Assessing Automated Prompt Injection Attacks in Agentic Environments

Indirect prompt injection poses a critical threat to LLM agents that interact with untrusted external data, yet automated attack methods--proven effective for jailbreaking--remain underexplored in realistic agentic settings. We present a comprehensive empirical evaluation of automated prompt...

RedEdit: Agentic Red-Teaming of Image Safety Classifiers Via MCTS-Guided Photo-Editing

Image safety classifiers serve as a critical component of contemporary content moderation systems on the internet. However, their resilience against user-style malicious image editing remains underexplored. Such behaviors are highly prevalent in daily scenarios but difficult to fully reproduce. T...

Most Remediation Programs Never Confirm the Fix Actually Worked

Security teams have never had better visibility into their environments and never been worse at confirming what they fix stays fixed. Mandiant's M-Trends 2026 report puts the mean time to exploit at an estimated negative seven days. The Verizon 2025 DBIR puts median time to remediate edge device...

ADAM: A Systematic Data Extraction Attack on Agent Memory Via Adaptive Querying

Large Language Model LLM agents have achieved rapid adoption and demonstrated remarkable capabilities across a wide range of applications. To improve reasoning and task execution, modern LLM agents would incorporate memory modules or retrieval-augmented generation RAG mechanisms, enabling them to...

Vulnerability Detection with Interprocedural Context in Multiple Languages: Assessing Effectiveness and Cost of Modern LLMs

Large Language Models LLMs have been a promising way for automated vulnerability detection. However, most prior studies have explored the use of LLMs to detect vulnerabilities only within single functions, disregarding those related to interprocedural dependencies. These studies overlook...

Your Agent, Their Asset: A Real-World Safety Analysis of OpenClaw

OpenClaw, the most widely deployed personal AI agent in early 2026, operates with full local system access and integrates with sensitive services such as Gmail, Stripe, and the filesystem. While these broad privileges enable high levels of automation and powerful personalization, they also expose...

A Defender-Attacker-Defender Model for Optimizing the Resilience of Hospital Networks to Cyberattacks

Considering the increasing frequency of cyberattacks affecting multiple hospitals simultaneously, improving resilience at a network level is essential. Various countermeasures exist to improve resilience against cyberattacks, such as deploying controls that strengthen IT infrastructures to limit...

Emoji-Based Jailbreaking of Large Language Models

Large Language Models LLMs are integral to modern AI applications, but their safety alignment mechanisms can be bypassed through adversarial prompt engineering. This study investigates emoji-based jailbreaking, where emoji sequences are embedded in textual prompts to trigger harmful and unethical...

On the Effectiveness of Instruction-Tuning Local LLMs for Identifying Software Vulnerabilities

Large Language Models LLMs show significant promise in automating software vulnerability analysis, a critical task given the impact of security failure of modern software systems. However, current approaches in using LLMs to automate vulnerability analysis mostly rely on using online API-based LL...

Evaluating LLMs for One-Shot Patching of Real and Artificial Vulnerabilities

Automated vulnerability patching is crucial for software security, and recent advancements in Large Language Models LLMs present promising capabilities for automating this task. However, existing research has primarily assessed LLMs using publicly disclosed vulnerabilities, leaving their...

How BAS Helps Threat Exposure Management: A Complete Guide

Your vulnerability scanner just produced a report with hundreds of "critical" CVEs. Now what? For most security teams, this is where the guessing game begins. You know you can't fix everything at once, so you're forced to make tough calls based on CVSS scores and gut feelings, all while hoping yo...

STAC: When Innocent Tools Form Dangerous Chains to Jailbreak LLM Agents

As LLMs advance into autonomous agents with tool-use capabilities, they introduce security challenges that extend beyond traditional content-based LLM safety concerns. This paper introduces Sequential Tool Attack Chaining STAC, a novel multi-turn attack framework that exploits agent tool use. STA...

Can Codeless Testing Tools Detect Common Security Vulnerabilities?

Learn what Codeless Testing Tools are and how effective they are in detecting common security vulnerabilities, along with understanding their strengths and limitations...

Trend Vision One™ Email Security Raises the Standard

Learn all the new aspects of Trend Vision One™ Email Security and how it's raising the standard of effectiveness for the industry...

Why SIEM Rules Fail and How to Fix Them: Insights from 160 Million Attack Simulations

Security Information and Event Management SIEM systems act as the primary tools for detecting suspicious activity in enterprise networks, helping organizations identify and respond to potential attacks in real time. However, the new Picus Blue Report 2025 , based on over 160 million real-world...

When Developer Aid Becomes Security Debt: a Systematic Analysis of Insecure Behaviors in LLM Coding Agents

LLM-based coding agents are rapidly being deployed in software development, yet their security implications remain poorly understood. These agents, while capable of accelerating software development, may inadvertently introduce insecure practices. We conducted the first systematic security...

The Democratization of Phishing: Popularity of PhaaS platforms on the rise

The Democratization of Phishing: Popularity of PhaaS Platforms on the Rise By Ryan Slaney · June 30, 2025 The phishing industry is being profoundly reshaped by the surge of Phishing-as-a-Service PhaaS platforms. These accessible, often Artificial Intelligence AI-powered, offerings are democratizi...

Anti-Phishing Training Does Not Work: a Large-Scale Empirical Assessment of Multi-Modal Training Grounded in the NIST Phish Scale

Social engineering attacks using email, commonly known as phishing, are a critical cybersecurity threat. Phishing attacks often lead to operational incidents and data breaches. As a result, many organizations allocate a substantial portion of their cybersecurity budgets to phishing awareness...

Control Validation: The Missing Link in Security Assurance

Running short on time but still want to stay in the know? Well, we’ve got you covered! We’ve condensed all the key takeaways into a handy audio summary. Our AI-driven podcasts are fit for on the go. Click right here to hear it all on CAASM & CDMB Inefficiencies! You've got the prettiest security...

AI Safety Vs. AI Security: Demystifying the Distinction and Boundaries

Artificial Intelligence AI is rapidly being integrated into critical systems across various domains, from healthcare to autonomous vehicles. While its integration brings immense benefits, it also introduces significant risks, including those arising from AI misuse. Within the discourse on managin...