Agentic AI Is Transforming Defense, But Only Secure IT Infrastructure Will Maximize It

Over the past several weeks, the cybersecurity community has been reminded how quickly frontier and agentic AI in defense networks can challenge our assumptions. When Anthropic's Claude Mythos model was made available to a limited set of organizations as a technical preview, it was reported that ...

SmartMES-Range

SmartMES Attack-Defense Drill Site The Smart Manufacturing En...

Membrane: A Self-Evolving Contrastive Safety Memory for LLM Agent Defense

Despite advances in safety alignment, large language models remain vulnerable to continuously evolving jailbreaks. Existing fine-tuned safety classifiers cannot adapt to these evolving attacks, while adaptive memory-based guardrails tend to over-refuse benign queries that resemble stored attacks...

Steering LLM Viewpoints through Fabricated Evidence Injection

As chatbots increasingly influence daily decision-making, their potential to produce misleading responses poses substantial risks to users. This paper investigates a critical cognitive vulnerability in LLMs: their tendency to uncritically trust external context when presented with fabricated...

Exploit for Stack-based Buffer Overflow in Microsoft

CVE-2026-41089 — SentinelCore Defensive Toolkit !Statushtt...

The Intersection of Encryption and AI

As part of their 20th Anniversary celebration, Dark Reading asked five cybersecurity industry leaders who wrote blogs or columns for them over the years to select their favorite piece and share their reflections on the topic today. This is my section. Renowned technologist and author Bruce Schnei...

AI Model Extraction Attacks: Bypassing Single-Client Assumptions in Defenses

Ensuring the protection of Artificial Intelligence AI models deployed in military Command and Control C2 systems and critical infrastructure is essential for maintaining information superiority. Model Extraction Attacks MEAs pose a significant threat, as they enable adversaries to replicate...

Backdoor Unlearning Generalization: A Path toward the Removal of Unknown Triggers in LLMs

Backdoor attacks in Large Language Models LLMs are a growing security concern, where models can generate adversary-chosen content. Existing defenses target backdoors one at a time and typically require knowledge of the trigger, leaving the defender at a structural disadvantage when unknown...

Operationalizing Cyber Attack Prediction: A Gap-Prioritized Framework with Dataset and Model Selection Guidelines

While AI and machine learning for cyber attack prediction have advanced, a critical gap persists between theoretical research and practical operational deployment. Building on Ankalaki et al. 2025, this paper provides a comprehensive analysis of 150+ benchmark datasets and 200+ studies to identif...

snyk-agentic-appsec-poc

Snyk Agentic AppSec POC Proof of concept demonstrating autono...

EUVD-2026-33597

A bug in the login redirect route in Apache Airflow allowed authenticated users to craft URLs that bypassed the issafeurl check, enabling redirection from a trusted Airflow domain to an attacker-controlled origin. Users are advised to upgrade to apache-airflow 3.2.2 or later. As a defense-in-dept...

Patcher: Post-Hoc Patching of Backdoored Large Language Models

Large language models remain vulnerable to jailbreak backdoor attacks, where adversaries poison safety alignment data to embed hidden triggers that bypass safety mechanisms. Existing defenses often require comprehensive attack information or multiple triggered examples, making them impractical wh...

Defenses and Enablers for Skill Injection Attacks on Terminal Based Agents

Large language model LLM agents increasingly rely on reusable skills i.e. documents describing task-specific procedures. However, this introduces a new attack surface for agents to manage. We study two complementary directions for this threat. First, we evaluate guardian-based defenses: an...

GHSA-Q3FM-4WCW-G57X vm2 setup-sandbox.js violates Defense Invariant #11 in stack-trace formatter

Summary defaultSandboxPrepareStackTrace in lib/setup-sandbox.js lines 605, 607 appends to a fresh sandbox-realm lines = via lineslines.length = value. This is the exact invariant-violating pattern that GHSA-9qj6-qjgg-37qq commit ca195f0, 2026-05-01 just patched in neutralizeArraySpeciesBatch and...

vm2 setup-sandbox.js violates Defense Invariant #11 in stack-trace formatter

Summary defaultSandboxPrepareStackTrace in lib/setup-sandbox.js lines 605, 607 appends to a fresh sandbox-realm lines = via lineslines.length = value. This is the exact invariant-violating pattern that GHSA-9qj6-qjgg-37qq commit ca195f0, 2026-05-01 just patched in neutralizeArraySpeciesBatch and...

Microsoft is named a Leader in the 2026 Gartner® Magic Quadrant™ for Endpoint Protection

As threats become more coordinated and faster to execute, endpoint protection has become the proving ground for modern defense. For the seventh consecutive time, Microsoft has been named a Leader in the 2026 Gartner® Magic Quadrant™ for Endpoint Protection. We believe this reflects both the...

Microsoft is named a Leader in the 2026 Gartner® Magic Quadrant™ for Endpoint Protection

As threats become more coordinated and faster to execute, endpoint protection has become the proving ground for modern defense. For the seventh consecutive time, Microsoft has been named a Leader in the 2026 Gartner® Magic Quadrant™ for Endpoint Protection. We believe this reflects both the...

PT-2026-47577

Summary defaultSandboxPrepareStackTrace in lib/setup-sandbox.js lines 605, 607 appends to a fresh sandbox-realm lines = via lineslines.length = value. This is the exact invariant-violating pattern that GHSA-9qj6-qjgg-37qq commit ca195f0, 2026-05-01 just patched in neutralizeArraySpeciesBatch and...

BadBone: Backdoor Attacks against Backbone Models in Visual Prompt Learning

Prompt learning is a new machine learning paradigm that has attracted ample attention due to its simplicity and proven efficacy. Despite its growing adoption, the security vulnerabilities associated with this paradigm remain underexplored. In this work, we take the first step to propose BadBone, ...

Stochastic Analysis of Cybersecurity Defense Strategies under Single Attack Scenario

This research presents a novel stochastic framework for proactive cybersecurity defense timing under a single attack scenario. The approach models the defense process as a continuous observation mechanism in which the defense instant and the subsequent observation slot follow independent...