Fuzz'EMup: Leveraging EM Side-Channel Emanation to Guide Black-Box Embedded Firmware Fuzzing

As IoT and embedded devices proliferate across various domains, securing their firmware has become critical. Fuzzing offers a systematic approach to uncovering vulnerabilities in firmware, and coverage feedback can improve its effectiveness by guiding exploration. However, many devices make...

A Control-Driven Framework for Secure SaaS Onboarding in Regulated Enterprises

As enterprises increasingly adopt Software-as-a-Service SaaS platforms for mission-critical functions, onboarding these services has emerged as a complex challenge extending well beyond procurement and basic security review. In regulated environments, SaaS onboarding must address multiple...

TaintRadar: Semantic-Aware Taint-Style Vulnerability Detection Via Augmented Code Property Graphs

Despite significant advances, static vulnerability analysis suffers from three critical limitations: coarse sanitization modeling, which treats validation as a binary barrier; database blindness, which breaks taint tracking across persistence layers; and shallow object-oriented analysis, which...

Reliable Remediation Impact Prediction for Black-Box Security Ratings

Security rating platforms summarize externally observable cyber exposure and are expected to help organizations prioritize remediation. A platform may want to tell an organization how a candidate remediation action would affect its score, but repeatedly exposing exact score responses can reveal...

SQUIRO: A Framework for Security-Aware Quantum-Classical Scheduling on Kubernetes

Distributed infrastructure schedulers traditionally optimise capacity, locality, and cost, but provide limited support for security posture and emerging quantum-classical workloads. As hybrid quantum-classical computing becomes increasingly practical and post-quantum security requirements begin t...

Routing Ceilings Are Domain-Independent: Structural Prior Injection in Code Security Vulnerability Detection

Large language models LLMs exhibit a well-documented gap between latent capability and consistent activation: the router hypothesis posits that models possess the knowledge to solve a task but lack reliable internal routing to activate it. Prior work in formal mathematical reasoning SAIR, C�zares...

Towards Secure and Trustworthy DAOs for Cross-Chain Governance

Cross-chain DAOs face unique security challenges that go beyond traditional single-chain vulnerabilities. This paper identifies and categorizes four critical attack vectors in cross-chain DAO governance: bribery attacks, token control exploits, human-computer interaction deceptions, and protocol...

Signal-Based Model Access Risk Analysis for AI System Operations Security

Artificial intelligence AI systems are now ubiquitous across domains such as security, finance, healthcare, consumer technology, and large-scale cloud services, where they process massive volumes of data and make consequential decisions daily. This widespread adoption has created a broad attack...

Enhanced Multi-Class DDoS Attack Identification Using a Meta-Learning Ensemble

Distributed Denial of Service DDoS attacks continue to pose significant threats to network availability and security. While many detection systems focus on binary classification attack vs. benign, effective mitigation often requires identifying the specific type of DDoS attack. This paper...

Revisiting Data-Driven Dynamic Security Assessment with a Tabular Foundation Model

Data-driven pre-fault dynamic security assessment DSA rapidly evaluates the dynamic risk of credible contingencies on a power system using machine learning. Existing approaches face two limitations. First, they require a large labelled database for training, with a separate model trained, tuned,...

Cloudflare Universal SSL CAA Augmentation

Cloudflare Universal SSL automatically adds CAA issue/issuewild records when a customer has Universal SSL enabled and publishes any CAA records for the zone. These auto-added records are not shown in the Cloudflare dashboard but are returned in DNS responses, and can include permissive...

MemPoison: Uncovering Persistent Memory Threats and Structural Blind Spots in LLM Agents

Persistent external memory enhances agent continuity but introduces persistent security vulnerabilities: adversarial content can be injected via standard interaction channels, retained across turns, and later distort downstream behavior. To address this challenge, we propose MemPoison, a...

Xalgorix Autonomous AI Pentesting Agent 4.5.62

Most scanners detect. Xalgorix proves. An autonomous LLM agent works a full pentest methodology, then an independent verifier re-exploits every finding before it's reported - so you get proof, not a pile of maybes to triage. Self-hosted, private, and bring-your-own-LLM. Built in Go + TypeScript...

On the Impact of Entropy-Based Features

Network anomaly detection is increasingly challenging due to the growing diversity and variability of traffic patterns, which are not always well captured by traditional statistical features. In this work, we explore the use of entropy as an additional feature to support supervised network traffi...

FlowGuard: From Signals to Evidence for MCP Security Detection

The Model Context Protocol MCP enables LLM agents to interact with external tools through metadata exchange, tool invocation, and response consumption. Existing MCP security scanners primarily reason about suspicious semantic signals rather than real execution behaviors, which can lead to...

The Distributed Open-Source Vulnerability Ecosystem

Identifying known software vulnerabilities is a central task in software supply chain security management. Although publicly available vulnerability information is based on shared standards, different vulnerability scanners often report divergent results for identical software inventories. These...

