Flounder 0.1.0

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...

Do (Not) Tell Me about My Insecurities: Assessing the Status Quo of Coordinated Vulnerability Disclosure in Germany Amid New EU Cybersecurity Regulations

In our increasingly interconnected world, good IT security practices are necessary to prevent vulnerabilities and data breaches. Providing security contacts, e.g., via Coordinated Vulnerability Disclosure CVD programs or security.txt files, is an important practice for businesses to facilitate...

Joern 4.0.564

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...

angr 9.2.222

angr is an open-source binary analysis platform for Python. It combines both static and dynamic symbolic "concolic" analysis, providing tools to solve a variety of tasks...

Helpful or Harmful? Evaluating LLM-Assisted Vulnerability Patching Via a Human Study

Software vulnerability remediation is a cognitively demanding task that requires specialized security expertise often lacking in general developers. In the meantime, Large Language Models LLMs assisted tools show potential in vulnerability detection, location, and repair tasks. Hypothesis: While...

Information Flow Security on Persistent Memory

Persistent memory is a recently proposed memory paradigm that delivers many system-wide benefits, including improved runtime efficiency and the ability of programs to recover from power outages and system crashes. While recent research has investigated techniques for proving functional correctnes...

NTForge Vulnerability Research / Exploit Reproduction Template

NTForge is a Windows 10/11 C++17 vulnerability-research and exploit-reproduction template intended for authorized testing and coordinated reporting to the Microsoft Security Response Center MSRC. It provides a documented native API resolver, internal structure references, safe memory primitives,...

Reinforcement Learning for Software Vulnerability Analysis: A Systematic Review with Emphasis on C/C++ Source Code and Static Analysis

Vulnerability detection in C/C++ software remains a major security challenge due to code complexity, manual memory management, and the limitations of traditional static analysis. Reinforcement Learning RL has emerged as a promising approach, particularly for fuzzing, test generation, program...

Malware Distribution Via Browser-in-the-Browser Kit

Unit42 From Palo Alto Networks has discovered a Browser-in-the-Browser BitB campaign specifically tailored for malware delivery...

Burnyard: Future of Malware Analysis

Malware analysis is a critical aspect of modern cybersecurity. The prevailing industry practice, sandboxing, involves executing suspicious binaries within isolated virtual machines in large-scale data centers. However, this approach can unintentionally expose samples to public platforms such as...

Red-Teaming the Agentic Red-Team

The use of agentic systems to perform offensive security operations has moved from a theoretical possibility to a commoditized capability. However, while the community has focused on creating more and more capable agents, less attention has been allocated to assessing the security of those system...

HelpBench: Assessing the Ability of LLMs to Provide Privacy, Safety, and Security Advice

This paper introduces HelpBench, a benchmark for assessing whether LLMs are capable of providing accurate help in response to questions about digital privacy, safety, and security. We curated 450 questions representing authentic user situations and developed rubrics for each question to evaluate...

Poisoned Playbooks: Demystifying Knowledge Poisoning Effects on AI Security Agents

AI security agents increasingly rely on Retrieval-Augmented Generation RAG to use external security knowledge for vulnerability analysis and exploit reasoning. This creates a new risk: poisoned write-ups can be operationalized into incorrect exploit behavior. Yet, prior work on RAG poisoning has...

Representation Matters: An Empirical Study of Program Representations for LLM Vulnerability Reasoning

Large Language Models LLMs are increasingly used for automated vulnerability detection, but it remains unclear how program structure and semantics should be represented for LLM-based reasoning. Most prompting-based approaches provide raw source code, implicitly assuming that more source-level...

Poster: Exploring the Limits of Audio-Based Detection of Turkish Phone Call Scams

Scam phone calls exploit vulnerable communities worldwide, yet research on detection has focused almost exclusively on English and other high-resource languages. In low-resource settings such as Turkish, detection is especially difficult, as annotated data is scarce and technological defenses...

Inside Crypter-As-A-Service: An Ecosystem Analysis of the Exploit.In Underground Forum Research Talks

Crypter-as-a-Service CraaS has become a key enabling layer of the contemporary malware economy by providing on-demand evasion capabilities through underground service markets. In this paper, we present a longitudinal characterization of the CraaS ecosystem on exploit.in, a major Russian-language...

Decoupling Reconnaissance and Exploitation: Measuring the Capability Boundaries of LLM-Based Web Penetration Testing

Large Language Models LLMs have shown promise for automated penetration testing, yet existing end-to-end black-box evaluations are highly susceptible to error cascading: failures in early reconnaissance can mask an agent's actual ability to exploit vulnerabilities. To more accurately characterize...

