EUVD-2026-39791

Docling simplifies document processing by parsing diverse formats and providing integrations with the generative AI ecosystem. Prior to 2.94.0, the HTML backend has unsafe URI and path handling. This vulnerability is fixed in 2.94.0...

EUVD-2026-39790

Docling simplifies document processing by parsing diverse formats and providing integrations with the generative AI ecosystem. From 2.45.0 until 2.91.0, the METS-GBS backend's XML parsing and the input document format detection lacked security controls. An attacker could craft malicious METS-GBS...

GenAI Is Both Hunter and Hunted at Pwn2Own Berlin 2026

This year’s Pwn2Own competition in Berlin revealed just how much of the AI stack remains exposed -- and the gap between what these tools promise and what they can withstand point to the fragile security foundations underneath...

GenTI: Benchmarking LLMs for Autonomous IDPS Rule Generation for Unseen Attacks

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. Additionally, existing public datasets e.g., CICIDS2017, UNSW-NB15 focus on...

azure-ai-generative (>=1.0.0b1 <=1.0.0b3), azure-ai-resources (>=1.0.0b1 <=1.0.0b9) +30 more potentially affected by CVE-2026-4035 via mlflow-skinny (>=3.0.0 <=3.11.0rc0)

mlflow-skinny PYPI version =3.0.0, =1.0.0b1, =1.0.0b1, =0.1.0, =0.1.0, =2.5.0, =0.0.13, =7.1.1, =0.2.0, =0.2.1 and more Source cves: CVE-2026-4035 Source advisory: SNYK:PYTHON-MLFLOWSKINNY-17135850...

New Russia-Linked GREYVIBE Targets Ukraine with AI-Powered Cyberattacks

A previously undocumented threat actor dubbed GREYVIBE has been attributed to ongoing and persistent attacks targeting Ukraine and Ukraine-related entities since at least August 2025. GREYVIBE, per WithSecure, is assessed to be a Russian-speaking group operating broadly in the Russian time zone,...

azure-ai-generative (>=1.0.0b1 <=1.0.0b3), azure-ai-resources (>=1.0.0b1 <=1.0.0b9) +15 more potentially affected by CVE-2026-2651 via mlflow-skinny (>=3.0.0 <=3.0.1)

mlflow-skinny PYPI version =3.0.0, =1.0.0b1, =1.0.0b1, =0.1.0, =0.1.0, =2.5.0, =0.0.13, =3.0.0, =0.1.0, =0.1.4 and more Source cves: CVE-2026-2651 Source advisory: SNYK:PYTHON-MLFLOWSKINNY-16874026...

Integration of AI in Cybersecurity: Current Trends with a Focused Look at Intrusion Detection Applications

Artificial Intelligence AI is widely adopted today for its ability to detect patterns, automate tasks, and reduce time and cost across various applications. Its integration into Cybersecurity has garnered significant attention, particularly in areas such as intrusion detection, malware analysis,...

azure-ai-generative (>=1.0.0b1 <=1.0.0b3), azure-ai-resources (>=1.0.0b1 <=1.0.0b9) +15 more potentially affected by CVE-2026-2652 via mlflow-skinny (>=3.0.0 <=3.0.1)

mlflow-skinny PYPI version =3.0.0, =1.0.0b1, =1.0.0b1, =0.1.0, =0.1.0, =2.5.0, =0.0.13, =3.0.0, =0.1.0, =0.1.4 and more Source cves: CVE-2026-2652 Source advisory: SNYK:PYTHON-MLFLOWSKINNY-16698136...

