GNUnet P2P Framework 0.26.2

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...

OATH Toolkit 2.6.15

OATH Toolkit attempts to collect several tools that are useful when deploying technologies related to OATH, such as HOTP one-time passwords. It is a fork of the earlier HOTP Toolkit...

Active Directory Certificate Services CA Chase Configuration Checker

The Certighost NetExec SMB module checks Active Directory Certificate Services configuration for the EDITFATTRIBUTESUBJECTALTNAME2 chase flag associated with CVE-2026-54121...

Decepticon 1.4.4

Decepticon is an AI-powered autonomous red team framework designed to automate penetration testing and adversary simulation. It integrates AI agents with security tools to perform reconnaissance, vulnerability discovery, exploitation, and post-exploitation activities. The framework supports...

Joern 4.0.655

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...

The Secure Software Factory: A Reference Architecture

The Secure Software Factory: A Reference Architecture is a 26-page whitepaper outlining a security framework for AI-driven software development environments. It describes how organizations can safely deploy autonomous coding agents by enforcing four security boundaries: sandbox isolation, network...

NetX Duo 6.5.2.202603 Out-Of-Bounds Read

NetX Duo version 6.5.2.202603 and earlier contains an out-of-bounds read in the SNMP OID parser when processing multi-byte BER lengths...

simple-git 3.36.0 Command Execution

simple-git versions through version 3.36.0 contain a command execution issue that bypasses unsafe operation checks through abbreviated Git long options...

Nebula AI-Powered Penetration Testing 3.0.22

Nebula is an advanced, AI-powered penetration testing open-source tool that revolutionizes penetration testing by integrating state-of-the-art AI models into your command-line interface. Designed for cybersecurity professionals, ethical hackers, and developers, Nebula automates vulnerability...

AGCRE Regular Expression Library 20261013

AGCRE is a BSD-licensed regular expression library written in C that implements pattern compilation and matching using a Pike Virtual Machine architecture. It supports POSIX regular expressions, Perl-style escapes, lazy matching, non-capturing groups, backreferences, Unicode escapes, UTF-8, and...

Beyond Model Scaling: Rethinking Sequence Construction for Transformer-Based Network Intrusion Detection

Transformer-based network intrusion detection systems NIDS have shown strong potential for detecting multi-stage cyberattacks, yet most methods construct input sequences using fixed temporalization schemes rather than treating sequence construction as a systems design decision. In flow-based...

Impact of Security Modeling Fidelity on Hyperscale Data Center Hosting Capacity Assessment

This paper assesses hyperscale data center hosting capacity in transmission grids. Hosting capacity HC analysis quantifies the maximum additional load a bus can accommodate without violating operational constraints. This paper defines data center HC as the maximum time-invariant active power dema...

NetCoFi: A Budget-Aware Coarse-Fine Dual-Branch Model for Encrypted Traffic Classification

Encrypted traffic classification is critical for network management and security, but practical deployment must balance classification accuracy and inference cost. Existing models typically process fixed flow windows with limited control over computation after training, which can limit the...

Mobile App Analysis in the New Era: Challenges and the Road Ahead

Mobile applications apps have grown into complex, multi-platform systems that support diverse services and operate within varying regulatory and distribution contexts. Traditional analysis techniques have established a strong foundation for ensuring quality, security, and compliance, but face...

Same Attack, Different Judge: A First Controlled Adversarial Comparison of Jev, LLM Judges, and Purpose-Built Safety Classifiers

TypeSafe AI's Jev is a new kind of safety judge. It generates no text and no label: it answers questions the developer defines in advance and returns a probability for each answer. The vendor admits that adversarial input can change these answers but gives no numbers. In this paper, we present th...

X.Js: A Live Benchmark for Node.Js Taint-Style Vulnerabilities

JavaScript vulnerabilities in npm packages pose a significant risk to the Node.js ecosystem, and a growing body of work aims to detect, exploit, and mitigate them. Studying and evaluating this work requires up-to-date collections of real vulnerabilities, yet the most commonly used datasets stop...

HULK: An Efficient Algorithm for Enabling Fast Bulk Bitwise Operations on Homomorphically Encrypted Data

A wide range of important cloud applications, e.g., database analytics, graph analytics, and genome analysis, spend a considerable amount of time performing bulk bitwise operations e.g., AND, OR, XOR. These applications often operate on highly sensitive data, making data privacy a critical concer...

Concealed Handgun Detection Using WiFi Signals

While conventional camera-based surveillance systems and metal detectors can provide a sufficient level of security when used appropriately, they have fundamental limitations that reduce their applicability. Camera-based systems are unable to detect occluded or concealed threats and metal detecto...

