-cascade-scan

cascade-scan AI Agent security evaluation framework — autom...

AI Agent Security: Automating Workflow Without Creating Prompt Injection or Data Leak Risks

AI agent security starts with a simple fact: the more authority an agent has, the tighter its access…...

Agent Security Is a Systems Problem

We take the position that agent security must be approached as a systems problem: the AI model powering the agent must be treated as an untrusted component, and security invariants must be enforced at the system level. Through this lens, efforts to increase model robustness the dominant viewpoint...

Architecture Matters for Multi-Agent Security

Multi-agent systems MAS, composed of networks of two or more autonomous AI agents, have become increasingly popular in production deployments, yet introduce security risks that do not arise in single-agent settings. Even if individual agents exhibit robust security, architectural decisions...

Ghost in the Agent: Redefining Information Flow Tracking for LLM Agents

Autonomous Large Language Model LLM agents are increasingly deployed to conduct complex tasks by interacting with external tools, APIs, and memory stores. However, processing untrusted external data exposes these agents to severe security threats, such as indirect prompt injection and unauthorize...

Towards Modeling Cybersecurity Behavior of Humans in Organizations

We undertake a comprehensive and structured synthesis of the drivers of human behavior in cybersecurity, focusing specifically on people within organizations i.e., especially employees in companies, and integrate key concepts such as awareness, security culture, and usability into a coherent...

Targeted Bit-Flip Attacks on LLM-Based Agents

Targeted bit-flip attacks BFAs exploit hardware faults to manipulate model parameters, posing a significant security threat. While prior work targets single-step inference models e.g., image classifiers, LLM-based agents with multi-stage pipelines and external tools present new attack surfaces,...

Extending the Formalism and Theoretical Foundations of Cryptography to AI

Recent progress in Large Language Models LMs has enabled the development of autonomous LM-based agents capable of executing complex tasks with minimal supervision. These agents have started to be integrated into systems with significant autonomy and authority. The security community has been...

GitGuardian Raises $50M Series C to Address Non-Human Identities Crisis and AI Agent Security Gap

New York, NY, 11th February 2026, CyberNewswire...

Security Threat Modeling for Emerging AI-Agent Protocols: A Comparative Analysis of MCP, A2A, Agora, and ANP

The rapid development of the AI agent communication protocols, including the Model Context Protocol MCP, Agent2Agent A2A, Agora, and Agent Network Protocol ANP, is reshaping how AI agents communicate with tools, services, and each other. While these protocols support scalable multi-agent...

A new era of agents, a new era of posture

The rise of AI Agents marks one of the most exciting shifts in technology today. Unlike traditional applications or cloud resources, these agents are not passive components- they reason, make decisions, invoke tools, and interact with other agents and systems on behalf of users. This autonomy...

Systems Security Foundations for Agentic Computing

This paper articulates short- and long-term research problems in AI agent security and privacy, using the lens of computer systems security. This approach examines end-to-end security properties of entire systems, rather than AI models in isolation. While we recognize that hardening a single mode...

A2AS: Agentic AI Runtime Security and Self-Defense

The A2AS framework is introduced as a security layer for AI agents and LLM-powered applications, similar to how HTTPS secures HTTP. A2AS enforces certified behavior, activates model self-defense, and ensures context window integrity. It defines security boundaries, authenticates prompts, applies...

EUVD-2018-10533

Malware in sbrugna...

EUVD-2021-13693

Malware in sbrugna...

EUVD-2020-6179

Malware in sbrugna...

EUVD-2017-2336

Malware in sbrugna...

EUVD-2025-18279

Malicious code in bioql PyPI...

EUVD-2022-28865

Malicious code in bioql PyPI...

Azure File Sync Agent v18.3 Release – August 2025 (KB5063613)

Security Update for Azure File Sync agent version 18.3.0.0. For more details, see the associated Microsoft Knowledge Base article...