From AI-Generated Content to Agentic Action: Security and Safety Threats in Generative AI

Generative AI systems are increasingly used not only to produce content but also to retrieve data, invoke tools, and execute actions. This work examines the security and safety implications of that shift across content-level, model-level, and agentic threats. We analyze how attacker access...

azure-ai-generative (>=1.0.0b1 <=1.0.0b3), azure-ai-resources (>=1.0.0b1 <=1.0.0b9) +15 more potentially affected by CVE-2026-2393 via mlflow-skinny (>=3.0.0 <=3.0.1)

mlflow-skinny PYPI version =3.0.0, =1.0.0b1, =1.0.0b1, =0.1.0, =0.1.0, =2.5.0, =0.0.13, =3.0.0, =0.1.0, =0.1.4 and more Source cves: CVE-2026-2393 Source advisory: SNYK:PYTHON-MLFLOWSKINNY-16642072...

Context-Aware Spear Phishing: Generative AI-Enabled Attacks against Individuals Via Public Social Media Data

We demonstrate how publicly available social-media data and generative AI GenAI can be misused to automate and scale highly personalized, context-aware spear-phishing campaigns. With minimal attacker effort, a small amount of public activity per target is sufficient for GenAI models to extract...

AI-Driven Security Alert Screening and Alert Fatigue Mitigation in Security Operations Centers: A Comprehensive Survey

Security alert screening is the downstream task of filtering, prioritizing, correlating, and contextualizing alerts for analyst attention in Security Operations Centers. This survey reviews artificial-intelligence-driven alert screening and alert-fatigue mitigation from 2015 to 2026. We synthesiz...

What Security and Privacy Transparency Users Need from Consumer-Facing Generative AI

Users increasingly rely on consumer-facing generative AI GenAI for tasks ranging from everyday needs to sensitive use cases. Yet, it remains unclear whether and how existing security and privacy S&P communications in GenAI tools shape users' adoption decisions and subsequent experiences...

Byte-Level Generative Predictions for Forensics Multimedia Carving

Digital forensic investigations often face significant challenges when recovering fragmented multimedia files that lack file system metadata. While traditional file carving relies on signatures and discriminative deep learning models for fragment classification, these methods cannot reconstruct o...

Understanding User Privacy Perceptions of GenAI Smartphones

GenAI smartphones, which natively embed generative AI at the system level, are transforming mobile interactions by automating a wide range of tasks and executing UI actions on behalf of users. Their superior capabilities rely on continuous access to sensitive and context-rich data, raising privac...

griptape 路径遍历漏洞

Griptape is an open-source generative AI application development framework created by Griptape. Version 0.19.4 of Griptape contains a path traversal vulnerability, which stems from incorrect handling of the parameter filename, potentially leading to path traversal attacks...

azure-ai-generative (>=1.0.0b1 <=1.0.0b3), azure-ai-resources (>=1.0.0b1 <=1.0.0b9) +15 more potentially affected by CVE-2026-0545 via mlflow-skinny (>=3.0.0 <=3.0.1)

mlflow-skinny PYPI version =3.0.0, =1.0.0b1, =1.0.0b1, =0.1.0, =0.1.0, =2.5.0, =0.0.13, =3.0.0, =0.1.0, =0.1.4 and more Source cves: CVE-2026-0545 Source advisory: SNYK:PYTHON-MLFLOWSKINNY-15922302...

GMA-SAWGAN-GP: A Novel Data Generative Framework to Enhance IDS Detection Performance

Intrusion Detection System IDS is often calibrated to known attacks and generalizes poorly to unknown threats. This paper proposes GMA-SAWGAN-GP, a novel generative augmentation framework built on a Self-Attention-enhanced Wasserstein GAN with Gradient Penalty WGAN-GP. The generator employs...

azure-ai-generative (>=1.0.0b1 <=1.0.0b3), azure-ai-resources (>=1.0.0b1 <=1.0.0b9) +30 more potentially affected by CVE-2025-15381 via mlflow-skinny (>=3.0.0 <=3.11.0rc0)

mlflow-skinny PYPI version =3.0.0, =1.0.0b1, =1.0.0b1, =0.1.0, =0.1.0, =2.5.0, =0.0.13, =7.1.1, =0.2.0, =0.2.1 and more Source cves: CVE-2025-15381 Source advisory: SNYK:PYTHON-MLFLOWSKINNY-15870197...