CVE-2026-6859 Instructlab: instructlab: arbitrary code execution due to hardcoded `trust_remote_code=true`

A flaw was found in InstructLab. The linuxtrain.py script hardcodes trustremotecode=True when loading models from HuggingFace. This allows a remote attacker to achieve arbitrary Python code execution by convincing a user to run ilab train/download/generate with a specially crafted malicious model...

llm-security-lab

LLM Security Lab Laboratoire de sécurité pour application...

TL-RL-FusionNet: An Adaptive and Efficient Reinforcement Learning-Driven Transfer Learning Framework for Detecting Evolving Ransomware Threats

Modern ransomware exhibits polymorphic and evasive behaviors by frequently modifying execution patterns to evade detection. This dynamic nature disrupts feature spaces and limits the effectiveness of static or predefined models. To address this challenge, we propose TL-RL-FusionNet, a reinforceme...

AVISE: Framework for Evaluating the Security of AI Systems

As artificial intelligence AI systems are increasingly deployed across critical domains, their security vulnerabilities pose growing risks of high-profile exploits and consequential system failures. Yet systematic approaches to evaluating AI security remain underdeveloped. In this paper, we...

CVE-2026-41131 OpenFGA has Improper Policy Enforcement

OpenFGA is an authorization/permission engine built for developers. Prior to version 1.14.1, in specific scenarios, models using conditions with caching enabled can result in two different check requests producing the same cache key. This could result in OpenFGA reusing an earlier cached result f...

DP-FlogTinyLLM: Differentially Private Federated Log Anomaly Detection Using Tiny LLMs

Modern distributed systems generate massive volumes of log data that are critical for detecting anomalies and cyber threats. However, in real world settings, these logs are often distributed across multiple organizations and cannot be centralized due to privacy and security constraints. Existing...

Involuntary In-Context Learning: Exploiting Few-Shot Pattern Completion to Bypass Safety Alignment in GPT-5.4

Safety alignment in large language models relies on behavioral training that can be overridden when sufficiently strong in-context patterns compete with learned refusal behaviors. We introduce Involuntary In-Context Learning IICL, an attack class that uses abstract operator framing with few-shot...

Evaluating LLM-Generated Obfuscated XSS Payloads for Machine Learning-Based Detection

Cross-site scripting XSS remains a persistent web security vulnerability, especially because obfuscation can change the surface form of a malicious payload while preserving its behavior. These transformations make it difficult for traditional and machine learning-based detection systems to reliab...

RAVEN: Retrieval-Augmented Vulnerability Exploration Network for Memory Corruption Analysis in User Code and Binary Programs

Large Language Models LLMs have demonstrated remarkable capabilities across various cybersecurity tasks, including vulnerability classification, detection, and patching. However, their potential in automated vulnerability report documentation and analysis remains underexplored. We present RAVEN...

Security Is Relative: Training-Free Vulnerability Detection Via Multi-Agent Behavioral Contract Synthesis

Deep learning for vulnerability detection has shown promising results on early benchmarks, but recent evaluations reveal catastrophic degradation: models achieving F1 0.68 on legacy datasets collapse to 0.031 under strict deduplication. We identify the root cause as the semantic ambiguity problem...

GuardPhish: Securing Open-Source LLMs from Phishing Abuse

The rapid adoption of open-source Large Language Models LLMs in offline and enterprise environments has introduced a largely unexamined security risk like susceptibility to adversarial phishing prompts under static safety configurations. In this work, we systematically investigate this...

cpython: Stack overflow parsing XML with deeply nested DTD content models

A stack overflow flaw has been discovered in the python pyexpat module. When an Expat parser with a registered ElementDeclHandler parses an inline document type definition containing a deeply nested content model a C stack overflow occurs. This will result in a program crash...

cpython: Stack overflow parsing XML with deeply nested DTD content models

A stack overflow flaw has been discovered in the python pyexpat module. When an Expat parser with a registered ElementDeclHandler parses an inline document type definition containing a deeply nested content model a C stack overflow occurs. This will result in a program crash...

Surgical Repair of Insecure Code Generation in LLMs

Large language models write production code, and yet they routinely introduce well-known vulnerabilities. We show that this is not a knowledge deficit: the same models that generate insecure code, correctly identify and explain the vulnerability when asked directly, this is a gap we call the...

[SECURITY] Fedora 44 Update: kf6-kitemmodels-6.25.0-1.fc44

KDE Frameworks 6 Tier 1 addon with item models...

CVE-2026-40729

Missing Authorization vulnerability in bPlugins 3D viewer – Embed 3D Models 3d-viewer allows Exploiting Incorrectly Configured Access Control Security Levels.This issue affects 3D viewer – Embed 3D Models: from n/a through = 1.8.5...

MLDAS: Machine Learning Dynamic Algorithm Selection for Software-Defined Networking Security

Network security is a critical concern in the digital landscape of today, with users demanding secure browsing experiences and protection of their personal data. This study explores the dynamic integration of Machine Learning ML algorithms with Software-Defined Networking SDN controllers to enhan...

LLM4C2Rust: Large Language Models for Automated Memory-Safe Code Transpilation

Memory safety has long been a critical challenge in software engineering, particularly for legacy systems written in memory-unsafe languages such as C and C++. Rust, one of the youngest modern programming languages, offers built-in memory-safety guarantees that make it a strong candidate for secu...

CVE-2026-40316 OWASP BLT has RCE in Github Actions via untrusted Django model execution in workflow

OWASP BLT is a QA testing and vulnerability disclosure platform that encompasses websites, apps, git repositories, and more. Versions prior to 2.1.1 contain an RCE vulnerability in the .github/workflows/regenerate-migrations.yml workflow. The workflow uses the pullrequesttarget trigger to run wit...

EUVD-2026-23134

OWASP BLT is a QA testing and vulnerability disclosure platform that encompasses websites, apps, git repositories, and more. Versions prior to 2.1.1 contain an RCE vulnerability in the .github/workflows/regenerate-migrations.yml workflow. The workflow uses the pullrequesttarget trigger to run wit...