Beyond Success Rate: Cost-Aware Evaluation of Offensive and Defensive Security Agents

Security-agent evaluations commonly measure peak offensive capability under generous inference budgets, emphasizing vulnerability discovery, exploit development, penetration testing, and CTF completion. Such measurements are useful but incomplete: in operational security, every reasoning step, to...

CodeQL 2.26.1

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...

Boundary-Seeking GAN-Augmented TabTransformer for Adversarially Robust Intrusion Detection

Machine learning-based intrusion detection systems IDSs often suffer from class imbalance and vulnerability to adversarial attacks, leading to degraded detection performance and reduced robustness. This study proposes a TabTransformer framework augmented by the Boundary-Seeking Generative...

SonicWall SMA1000 Series SSRF Detection Tool

A safe detection tool for identifying CVE-2026-15409 affecting SonicWall SMA1000 Series appliances. The Python utility performs non-destructive checks by issuing requests to common application endpoints using an external test URL and reports indicators of possible server-side request forgery...

Qubes OS Security in the Public Record

Qubes OS is a revealing case for security measurement because its architecture makes component boundaries security-relevant. We present a protocol-driven longitudinal analysis of 109 public Qubes Security Bulletins QSBs, 2011--2025, the official Qubes-maintained Xen Security Advisory XSA tracker,...

RedAmon 6.0.2

An autonomous AI framework that chains reconnaissance, exploitation, and post-exploitation into a single pipeline, then goes further by triaging every finding, implementing code fixes, and opening pull requests on your repository. From first packet to merged patch, with human oversight at every...

Setup Complete, Now You Are Compromised: Weaponizing Setup Instructions against AI Coding Agents

AI coding agents set up projects by reading documentation and installing the dependencies it lists, without verifying their names, sources, or known vulnerabilities. By editing only a README, requirements file, or Makefile, an attacker can redirect the agent to an untrusted registry, a...

Joern 4.0.582

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...

Bad Memory: Evaluating Prompt Injection Risks from Memory in Agentic Systems

A growing class of agentic systems maintain persistent state across sessions through memory files, behavioral preferences, and knowledge bases. While this makes agents more useful and self-improving, it also creates a new attack surface for prompt injections in which malicious instructions can be...

Specter 1.0 NFC Reader / Skimmer Bug-Sweep

Specter turns your Flipper Zero into a pocket counter-surveillance bug-sweep for active 13.56 MHz NFC readers - a hidden card skimmer slipped into a payment terminal, a covert reader behind a door panel, a rogue logger taped under a desk. It passively senses the RF carrier that any powered-on...

Security Evaluation of Quantum Distance-Bounding Protocols Via Semidefinite Programming

Quantum distance-bounding QDB protocols let a verifier check that a prover is both genuine and physically nearby. During a timed fast phase of quantum communication, the verifier measures round-trip times to obtain an upper bound on the prover's distance. For a uniform comparison, we isolate the...

To Play or Not to Play: Insights and Lessons Learned from 20 Years of CTFs with ENOFLAG

Security contests in the form of CTF Capture The Flag exercises are nowadays a common way to learn cyber security. 20 years ago at DIMVA 2006 the on-site CTF CIPHER II was one of the conference highlights and led to the foundation of the team ENOFLAG. In this poster, we reflect on the changes in...

A SecOps Practitioner's View of Project Glasswing and the Halcyon Imperative

This paper is written from the ground level, from the perspective of someone running a Security Operations Center SOC and an Attack Surface Management program day to day. It is not a strategic overview for the boardroom. It is a practitioner's assessment of what Glasswing changes functionally, wh...

Meeting Uncertain Threats with Feedback

Air and missile defense, naval force protection, and critical-infrastructure security require rapid allocation of scarce effectors against multiple incoming threats when neutralization is uncertain and observed only after a firing round. We formulate this defensive-allocation problem as a Markov...

Traffic-Aware Randomized Smoothing for LLM-Based Network Intrusion Detection

Large language model LLM-based intrusion detection systems IDS are increasingly studied for security monitoring, yet their robustness against feasible traffic manipulation remains largely empirical. We present Traffic-Aware Randomized Smoothing TA-RS, a classifier-agnostic certified defense that...

Adversarial Prompting Framework for AI Safety Assessment

Artificial Intelligence AI, especially Generative AI GenAI, adoption has increased in industries significantly in recent years. However, the use of these models may also expose systems to new forms of cyberattacks by different malicious actors -- adversarial prompt attack APA being one of the mos...

DREA: Decoupled Reasoning and Exploration Agents for Repository-Level Vulnerability Detection

Large language models LLMs are increasingly applied to vulnerability detection due to their strong code comprehension capabilities, but most existing approaches rely on isolated functions or context extracted by fixed program-analysis rules. These methods cannot adaptively explore repository-leve...

Reveal, Correct, Then Pay: Encrypted Mempools and Perpetual Funding Security

Encrypted mempools are designed to hide transaction contents until execution order is fixed, preventing many victim dependent forms of maximal extractable value. This paper studies a different class of attack in the form of self-authored state manipulation, in which the attacker knows its own...

