arXiv Machine Learning
Jun 18
Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution
arXiv:2606. 19023v1 Announce Type: cross Abstract: The growing reliance on pre-trained Machine Learning (ML) models has introduced new attack surfaces.
ML-Powered LDAP Reconnaissance Detection using Weak Supervision
arXiv:2606. 28917v1 Announce Type: new Abstract: Lightweight Directory Access Protocol (LDAP) is a protocol that allows users to query and modify Active Directory (AD) data.
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arXiv Machine Learning
Jul 7
VLMGuard: Bootstrapping Malicious Prompt Detectors from Unlabeled Vision-Language Prompts in the Wild
arXiv:2410. 00296v2 Announce Type: replace Abstract: Vision-language Models (VLMs) are essential for contextual understanding of both visual and textual information.
Hugging Face Trending Papers
Jun 17
Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution
The growing reliance on pre-trained Machine Learning (ML) models has introduced new attack surfaces. Recent vulnerabilities demonstrate that malicious behavior can be embedded within model artifacts, often bypassing existing defenses.
arXiv AI
Jun 2
Safe-FedLLM: Delving into the Safety of Federated Large Language Models
arXiv:2601. 07177v5 Announce Type: replace-cross Abstract: Federated learning (FL) addresses privacy and data-silo issues in the training of large language models (LLMs).
arXiv Machine Learning
Aug 7
Robust Context-Aware Detection of Malicious Instructions in Text
arXiv:2608. 05430v1 Announce Type: cross Abstract: The remarkable instruction-following ability of modern LLMs has enabled their practical use as the minds of agents that can autonomously complete increasingly complex tasks.
arXiv Machine Learning
2d ago
LLMs for Zero-Shot Threat Detection via Structured Risk Indicators
arXiv:2608. 16508v1 Announce Type: cross Abstract: We propose a two-stage large language model (LLM) framework for zero-shot detection of insider threats and advanced persistent threats (APTs) from heterogeneous security logs.
arXiv Machine Learning
Jun 30
A Hybrid Framework For Crypto-Ransomware Detection In Enterprise Shared Storage
arXiv:2606. 30586v1 Announce Type: cross Abstract: Most corporate workplace environments enforce policies and technical controls that limit the storage of sensitive data on client endpoints.
arXiv AI
Aug 11
Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection
arXiv:2608. 08100v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) enables large language models to classify network flows and generate human-readable incident reports by retrieving semantically similar historical traffic from a vector knowledge base.
arXiv AI
Jun 6
GenTI: Benchmarking LLMs for Autonomous IDPS Rule Generation for Unseen Attacks
arXiv:2606. 05844v1 Announce Type: cross Abstract: Rule-based Intrusion Detection and Prevention Systems (IDPS) offer precise attack detection as well as mitigation, however their manually crafted, signature-driven rules limit adaptability to emerging and zero-day threats.
arXiv AI
Jul 16
SingGuard-NSFA: Extensible Guardrails for Agentic AI via Generative Reasoning and Real-Time Classification
arXiv:2607. 13081v1 Announce Type: cross Abstract: We present nsfaguard, a guardrail framework for securing agentic AI systems against operational threats, such as prompt injection, sensitive information extraction, malicious code requests, dangerous tool misuse, and resource exhaustion.
Hugging Face Trending Papers
Jun 29
A Hybrid Framework For Crypto-Ransomware Detection In Enterprise Shared Storage
Most corporate workplace environments enforce policies and technical controls that limit the storage of sensitive data on client endpoints. Consequently, ransomware operators have evolved variants that expand their attack surface from local systems to network drives and shared storage resources.
Hugging Face Trending Papers
Jul 13
SingGuard-NSFA: Extensible Guardrails for Agentic AI via Generative Reasoning and Real-Time Classification
We present nsfaguard, a guardrail framework for securing agentic AI systems against operational threats, such as prompt injection, sensitive information extraction, malicious code requests, dangerous tool misuse, and resource exhaustion. We first introduce the NSFA taxonomy, which organizes 185 risk variants into a CIA-triad-grounded hierarchy and is cross-validated against three well-established OWASP guidelines.