A Hybrid CNN-LSTM Intrusion Detection Framework for Cybersecurity in Smart Renewable Energy Grids

The accelerated digitalization of renewable energy smart grids through IoT sensors, AMI, and SCADA systems has significantly expanded the attack surface for sophisticated cyberattacks, FDI attacks that stealthily distort state estimation and DoS/DDoS attacks that flood communication channels...

PowerFuzz: Power-Based Black-Box Firmware Fuzzing

Fuzzing is widely used for software and hardware verification, offering an effective alternative to random testing. While gray-box fuzzers benefit from full visibility into the system under test and can leverage execution feedback such as branch coverage, these approaches are not applicable when...

Deep-Research Agents Can Be Poisoned Via User-Generated Content

Deep-research agents, i.e., systems that rely on multi-agent pipelines to iteratively retrieve, synthesize, and cite Web content in order to produce structured reports, are rapidly replacing traditional search for both routine and complex information needs. These agents issue many related queries...

CITADEL: CSI-Based Jamming Detection and Open-Set Classification for IIoT Networks

Radio frequency jamming poses a critical threat to the availability of wireless Industrial Internet of Things IIoT networks. Existing detection and classification techniques are poorly suited to this setting: coarse signal-strength and cross-layer features lack information richness, while raw I/Q...

A Hybrid Intrusion Detection System for Electric Vehicle Charging Infrastructure

The integration of Electric Vehicle Charging Stations EVCSs into the smart grid necessitates sophisticated digital infrastructure for their management and coordination, which expands the attack surface and makes both the power grid and EVCSs vulnerable to cyberattacks. This research addresses...

Detecting Malicious Agent Skills in the Wild Using Attention

LLM agents increasingly load skills, file-based packages of natural-language instructions written by third parties and distributed through marketplaces, that execute with the user's privileges. A single malicious skill can exfiltrate data, hijack the agent, or persist as a supply-chain foothold,...

CVE MCP Server 0.2.0

CVE MCP Server is a production-grade Model Context Protocol MCP server that turns Claude into a full-spectrum security analyst. Instead of juggling 15+ browser tabs across NVD, EPSS, CISA KEV, Shodan, VirusTotal, and GreyNoise, ask Claude one question and get correlated intelligence in seconds...

WPProbe Plugin Enumeration Tool 0.12.1

A fast WordPress plugin and theme scanner that detects installed plugins via REST API enumeration and themes from HTML discovery, then maps them to known vulnerabilities. Over 5,000 plugins detectable without brute-force, thousands more with it...

RIFT-Bench: Dynamic Red-Teaming for Agentic AI Systems

Agentic AI systems powered by large language models LLMs are rapidly evolving into autonomous decision-making systems, exposing attack vectors beyond those of traditional LLM vulnerabilities. Existing security evaluations are often tied to specific implementations or domains, limiting unified...

Apple Security Advisory 06-16-2026-1

Apple Security Advisory 06-16-2026-1 - Beats Firmware Update 1B211 addresses an eavesdropping vulnerability...

AI Toolchain Hijacked: IDE Plugin API Key Theft

Whitepaper called AI Toolchain Hijacked: IDE Plugin API Key Theft. The proliferation of AI-assisted development tools has substantially changed how developers configure and manage credentials in their working environment. Where a developer's IDE once contained little more than syntax highlighting...

AutoPRAC: Automating Attack Discovery for PRAC-Based Rowhammer Defenses Using Model Checkers

Per-Row Activation Counting PRAC in DDR5 is a specification to mitigate Rowhammer attacks by tracking activations per row and triggering mitigative refreshes when needed. However, the security of PRAC designs is currently evaluated using human-crafted attack patterns and we lack formal verificati...

Rising from the Ashes: How Agentic AI Is Unblocking Challenges in Cybersecurity

Security remains a high-cost challenge, with many problems historically deemed inefficient to address or effectively unsolvable. A significant number of these problems stem from labor-intensive tasks that create bottlenecks in defensive approaches. Agentic AI has the potential to alleviate these...

Maestro 0.17.1

Maestro is a cross-platform desktop app for orchestrating your fleet of AI agents and projects. It's a high-velocity solution for hackers who are juggling multiple projects in parallel. Designed for power users who live on the keyboard and rarely touch the mouse. Collaborate with AI to create...

PixJail: Self-Evolving Paper-To-Pipeline Reproduction for Text-To-Image Jailbreak Evaluation

As Text-to-Image T2I jailbreak techniques evolve rapidly, existing benchmarks and reproduction workflows often struggle to keep pace. More importantly, T2I jailbreak evaluation is not a single prompt-level test, but a pipeline-level problem shaped by multiple stages, including prompt...

A Quantum Algorithm for One-Shot Signatures

We provide a pre-obfuscation circuit-level implementation of an efficient one shot signature scheme, which has known applications to delegated signatures, secured token transfer, and publicly verifiable randomness. The algorithm consists of two stages: a key generation stage where a classical...

