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...

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...

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...

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...

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...

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...

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...

Cross-Ecosystem Vulnerability Analysis for Python Applications

Python applications depend on native libraries that may be vendored within package distributions or installed on the host system. When vulnerabilities are discovered in these libraries, determining which Python packages are affected requires cross-ecosystem analysis spanning Python dependency...

Mining the YARA Ecosystem: From Ad-Hoc Sharing to Data-Driven Threat Intelligence

YARA has established itself as the de facto standard for "Detection as Code," enabling analysts and DevSecOps practitioners to define signatures for malware identification across the software supply chain. Despite its pervasive use, the open-source YARA ecosystem remains characterized by ad-hoc...

FP-Predictor - False Positive Prediction for Static Analysis Reports

Static Application Security Testing SAST tools play a vital role in modern software development by automatically detecting potential vulnerabilities in source code. However, their effectiveness is often limited by a high rate of false positives, which wastes developer's effort and undermines trus...

Avoid Evasive Scraping with Stronger Content Protection

Learn about the enhancements to Akamai Content Protector that stop evasive scraping across web and mobile while minimizing user friction and false positives...

OpenAnt LLM-Based Vulnerability Discovery

OpenAnt from Knostic is an open source LLM-based vulnerability discovery product that helps defenders proactively find verified security flaws while minimizing both false positives and false negatives. Stage 1 detects. Stage 2 attacks. What survives is real...