Nudge the Judge: Uncovering Program Decision Hijacking in Real-World Jev Applications

System One models such as Jev change how software makes decisions by mapping open-ended semantic contexts into structured judgments that directly drive program execution. However, this paradigm introduces a new security risk, which we term Jev Program Decision Hijacking JPDH: attacker-controlled...

Autonomous Cyber Operations Gym for Training and Evaluating AI Models for Defence

This paper proposes an Autonomous Cyber Operations ACO gym, a unified framework integrating high-fidelity network emulation, realistic user behaviour modelling for benign network traffic and adversarial profiles, and the generation of cybersecurity scenarios through open toolkits. By supporting...

Dynamic Attack Surfaces: A Queue of Branching Processes

Modern attack surfaces are inherently dynamic. Vulnerabilities emerge over time and they remain exposed to exploit until defenders discover and patch them. Artificial intelligence AI amplifies these dynamics by accelerating both offensive and defensive processes, making modern cybersecurity...

AegisAsync: Symbolic Async-Event Simulation for Risks in Python Asynchronous Programs

Security and robustness risks in Python async programs depend on event order, object identity, and execution after exceptions or cancellation. Detecting these risks requires connecting related operations across function calls and tracking their effects along execution paths. We present AegisAsync...

ProtoArena: Can AI Agents Discover and Exploit Real-World Cross-Component Protocol Vulnerabilities?

Large language model LLM agents are increasingly used for vulnerability analysis, yet existing benchmarks provide limited coverage of exploitation that depends on interactions among network protocol components. Such vulnerabilities arise from inconsistencies in message interpretation, timing,...

CompanionSafe: From Multi-Turn Safety Evaluation to Guardrails for AI Companions

AI companions provide users with emotional support and ongoing companionship, but their sustained relational interactions also introduce distinct safety risks. Prior work largely targets general harms or specific companion platforms and risk categories, while relying on manually collected...

SkillScreen: High-Recall Screening of Malicious Agent Skills with Decision Models

Agent skills turn natural-language instructions into actions, creating a security challenge: legitimate automation and malicious behaviour can look deceptively similar. A practical screen must catch nearly every attack while keeping the review load manageable. We present SkillScreen, a compact...

Tanchun: Robust Flow-Based HTTP(S) DDoS Detection Via Behavioral Attribute Guidance

HTTPS DDoS attacks have surged in frequency and scale, posing a significant threat to network security. Flow-based detection is a promising solution for large-scale HTTPS DDoS detection due to its decryption-free operation and scalability. However, the coarse-grained numerical statistics in flow...

Encrypted Skills Can Become New Security Exploits If AI Agents Know How to Decipher

Third-party skills can expose LLM agents to malicious instructions hidden by encoding. We introduce Ciphered Skill Injection CSI, which embeds such instructions in skill files for agents to decode and follow. We evaluate Caesar and layered variants across eight models and 139 injection-task pairs...

Rethinking Quality in Large Language Model Routing: Security-Conditioned Model-And-Budget Selection

Large language model LLM routers reduce serving cost by choosing which model to call and how many output tokens to grant it for each query. Existing routers rank model-budget actions using a single quality metric. This does not work for mixed workloads. For ordinary queries, a good answer is...

Provenance and Authorization in Autobiographical Language Models

Autobiographical language models may draw on archives containing observations, quotations, emotional reports, and earlier model outputs. Cryptographic authentication can preserve an archive while leaving these sources semantically conflated. We formulate this gap as a computer-security problem:...

MikroTik RouterOS Before 7.24 Integer Underflow

MikroTik RouterOS versions before 7.24 contain a pre-authentication integer underflow in HTTP request body handling that can cause a web management service denial of service and may allow code execution...

GRAudit Grep Auditing Tool 4.1

Graudit is a simple script and signature sets that allows you to find potential security flaws in source code using the GNU utility, grep. It's comparable to other static analysis applications like RATS, SWAAT, and flaw-finder while keeping the technical requirements to a minimum and being very...

OpenSCAP Libraries 1.4.5

The openscap project is a set of open source libraries that support the SCAP Security Content Automation Protocol set of standards from NIST. It supports CPE, CCE, CVE, CVSS, OVAL, and XCCDF...

GitLab CE/EE 19.4.1 CI/CD Regular Expression Compiler Remote Code Execution

GitLab CE/EE versions 19.2 before 19.2.8, 19.3 before 19.3.5, and 19.4 before 19.4.2 contain an integer overflow and insufficient regular expression validation issue that may allow unauthenticated arbitrary code execution through a specially crafted CI/CD configuration...

Decepticon 1.4.0

Decepticon is an AI-powered autonomous red team framework designed to automate penetration testing and adversary simulation. It integrates AI agents with security tools to perform reconnaissance, vulnerability discovery, exploitation, and post-exploitation activities. The framework supports...

Joern 4.0.654

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...

