CVE-2026-42945

CVE-2026-42945 - NGINX Rift Vulnerability Analysis and Reproduction Overview CVE-2026-42945 codename "NGINX Rift" is a heap buffer overflow vulnerability in the NGINX ngxhttprewritemodule, with a CVSS v4 score of 9.2 Critical. Discovered by the depthfirst security research team in April 2026, thi...

IPI-exposure-signal

IPI Exposure Signal This is the code repository for our paper: Your Agentic LLMs Secretly Encode Latent Signals of Indirect Prompt-Injection Exposure. ArXiv version and paper link: https://arxiv.org/abs/2608.02657 This repository implements the probing pipeline for latent IPI-exposure signals:...

Parameters Efficient Language Model with Latent Cross-Attention for IoT Intrusion Detection

Language models have shown strong potential for intrusion detection, but their high memory and computational demands make them difficult to deploy in resource-constrained IoT environments. In this work, we propose a compact Transformer-based architecture that compresses the input into a small...

aegis-latent-core

Aegis Latent Core The evidence gateway for AI systems that must be explainable after the fact. Aegis sits between your application and one or more LLM providers. It admits, bounds, redacts, forwards and records governed calls, then emits portable cryptographic evidence that an independent verifie...

Phantomware: A Data Augmentation Framework for the Detection of Emerging Malware Campaigns

Detecting unseen malware variants remains a major challenge as malware families continuously evolve. This issue is exacerbated in data-scarce scenarios such as emerging malware campaigns, where only a few samples are available to train robust detectors. A common strategy is to proactively generat...

Safeguarding LLMs Via Model-Agnostic Latent Safety Signals from Dark Knowledge

LLMs have advanced rapidly, raising growing concerns about their safety. Recent work has proposed approaches to detect and defend against attacks including defenses at decoding stage that leverage models' hidden states. However, existing decoding-stage defenses suffer from two limitations. First,...

ContractLens: Latent Security Knowledge for Malicious Smart Contract Detection

Detecting malicious smart contracts is essential to safeguarding the Web3.0 ecosystem. However, existing auditing methods based on large language models LLMs largely rely on prompt engineering or attack-specific fine-tuning, while the internal representations that support malicious logic detectio...

Information Blackhole: Exploring Backdoor Mechanism in 3D Point Cloud Reconstruction

Point cloud autoencoders are fundamental components for 3D world representation and support many safety-critical downstream applications. Existing studies have extensively investigated backdoor attacks on point cloud classification, whereas backdoor attacks against point cloud autoencoders remain...

Stage-Supervised Latent Reasoning for Single-Shot JavaScript Deobfuscation

JavaScript obfuscation is widely used to protect code, but it also makes program analysis and security review substantially harder. Existing LLM-based deobfuscation methods usually treat the task as one-step translation, ignoring the staged structure of practical deobfuscation pipelines. This WIP...

Navigating the Latent Manifold: Proactive Concept Drift Adaptation for Resilient NIDS

Network intrusion detection systems NIDS are critical for cybersecurity, safeguarding services and data from potential attacks. However, existing AI-based NIDS often assume static data distributions and fail to handle concept drift, leading to degraded performance and increased false positives in...

PYSEC-2026-3745

opensslencrypt before 1.4.0 imports Python's non-cryptographic 'random' module Mersenne Twister PRNG at line 15 of opensslencrypt/modules/pqc.py. No direct calls to random. were present in the code, so no cryptographic operation is currently affected; however, the import creates a hazard that...

Malicious code in boxy-debugger (npm)

--- -= Per source details. Do not edit below this line.=- Source: amazon-inspector 0b6ac284218d923021a85994af157c45906518ab6651f7a164641f02a5bc4db2 boxy-debugger 35.3.4 presents itself as a debugger library, but requiring the package triggers platform.js, which reconstructs attacker-controlled...

Benign on Label, Malicious by Design: Clean-Label Dormant-To-Activated Backdoor Via Machine Unlearning with Removable Camouflage

Existing backdoor attacks often become effective immediately after backdoor implantation and may therefore be exposed before exploitation. Machine unlearning activated dormant backdoors mitigate such behavioral exposure by remaining inactive after training and becoming effective only after select...

Hybrid Latent-Structural Fusion (HLSF) for Cyber Anomaly Detection

Malicious anomalous activity detection is a fundamental challenge for cyber security systems. Both tensor decomposition under statistical framework with CANDECOMP-PARAFAC alternating Poisson regression CP-APR and normalizing flows have proven to be powerful unsupervised machine learning methods...

PI-Hunter: Automated Red-Teaming for Exposing and Localizing Prompt Injections

Large Language Models LLMs are rapidly evolving into agentic systems that interact with external tools and environments, introducing new security risks such as indirect prompt injection attacks through untrusted external sources. Existing defenses mainly focus on blocking malicious content at...

Backdoor Channels Hidden in Latent Space: Cryptographic Undetectability in Modern Neural Networks

Recent cryptographic results establish that neural networks can be backdoored such that no efficient algorithm can distinguish them from a clean model. These guarantees, however, have been confined to stylised architectures of limited practical relevance, leaving open whether comparable...

Tracing the Dynamics of Refusal: Exploiting Latent Refusal Trajectories for Robust Jailbreak Detection

Representation Engineering typically relies on static refusal vectors derived from terminal representations. We move beyond this paradigm, demonstrating that refusal is a dynamic and sparse process rather than a localized outcome. Using Causal Tracing, we uncover the Refusal Trajectory-a persiste...

PRoADS: Provably Secure and Robust Audio Diffusion Steganography with Latent Optimization and Backward Euler Inversion

This paper proposes PRoADS, a provably secure and robust audio steganographic framework based on audio diffusion models. As a generative steganography scheme, PRoADS embeds secret messages into the initial noise of diffusion models via orthogonal matrix projection. To address the reconstruction...

Robust Provably Secure Image Steganography Via Latent Iterative Optimization

We propose a robust and provably secure image steganography framework based on latent-space iterative optimization. Within this framework, the receiver treats the transmitted image as a fixed reference and iteratively refines a latent variable to minimize the reconstruction error, thereby improvi...

CVE-2026-24892 openITCOCKPIT has Unsafe Deserialization in openITCOCKPIT Changelog Handling

openITCOCKPIT is an open source monitoring tool built for different monitoring engines like Nagios, Naemon and Prometheus. openITCOCKPIT Community Edition 5.3.1 and earlier contains an unsafe PHP deserialization pattern in the processing of changelog entries. Serialized changelog data derived fro...