Understanding the (In)Security of Vibe-Coded Applications

Recent advances in large language models LLMs have enabled vibe coding, an emerging software development paradigm in which users create applications primarily through natural-language interactions with AI agents. Due to its low barrier to entry, vibe coding is rapidly gaining adoption in practice...

Understanding the Stealthy BGP Hijacking Risk in the ROV Era

The partial deployment of Route Origin Validation ROV poses an unexpected security threat known as stealthy BGP hijacking, i.e., a particularly elusive form of BGP hijacking where malicious routes divert traffic without reaching and thus alerting the victims. This risk remains largely unexplored,...

What You See Is Not What You Execute: Memory-Based Runtime SBOM Generation for Supply Chain Security

Modern software development relies heavily on third-party components from public repositories, expanding the software supply chain attack surface. In response to these growing risks, federal initiatives have advanced the Software Bill of Materials SBOM as a standardized mechanism for improving...

Joern 4.0.562

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...

Faraday 5.22.0

Faraday is a tool that introduces a new concept called IPE, or Integrated Penetration-Test Environment. It is a multiuser penetration test IDE designed for distribution, indexation and analysis of the generated data during the process of a security audit. The main purpose of Faraday is to re-use...

Towards Robust Personalized Federated Learning: Vulnerability Assessment and Defense Co-Design

The proliferation of IoT devices has fueled distributed edge systems to collect vast amounts of sensitive data, creating fertile ground for on-device machine learning applications. While federated learning FL mitigates privacy concerns by exchanging model parameters instead of raw data, we identi...

RAVEN: Agentic RAG for Automated Vulnerability Repair

Automated vulnerability repair has emerged as a promising direction to mitigate the growing number of software vulnerabilities. Recent advances in Large Language Models LLMs have further accelerated research in automated repair. However, existing frameworks remain largely restricted to...

From CVE to CWE: Syscall-Based HIDS Generalisation

Host intrusion detection systems HIDS based on system-call traces are typically trained and evaluated against individual Common Vulnerabilities and Exposures CVE instances. In operational settings, however, defenders need to recognise new exploits of an already known type of weakness. We...

One-Prompt Censorship Evasion Via Generative Diffusion Models

The escalating arms race between Internet censorship and evasion has driven censors to evolve from static rule-based filtering to sophisticated deep learning-based traffic analysis. While recent automated evasion tools have attempted to counter this by leveraging stochastic search and programmabl...

Revelio: Cost-Efficient Agentic Memory Safety Vulnerability Detection for Repository-Scale Codebases

Memory safety vulnerabilities remain a significant threat even for projects with extensive fuzzing and manual auditing. Recent results suggest that large language models hold great promise for detecting such vulnerabilities, but they are unreliable, at risk of hallucination, and challenging to...

DejaVu: Why You Should Write to Your DRAM Rows Twice, Carefully

We provide the first experimental demonstration of DejaVu, a phenomenon where the data previously written to DRAM cells affects DRAM's vulnerability to read disturbance. Our experimental characterization using 112 COTS DDR4 DRAM chips from all three major manufacturers shows that, compared to the...

Investigating the Security of Modern AI and Cloud Infrastructure

The widespread deployment of Deep Neural Networks and Large Language Models LLMs relies on a foundational assumption of isolation that this dissertation challenges. This work systematically deconstructs security assumptions around AI and modern cloud infrastructure through a taxonomy of interacti...

AgentRiskBOM: A Risk-Scoping Security Bill of Materials for Agentic AI Systems

Agentic AI systems retrieve private context, invoke tools, write files, call external services, coordinate with other agents, and may act without human approval. Existing bill of materials artifacts improve transparency for dependencies, model metadata, and training provenance, but leave an agent...

TRACE: A Threat Modelling Methodology for Distributed, Cloud-First, and Decentralized Organisations

Established threat modelling methodologies STRIDE, PASTA, Trike, OCTAVE, LINDDUN, attack trees, and adversary-behaviour catalogues such as MITRE ATT&CK were designed for software products and enterprises with a discernible security perimeter, a single owning organisation, and a clean separation...

Veno File Manager 4.4.9 Logs Export Checker

This is a Metasploit auxiliary module used for security testing of Veno File Manager that checks whether the log export endpoint is accessible without authentication...

Joplin Plugin Persistence

This Metasploit module installs a malicious Joplin plugin .jpl into the targets Joplin plugin directory. The plugin executes the payload each time Joplin is launched, providing persistent code execution. Joplin can not be running at the time of plugin installation, or it will be overwritten at...

A Longitudinal Study of Android Apps Signing Key Protection

Android app signing relies on developer-managed credentials, making secure key protection essential for the integrity of the software supply chain. A recent platform key leakage incident involving two major OEM manufacturers demonstrates that even robustly designed signing mechanisms can be...