Kairos: Transactional Security Enforcement at the System Boundary for LLM Agents

Large language model LLM agents are becoming an integral part of the software development lifecycle, and the capabilities granted to them allow an agent to act with the user's authority on any resource it can access. The reach that gives an agent its utility is equally available to an attacker wh...

Bytes to Threats: Byte-Sequence Transformer for Malware Detection

Existing malware detection approaches heavily rely on handcrafted features derived from static or dynamic analysis of the executable files. These methods require specialized domain expertise, dedicated analysis tools, and time-consuming analysis, which limits their scalability and robustness in t...

FedGraph: Defending Federated Large Language Model Fine-Tuning against Backdoor Attacks Via Graph-Based Aggregation

Federated fine-tuning of large language models LLMs allows multiple clients to collaboratively adapt models without sharing raw data, offering strong privacy benefits. However, this setting is highly vulnerable to backdoor attacks, in which malicious clients manipulate their updates to induce...

Jev-Guard: Fast Routing and Auditing Agent Actions over Editable Policy Trees

Agent harnesses require a low-latency guardrail model together with customizable audit policies. However, deploying an auto-regressive guardrail model remains challenging: such models incur high inference latency and are often poorly aligned with customized policies. To address these problems, we...

Nebula AI-Powered Penetration Testing 3.0.8

Nebula is an advanced, AI-powered penetration testing open-source tool that revolutionizes penetration testing by integrating state-of-the-art AI models into your command-line interface. Designed for cybersecurity professionals, ethical hackers, and developers, Nebula automates vulnerability...

ML-Assisted Power Side-Channel Attacks on ML Accelerators in Shared FPGAs

Cloud providers offer on-demand access to Field-Programmable Gate Arrays FPGAs, and multi-tenant FPGAs let multiple users share one device to improve utilization. This sharing introduces security risks: an adversary co-located with a victim on the same FPGA can mount power side-channel attacks...

COMPASS: Membership Inference Attack against Vision Large Language Models Via Adaptive Noise Calibration

Vision large language models VLLMs are deployed in privacy-sensitive domains, raising training-data exposure concerns. Existing gray-box membership inference attacks MIAs commonly rely on entropy statistics or generated descriptions, requiring costly generation with limited membership separation...

Metasurface Quantum Graphs for Polarization-Independent Certified Randomness

Quantum random number generators are crucial for information security, yet existing implementations are hindered by bulky optics, device imperfections, and state alignment constraints. Here, using a compact metasurface platform, we achieve polarization-independent certified randomness by...

The Right to Be Forgotten under Correlation: Privacy-Utility Tradeoffs

We study privacy-preserving algorithms that redact information from a correlated dataset. The goal is to reduce the information leakage about sensitive parts. We analytically characterize the optimal tradeoff between privacy leakage through correlation and utility number of redactions for local...

Doctor Trigger: A Framework for Release-Bound Face Verification

Face swapping and generative editing enable realistic facial manipulation, while online redistribution complicates publisher oversight of circulating face images. Existing approaches establish provenance, detect manipulation, recover embedded watermarks, verify image integrity, or disrupt...

Enhanced Detective: A Dual-Stage Proactive Defense against Internal Poisoning Attacks in Financial Fraud Detection Using Federated Learning

With recent developments in Artificial Intelligence AI, the adoption of distributed learning paradigms such as Federated Learning FL has emerged. In simple terms, FL enables multiple entities to collaboratively train AI models without sharing local data. The FL paradigm is particularly valuable i...

Toward Realistic Privacy Risk in FL-Enabled OT Intrusion Detection Systems

In Operational Technology OT environments, Federated Learning FL is increasingly adopted to train Intrusion Detection Systems IDSs without sharing raw operational data across facilities. However, model updates may still leak sensitive information about industrial processes, creating privacy risks...

VulnBump: A Benchmark for Fixing Vulnerable Dependencies in Real Projects While Keeping the Build and Tests Green

Software composition analysis SCA tools report far more vulnerable dependencies than teams fix: in Snyk Open Source production data, 94% of vulnerability findings have a known fixed version, yet only about 10% are resolved. Agentic coding tools could close this gap, but no benchmark evaluates the...

Purpose IR: Compiling User Purpose for Privacy-Preserving Agent Workflow State

LLM-agent workflows routinely transform rich observations into plans, summaries, memories, handoffs, and other reusable state. This creates a privacy boundary that task relevance alone does not capture: an observation may be needed as evidence for a task without its full semantics being authorize...

TRAP: Tree-Guided Reinforcement-Augmented Probing for Automated LLM Jailbreaking

Aligned large language models LLMs remain vulnerable to jailbreak prompts that circumvent their safety guardrails, making the identification of these vulnerabilities important for understanding and mitigating model weaknesses. Existing automated jailbreak methods explore prompt candidates or reus...