Joern 4.0.581

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...

Xalgorix Autonomous AI Pentesting Agent 4.5.60

Most scanners detect. Xalgorix proves. An autonomous LLM agent works a full pentest methodology, then an independent verifier re-exploits every finding before it's reported - so you get proof, not a pile of maybes to triage. Self-hosted, private, and bring-your-own-LLM. Built in Go + TypeScript...

Semgrep Rules 2.0.0 Static Analysis Rule Collection

A collection of Semgrep rules for identifying potentially vulnerable code patterns during static source code analysis. The rule set focuses on vulnerability research across multiple languages and includes checks for common security issues to assist developers, auditors, and security researchers...

Agent Skill Security: Threat Models, Attacks, Defenses, and Evaluation

Reusable skills are becoming a fundamental building block of Large Language Model LLM agents, enabling capabilities to be packaged, shared, and reused across diverse applications. However, existing security research primarily focuses on prompt injection and runtime execution, leaving security ris...

ProfMalPlus: Agent-Coordinated Detection of Malicious NPM Packages Via Static-Dynamic Analysis Synergy

Open source software is vulnerable to supply-chain attacks through transitive dependencies, especially malicious code injected into NPM packages. Existing detectors often inadequately model obfuscated behavior, overlook JavaScript's object-centric features, poorly coordinate static and dynamic...

MIMEDefang Email Scanner 3.71

MIMEDefang is a flexible MIME email scanner designed to protect Windows clients from viruses. Includes the ability to do many other kinds of mail processing, such as replacing parts of messages with URLs. It can alter or delete various parts of a MIME message according to a very flexible...

Rethinking Penetration Testing for AI-Enabled Systems: From Resource Compromise to Behavioral Objective Violation

Penetration testing traditionally evaluates whether adversaries can exploit weaknesses in software, infrastructure, configurations, or operational controls to achieve security-relevant compromise. This paradigm remains necessary for AI-enabled systems, but it is no longer sufficient. In such...

How Agents Ask for Permission: User Permissions for AI Agents, from Interfaces to Enforcement

As AI agents gain prevalance, users are increasingly exposed to the risks such systems entail. Prompt injection attacks, as well as hallucination, can cause agents to leak private information to third parties. As autonomous systems, agents also present the more active danger of performing sensiti...

A Measurement Study of AI-Environment Realism Gaps in Malware-Analysis Sandboxes

Sandboxing remains a core technique for observing suspicious program behavior, yet environment-aware malware increasingly suppresses execution when analysis is suspected. Prior generations of sandbox evasion focused on virtualization artifacts, timing discrepancies, and wear-and-tear realism. In...

Security Evaluation of Laser-Phase-Noise Quantum Random Number Generators with Intrinsic Correlations

Quantum random number generators are essential for achieving information-theoretical security in modern cryptographic systems. Among various implementations, laser phase noise schemes are widely favored for their simple architecture and high integration potential. However, the intrinsic...

The Prover Is the Judge: Verified Security Software from AI Coding Agents in Ada/SPARK

AI coding agents produce code faster than humans can review it. In our approach, the prover is the judge of whether the code is correct. Under a verifier-driven loop, AI agents wrote and verified bare-metal security software in Ada/SPARK spanning classical and post-quantum cryptography, TLS 1.3,...

Context Contamination in LLM Analysis of Network Security Logs: Poison with Passive Prompt Injection and Mitigation Evaluation

Large Language Models are increasingly deployed in Security Operations Centers for log analysis tasks including summarization, alert triage, and threat investigation. These systems ingest logs from external-facing services and process network logs as natural language contexts to generate security...

Assessing the Forensic Viability of Android Memory Analysis across Production Builds: A Cross-Version Study of Security Hardening and Structure Preservation

Android memory forensics recovers evidence that never touches disk: decrypted messages, session credentials, and the live internal state of a running application. The tools that perform this recovery depend on debug symbols embedded in libart.so, the Android Runtime library, to locate data...

Towards Quantum Machine Learning for Assessing the Resilience of Post-Quantum Cryptography

The potential capabilities of quantum computers motivated the development of cryptographic protocols suitable for securing communication against adversaries with access to large fault-tolerant quantum computers. However, even though current quantum computers are limited in terms of size and...

Designing a GDPR-Compliant Security Architecture for Remote Elderly Care Systems: A Privacy-By-Design Approach

IoMT-based remote elderly care systems generate continuous streams of sensitive health data, yet existing security architectures have not simultaneously addressed three interdependent challenges: GDPR-compliant edge-layer pseudonymisation, elderly-specific zero-interaction usability as a binding...

Evaluating Frontier AI Agents As Autonomous Clinical Security Auditors

Clinical AI models can expose patients to harm when adversarial vulnerabilities go undetected, yet formal security auditing requires statistical expertise, specialized tools, and significant time. We present an open evaluation task, built on METR Task Standard v0.3.0, that tests whether frontier ...