Securing the Dark Matter: A Semantic-Enhanced Neuro-Symbolic Framework for Supply Chain Analysis of Opaque Industrial Software

Automated vulnerability detection in critical-infrastructure software confronts a fundamental barrier: industrial software is routinely deployed as stripped, symbol-free binaries that deprive conventional Software Composition Analysis of the source-level transparency it requires. Existing binary...

alika-vuln-shield

Vuln Shield Fast container vulnerability scanner that filters...

Evolution of Log-Based Detection Rules in Public Repositories

Log-based detection rules remain central to modern security operations, encoding domain expertise that analysts iteratively refine to balance detection coverage against alert volume. Yet while prior work has examined the evolution of network intrusion detection signatures, the longitudinal behavi...

Rayhunter IMSI Catcher Detector

Rayhunter is a project for detecting IMSI catchers, also known as cell-site simulators or stingrays. It was first designed to run on a cheap mobile hotspot called the Orbic RC400L, but thanks to community efforts, it can support some other devices as well. It's also designed to be as easy to...

QASecClaw: A Multi-Agent LLM Approach for False Positive Reduction in Static Application Security Testing

Static Application Security Testing tools help developers find security vulnerabilities before release, but they often produce many false positives. This increases manual review effort, reduces developer trust, and may cause real vulnerabilities to be ignored among noisy reports. We present...

How Code Representation Shapes False-Positive Dynamics in Cross-Language LLM Vulnerability Detection

How code representation format shapes false positive behaviour in cross-language LLM vulnerability detection remains poorly understood. We systematically vary training intensity and code representation format, comparing raw source text with pruned Abstract Syntax Trees at both training time and...

WP-Plugin-Fuzzer-PoC-

wpgarlic A proof-of-concept WordPress plugin fuzzer that led t...

Beyond Code Reasoning: A Specification-Anchored Audit Framework for Expert-Augmented Security Verification

Security-critical software is routinely audited by tools that reason about vulnerabilities as repository-local code patterns. Yet specification-governed systems -- protocol stacks, consensus implementations, cryptographic libraries -- are constrained by invariants and correctness conditions defin...

EDySec: A Deep Learning-Based Explainable Dynamic Analysis Framework for Detecting Malicious Packages in PyPI Ecosystem

The security of open-source software repositories is increasingly threatened by next-gen software supply chain attacks. These attacks include multiphase malware execution, remote access activation, and dynamic payload generation. Traditional Machine Learning ML detectors struggle to detect these...

Detecting Avalanche Effect in Adversarial Settings: Spotting the Encryption Loops in Ransomware

Spotting encryption loops in binary-only ransomware is a critical reverse engineering task. Since the existence of avalanche effect, an intrinsic characteristic of any secure encryption algorithms, is unavoidable during a victim data encryption attack, it is a very promising direction to spot...

Nuclei 3.8.0

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...

Enhancing Anomaly-Based Intrusion Detection Systems with Process Mining

Anomaly-based Intrusion Detection Systems IDSs ensure protection against malicious attacks on networked systems. While deep learning-based IDSs achieve effective performance, their limited trustworthiness due to black-box architectures remains a critical constraint. Despite existing explainable...

sqli-research

🔬 sqli-research Time-Based Blind SQL Injection — Riset, Po...

OPENSUSE-SU-2026:20579-1 Security update for gosec

This update for gosec fixes the following issues: Changes in gosec: - Update to version 2.25.0: choredeps: bump google.golang.org/grpc from 1.75.0 to 1.79.3 1617 fix: allow barry action to access secrets on fork PRs 1616 fix: reduce G117 false positives for custom marshalers and transformed value...

GHSA-W6C6-C85G-MMV6 Cosign's verify-blob-attestation reports false positive when payload parsing fails

Description cosign verify-blob-attestation may erroneously report a "Verified OK" result for attestations with malformed payloads or mismatched predicate types. For old-format bundles and detached signatures, this was due to a logic flaw in the error handling of the predicate type validation. For...

Cosign's verify-blob-attestation reports false positive when payload parsing fails

Description cosign verify-blob-attestation may erroneously report a "Verified OK" result for attestations with malformed payloads or mismatched predicate types. For old-format bundles and detached signatures, this was due to a logic flaw in the error handling of the predicate type validation. For...

Explainable Autonomous Cyber Defense Using Adversarial Multi-Agent Reinforcement Learning

Autonomous agents are increasingly deployed in both offensive and defensive cyber operations, creating high-speed, closed-loop interactions in critical infrastructure environments. Advanced Persistent Threat APT actors exploit "Living off the Land" techniques and targeted telemetry perturbations ...

RuleForge: Automated Generation and Validation for Web Vulnerability Detection at Scale

Security teams face a challenge: the volume of newly disclosed Common Vulnerabilities and Exposures CVEs far exceeds the capacity to manually develop detection mechanisms. In 2025, the National Vulnerability Database published over 48,000 new vulnerabilities, motivating the need for automation. W...

Why Aggregate Accuracy Is Inadequate for Evaluating Fairness in Law Enforcement Facial Recognition Systems

Facial recognition systems are increasingly deployed in law enforcement and security contexts, where algorithmic decisions can carry significant societal consequences. Despite high reported accuracy, growing evidence demonstrates that such systems often exhibit uneven performance across demograph...

The System Prompt Is the Attack Surface: How LLM Agent Configuration Shapes Security and Creates Exploitable Vulnerabilities

System prompt configuration can make the difference between near-total phishing blindness and near-perfect detection in LLM email agents. We present PhishNChips, a study of 11 models under 10 prompt strategies, showing that prompt-model interaction is a first-order security variable: a single...