection: A Component Model for Structured Analysis

Four years after prompt injection was first identified in 2022, attacks are still predominantly documented as verbatim strings rather than structured exploits, despite advancing agent capabilities and threat actors embedding injections to subvert AI-assisted security analysis. This paper formaliz...

Clam AntiVirus Toolkit 1.5.4

Clam AntiVirus is an anti-virus toolkit for Unix. The main purpose of this software is the integration with mail servers attachment scanning. The package provides a flexible and scalable multi-threaded daemon, a command-line scanner, and a tool for automatic updating via Internet. The programs ar...

Cisco Catalyst 8000V Heap Buffer Overflow

An authenticated heap buffer overflow in Cisco Catalyst 8000V sd-wan allows an attacker with low privileges to corrupt process memory and achieve remote code execution...

China RealDID: Verifiable Credentials Anchored in Legal Identity

Verifiable credentials VCs and decentralized identifiers DIDs enable selective disclosure but lack legal anchoring: without a trusted identity root, verifiers cannot distinguish a genuine holder from a fabricated identity. State identity systems provide biometric-grounded verification but impose...

Apple Security Advisory 07-27-2026-1

Apple Security Advisory 07-27-2026-1 - iOS 26.6 and iPadOS 26.6 addresses buffer overflow, bypass, code execution, heap corruption, information leakage, integer overflow, out of bounds access, out of bounds read, out of bounds write, spoofing, and use-after-free vulnerabilities...