Security update for kernel-livepatch-MICRO-6-0-RT_Update_9

This update for kernel-livepatch-MICRO-6-0-RTUpdate9 fixes the following issues: CVE-2025-38083: netsched: prio: fix a race in priotune bsc1245350 CVE-2025-38494: HID: core: do not bypass hidhwrawrequest bsc1247350 CVE-2025-38495: HID: core: ensure the allocated report buffer can contain the...

SUSE-SU-2025:20678-1 Security update for kernel-livepatch-MICRO-6-0_Update_5

This update for kernel-livepatch-MICRO-6-0Update5 fixes the following issues: - CVE-2025-38079: crypto: algifhash - fix double free in hashaccept bsc1245218 - CVE-2025-38083: netsched: prio: fix a race in priotune bsc1245350 - CVE-2025-38494: HID: core: do not bypass hidhwrawrequest bsc1247350 -...

AI Agentic Vulnerability Injection and Transformation with Optimized Reasoning

The increasing complexity of software systems and the sophistication of cyber-attacks have underscored the critical need for effective automated vulnerability detection and repair systems. Traditional methods, such as static program analysis, face significant challenges related to scalability,...

Consiglieres in the Shadow: Understanding the Use of Uncensored Large Language Models in Cybercrimes

The advancement of AI technologies, particularly Large Language Models LLMs, has transformed computing while introducing new security and privacy risks. Prior research shows that cybercriminals are increasingly leveraging uncensored LLMs ULLMs as backends for malicious services. Understanding the...

Mitigating Jailbreaks with Intent-Aware LLMs

Despite extensive safety-tuning, large language models LLMs remain vulnerable to jailbreak attacks via adversarially crafted instructions, reflecting a persistent trade-off between safety and task performance. In this work, we propose Intent-FT, a simple and lightweight fine-tuning approach that...

MAL-2025-19218 Malicious code in edge-ai-tuning-kit (npm)

The package edge-ai-tuning-kit was found to contain malicious code. --- -= Per source details. Do not edit below this line.=-...

Malicious code in edge-ai-tuning-kit (npm)

The package edge-ai-tuning-kit was found to contain malicious code. --- -= Per source details. Do not edit below this line.=-...

Code Vulnerability Detection across Different Programming Languages with AI Models

Security vulnerabilities present in a code that has been written in diverse programming languages are among the most critical yet complicated aspects of source code to detect. Static analysis tools based on rule-based patterns usually do not work well at detecting the context-dependent bugs and...

BERTector: Intrusion Detection Based on Joint-Dataset Learning

Intrusion detection systems IDS are facing challenges in generalization and robustness due to the heterogeneity of network traffic and the diversity of attack patterns. To address this issue, we propose a new joint-dataset training paradigm for IDS and propose a scalable BERTector framework based...

Linux Distros Unpatched Vulnerability : CVE-2022-48996

The Linux/Unix host has one or more packages installed that are impacted by a vulnerability without a vendor supplied patch available. - In the Linux kernel, the following vulnerability has been resolved: mm/damon/sysfs: fix wrong empty schemes assumption under online tuning in damonsysfssetschem...

A Real-Time, Self-Tuning Moderator Framework for Adversarial Prompt Detection

Ensuring LLM alignment is critical to information security as AI models become increasingly widespread and integrated in society. Unfortunately, many defenses against adversarial attacks and jailbreaking on LLMs cannot adapt quickly to new attacks, degrade model responses to benign prompts, or...

net_sched: prio: fix a race in prio_tune()

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Proactive Disentangled Modeling of Trigger-Object Pairings for Backdoor Defense

Deep neural networks DNNs and generative AI GenAI are increasingly vulnerable to backdoor attacks, where adversaries embed triggers into inputs to cause models to misclassify or misinterpret target labels. Beyond traditional single-trigger scenarios, attackers may inject multiple triggers across...

PT-2025-32492 · Pypi · Ms-Swift

I. Detailed Description: 1. Install ms-swift pip install ms-swift -U 2. Start web-ui swift web-ui --lang en 3. After startup, access through browser at http://localhost:7860/ to see the launched fine-tuning framework program 4. Fill in necessary parameters In the LLM Training interface, fill in...

SAEL: Leveraging Large Language Models with Adaptive Mixture-Of-Experts for Smart Contract Vulnerability Detection

With the increasing security issues in blockchain, smart contract vulnerability detection has become a research focus. Existing vulnerability detection methods have their limitations: 1 Static analysis methods struggle with complex scenarios. 2 Methods based on specialized pre-trained models...

SDD: Self-Degraded Defense against Malicious Fine-Tuning

Open-source Large Language Models LLMs often employ safety alignment methods to resist harmful instructions. However, recent research shows that maliciously fine-tuning these LLMs on harmful data can easily bypass these safeguards. To counter this, we theoretically uncover why malicious fine-tuni...

LoRA-Leak: Membership Inference Attacks against LoRA Fine-Tuned Language Models

Language Models LMs typically adhere to a "pre-training and fine-tuning" paradigm, where a universal pre-trained model can be fine-tuned to cater to various specialized domains. Low-Rank Adaptation LoRA has gained the most widespread use in LM fine-tuning due to its lightweight computational cost...

Scaling Decentralized Learning with FLock

Fine-tuning the large language models LLMs are prevented by the deficiency of centralized control and the massive computing and communication overhead on the decentralized schemes. While the typical standard federated learning FL supports data privacy, the central server requirement creates a...

Jailbreak-Tuning: Models Efficiently Learn Jailbreak Susceptibility

AI systems are rapidly advancing in capability, and frontier model developers broadly acknowledge the need for safeguards against serious misuse. However, this paper demonstrates that fine-tuning, whether via open weights or closed fine-tuning APIs, can produce helpful-only models. In contrast to...

May I Have Your Attention? Breaking Fine-Tuning Based Prompt Injection Defenses Using Architecture-Aware Attacks

A popular class of defenses against prompt injection attacks on large language models LLMs relies on fine-tuning the model to separate instructions and data, so that the LLM does not follow instructions that might be present with data. There are several academic systems and production-level...