474 matches found
EUVD-2026-9694
Improper Control of Filename for Include/Require Statement in PHP Program 'PHP Remote File Inclusion' vulnerability in ThemeREX Tuning tuning allows PHP Local File Inclusion.This issue affects Tuning: from n/a through = 1.3...
CVE-2026-28032
Improper Control of Filename for Include/Require Statement in PHP Program 'PHP Remote File Inclusion' vulnerability in ThemeREX Tuning tuning allows PHP Local File Inclusion.This issue affects Tuning: from n/a through = 1.3...
CVE-2026-28032 WordPress Tuning theme <= 1.3 - Local File Inclusion vulnerability
Improper Control of Filename for Include/Require Statement in PHP Program 'PHP Remote File Inclusion' vulnerability in ThemeREX Tuning tuning allows PHP Local File Inclusion.This issue affects Tuning: from n/a through = 1.3...
CVE-2026-28032
CVE-2026-28032 : WordPress Theme Tuning (ThemeREX) <= 1.3 suffers an Improper Control of Filename for Include/Require Statement (PHP Local File Inclusion). The vulnerability type is described as a PHP Remote File Inclusion in the entry, with the Theme reportedly affected through version <= ...
CVE-2026-28032 WordPress Tuning theme <= 1.3 - Local File Inclusion vulnerability
Improper Control of Filename for Include/Require Statement in PHP Program 'PHP Remote File Inclusion' vulnerability in ThemeREX Tuning tuning allows PHP Local File Inclusion.This issue affects Tuning: from n/a through = 1.3...
PT-2026-23314
Improper Control of Filename for Include/Require Statement in PHP Program 'PHP Remote File Inclusion' vulnerability in ThemeREX Tuning tuning allows PHP Local File Inclusion.This issue affects Tuning: from n/a through = 1.3...
WordPress plugin Tuning 安全漏洞
WordPress and WordPress plugins are both products of the WordPress Foundation. WordPress is a blog platform developed using the PHP language. This platform allows for the creation of personal blog websites on servers based on PHP and MySQL. A WordPress plugin is an application that can be install...
WordPress Tuning theme <= 1.3 - Local File Inclusion vulnerability
Local File Inclusion vulnerability discovered by Tran Nguyen Bao Khanh VCI - VNPT Cyber Immunity in WordPress Theme Tuning versions = 1.3...
6 Ways Agentic AI Changes How Systems Act and Adapt
Learn how agentic AI changes system behavior in production environments through supervised fine-tuning, structured oversight, and lifecycle governance to improve reliability, manage risk, and support accountable deployment...
TraceGuard: Process-Guided Firewall against Reasoning Backdoors in Large Language Models
The deployment of Large Reasoning Models LRMs in high-stakes decision-making pipelines has introduced a novel and opaque attack surface: reasoning backdoors. In these attacks, the model's intermediate Chain-of-Thought CoT is manipulated to provide a linguistically plausible but logically fallacio...
Detecting PowerShell-Based Fileless Cryptojacking Attacks Using Machine Learning
With the emergence of remote code execution RCE vulnerabilities in ubiquitous libraries and advanced social engineering techniques, threat actors have started conducting widespread fileless cryptojacking attacks. These attacks have become effective with stealthy techniques based on PowerShell-bas...
MultiVer: Zero-Shot Multi-Agent Vulnerability Detection
We present MultiVer, a zero-shot multi-agent system for vulnerability detection that achieves state-of-the-art recall without fine-tuning. A four-agent ensemble security, correctness, performance, style with union voting achieves 82.7% recall on PyVul, exceeding fine-tuned GPT-3.5 81.3% by 1.4...
From SFT to RL: Demystifying the Post-Training Pipeline for LLM-Based Vulnerability Detection
The integration of LLMs into vulnerability detection VD has shifted the field toward interpretable and context-aware analysis. While post-training methods have shown promise in general coding tasks, their systematic application to VD remains underexplored. In this paper, we present the first...
GoodVibe: Security-By-Vibe for LLM-Based Code Generation
Large language models LLMs are increasingly used for code generation in fast, informal development workflows, often referred to as vibe coding, where speed and convenience are prioritized, and security requirements are rarely made explicit. In this setting, models frequently produce functionally...
A one-prompt attack that breaks LLM safety alignment
Large language models LLMs and diffusion models now power a wide range of applications, from document assistance to text-to-image generation, and users increasingly expect these systems to be safety-aligned by default. Yet safety alignment is only as robust as its weakest failure mode. Despite...
A one-prompt attack that breaks LLM safety alignment
Large language models LLMs and diffusion models now power a wide range of applications, from document assistance to text-to-image generation, and users increasingly expect these systems to be safety-aligned by default. Yet safety alignment is only as robust as its weakest failure mode. Despite...
The Trigger in the Haystack: Extracting and Reconstructing LLM Backdoor Triggers
Detecting whether a model has been poisoned is a longstanding problem in AI security. In this work, we present a practical scanner for identifying sleeper agent-style backdoors in causal language models. Our approach relies on two key findings: first, sleeper agents tend to memorize poisoning dat...
Evaluating Large Language Models for Security Bug Report Prediction
Early detection of security bug reports SBRs is critical for timely vulnerability mitigation. We present an evaluation of prompt-based engineering and fine-tuning approaches for predicting SBRs using Large Language Models LLMs. Our findings reveal a distinct trade-off between the two approaches...
PIDSMaker: Building and Evaluating Provenance-Based Intrusion Detection Systems
Recent provenance-based intrusion detection systems PIDSs have demonstrated strong potential for detecting advanced persistent threats APTs by applying machine learning to system provenance graphs. However, evaluating and comparing PIDSs remains difficult: prior work uses inconsistent preprocessi...
Llama-3.1-FoundationAI-SecurityLLM-Reasoning-8B Technical Report
We present Foundation-Sec-8B-Reasoning, the first open-source native reasoning model for cybersecurity. Built upon our previously released Foundation-Sec-8B base model derived from Llama-3.1-8B-Base, the model is trained through a two-stage process combining supervised fine-tuning SFT and...