fixing-google-secops-detections

Google SecOps Chronicle Curated Detections: Flaw Analysis & Tuning This repository documents architectural design flaws, logic discrepancies, and tuning strategies for native Google SecOps Chronicle Curated Detections. While Google Threat Intelligence GTIG provides exceptional conceptual threat...

scodescanner

SCodeScanner SCodeScanner stands for Source Code scanner where the user can scans the source code for finding the Critical Vulnerabilities. The main objective for this scanner is to find the vulnerabilities inside the source code before code gets published in Prod. Website for newreleases, new...

pulledpork

PulledPork PulledPork for Snort and Suricata rule management from Google code Find us on Libera.Chat IRC pulledpork Copyright C 2009-2021 JJ Cummings, Michael Shirk and the PulledPork Team! Thank you for choosing to use PulledPork! This file provides some basic guidance on the usage of PulledPork...

steamer

Steamer Import, manage, search public dumps. Do you have massive amounts of CSV, .sql, .txt, that have credentials, passwords, and hashes inside? Use Steamer to manage them! Load them into a MongoDB database, and either use the console directly, or just use the handy web interface complete with...

refusal-relocates

Project Page · Quick start · Usage · CLI · Results · Reproduce · FAQ · Citation News 2026-09-28 Code released, with the run records and scripts that rebuild the paper's tables. Overview A few dozen harmful examples can remove an aligned model's refusal of harmful requests. Prior work localizes...

SLDR

NeurIPS 2026 SLDR: Defending Against Malicious Fine-tuning via Selective Layers Recovery and Dynamic Routing 🔧 Environment Setup Clone the repository, create and activate the Conda environment, then install the required dependencies: git clone https://github.com/Stardust457/SLDR.git cd SLDR conda...

DeeCLIP

DeeCLIP: A Robust and Generalizable Transformer-Based Framework for Detecting AI-Generated Images ☀️ If you find this work useful for your research, please kindly star our repo and cite our paper! ☀️ TODO We are working hard on the following items: Release ArXiv paper Release training scripts...

better_opts_attacks

May I have your attention? Breaking Fine-Tuning based Prompt Injection Defenses using Architecture-Aware Attacks This repository contains code to run the ASTRA and ASTRA++ attacks that break SecAlign++, SecAlign, StruQ. This repository also contains some examples of generated attacks and attack...

ASCENT

ASCENT First-Order Optimal Fine-Tuning with Recalibration for Safety–Utility Co-Enhancement ASCENT derives a first-order optimal safety calibration update and the corresponding safety-related structure, optimizes downstream task updates to preserve safety-compatible components while suppressing...

CVE-2026-110392

A vulnerability exists in Samsung Open Source QA-Board where improper neutralization of special elements used in an OS command leads to OS Command Injection . An unauthenticated attacker can exploit this flaw to execute arbitrary commands. The vulnerability is characterized by a CVSS 3.1 score of...

CVE-2026-110392 Samsung QA-Board — Unauthenticated OS command injection via output redo/tuning

Improper neutralization of special elements used in an OS command 'OS command injection' vulnerability in Samsung Open Source QA-Board allows : OS Command Injection...

Understanding and Enhancing Backdoor Persistency in LLM Agent Post-Training

Developers can build LLM agents by adapting third-party models through benign post-training. We study a supply-chain threat in which an attacker supplies a model with a backdoor: hidden behavior that produces malicious outputs when a particular input pattern appears. Focusing on...

Sleeping Secrets: How Fine-Tuning Reawakens Privacy Risks in Language Models

Beyond adapting Large Language Models LLMs to specialized applications, fine-tuning has recently been shown to recover private information that is no longer accessible through direct queries. Previous fine-tuning recovery attacks, however, require genuine private supervision drawn from the same...

Backdoor Purification for LoRA-Tuned LLMs Via Null-Space Projection

With the rapid adoption of large language models LLMs and parameter-efficient fine-tuning PEFT methods, the risk of backdoor attacks has become more severe. Existing backdoor purification methods typically rely on at least one of the strong assumptions, such as prior knowledge of triggers, access...

Selective Channel Restoration for Backdoored Vision-Language Models

Vision-language models VLMs exhibit strong multimodal capabilities but remain vulnerable to backdoors implanted through poisoned fine-tuning data. Existing defenses often require extensive parameter updates during fine-tuning or incur per-query overhead during inference. To address these...

Backdoor Mitigation in Decentralized LLM Fine-Tuning

Decentralized large language model LLM fine-tuning lets organizations collaboratively train a shared LLM on data they cannot pool, without a central coordinator. In every round, each node exchanges a trainable adapter with its neighbors over a communication graph, and then aggregates them. This...

SecureVibe: Making Vibe Coding More Secure

As vibe coding becomes increasingly capable and widespread, security vulnerabilities in even functionally correct solutions are a growing concern. When investigating functionally correct but insecure solutions, we find that the insecure agent is less than half as likely to conduct effective...

RAISE: Reinforcing Access Control Policy Synthesis in LLMs Via Symbolic Evaluation

Translating natural-language access-control requirements into policies requires careful reasoning about permissions, constraints, and exceptions, and even frontier LLMs often produce policies that violate the intended authorization semantics. We construct CedarInstruct, to our knowledge the first...

Astra Linux – Vulnerability in Linux 5.10, Linux, Linux 5.15

In the Linux kernel, the following vulnerabilities have been resolved: ALSA: hda/ca0132: fixed a buffer overflow issue in tuningctlset The tuningctlset function might cause a buffer overflow if it does not break the loop after matching A. static int tuningctlset... for i = 0; i TUNINGCTLSCOUNT; i...

Exploring Automated Vulnerability Identification in JavaScript Code Using Large Language Models

JavaScript powers approximately 98.8% of all websites, making vulnerabilities in its code a significant security risk, yet existing detection approaches such as Static Application Security Testing SAST tools often fail to identify many real-world vulnerabilities when applied to isolated code...