Exploring AI in Steganography and Steganalysis: Trends, Clusters, and Sustainable Development Potential

Steganography and steganalysis are strongly related subjects of information security. Over the past decade, many powerful and efficient artificial intelligence AI - driven techniques have been designed and presented during research into steganography as well as steganalysis. This study presents a...

Introducing Spring AI Agents and Spring AI Bench

I'd like to introduce two new projects that are part of the Spring AI Community GitHub organization: Spring AI Agents, and Spring AI Bench. These two projects focus on using agentic coding tools—tools you likely already have in your enterprise. In 2025 AI coding agents have matured to the point...

CVE-2025-60932

Multiple stored cross-site scripting XSS vulnerabilities in the Current Goals function of HR Performance Solutions Performance Pro v3.19.17 allows attackers to execute arbitrary web scripts or HTML via a crafted payload injected into the Goal Name, Goal Notes, Action Step Name, Action Step...

EUVD-2025-35169

Multiple stored cross-site scripting XSS vulnerabilities in the Future Goals function of HR Performance Solutions Performance Pro v3.19.17 allows attackers to execute arbitrary web scripts or HTML via a crafted payload injected into the Goal Name, Goal Notes, Action Step Name, Action Step...

CVE-2025-60933

CVE-2025-60933 affects HR Performance Solutions Performance Pro v3.19.17. The vulnerability is stored XSS in the Future Goals function, allowing an attacker to inject arbitrary web scripts/HTML via crafted payloads into Goal Name, Goal Notes, Action Step Name, Action Step Description, Note Name, ...

HR Performance Solutions Performance Pro 安全漏洞

HR Performance Solutions Performance Pro is an employee performance management platform from HR Performance USA. A security vulnerability exists in Performance Pro version v3.19.17, which stems from improper handling of the Goal Name, Goal Notes, Action Step Name, Action Step Description, Note...

CVE-2025-60933

Multiple stored cross-site scripting XSS vulnerabilities in the Future Goals function of HR Performance Solutions Performance Pro v3.19.17 allows attackers to execute arbitrary web scripts or HTML via a crafted payload injected into the Goal Name, Goal Notes, Action Step Name, Action Step...

CVE-2025-60932

Multiple stored cross-site scripting XSS vulnerabilities in the Current Goals function of HR Performance Solutions Performance Pro v3.19.17 allows attackers to execute arbitrary web scripts or HTML via a crafted payload injected into the Goal Name, Goal Notes, Action Step Name, Action Step...

Agentic Misalignment: How LLMs Could Be Insider Threats

We stress-tested 16 leading models from multiple developers in hypothetical corporate environments to identify potentially risky agentic behaviors before they cause real harm. In the scenarios, we allowed models to autonomously send emails and access sensitive information. They were assigned only...

EUVD-2025-15371

Malicious code in bioql PyPI...

Malicious code in test-mlw2-goals-imago (npm)

The package test-mlw2-goals-imago was found to contain malicious code...

MAL-2025-35431 Malicious code in test-mlw2-goals-imago (npm)

The package test-mlw2-goals-imago was found to contain malicious code...

Simulation in Cybersecurity: Understanding Techniques, Applications, and Goals

Modeling and simulation are widely used in cybersecurity research to assess cyber threats, evaluate defense mechanisms, and analyze vulnerabilities. However, the diversity of application areas, the variety of cyberattacks scenarios, and the differing objectives of these simulations makes it...

Malicious code in goals-summary-widget (npm)

The package communicates with a domain associated with malicious activity...

MAL-2025-6724 Malicious code in goals-summary-widget (npm)

The package communicates with a domain associated with malicious activity...

SHADE-Arena: Evaluating Sabotage and Monitoring in LLM Agents

As Large Language Models LLMs are increasingly deployed as autonomous agents in complex and long horizon settings, it is critical to evaluate their ability to sabotage users by pursuing hidden objectives. We study the ability of frontier LLMs to evade monitoring and achieve harmful hidden goals...

One Patch to Rule Them All: Transforming Static Patches into Dynamic Attacks in the Physical World

Numerous methods have been proposed to generate physical adversarial patches PAPs against real-world machine learning systems. However, each existing PAP typically supports only a single, fixed attack goal, and switching to a different objective requires re-generating and re-deploying a new PAP...

A Hitchhiker'S Guide to Privacy-Preserving Cryptocurrencies: a Survey on Anonymity, Confidentiality, and Auditability

Cryptocurrencies and central bank digital currencies CBDCs are reshaping the monetary landscape, offering transparency and efficiency while raising critical concerns about user privacy and regulatory compliance. This survey provides a comprehensive and technically grounded overview of...

WASP: Benchmarking Web Agent Security against Prompt Injection Attacks

Autonomous UI agents powered by AI have tremendous potential to boost human productivity by automating routine tasks such as filing taxes and paying bills. However, a major challenge in unlocking their full potential is security, which is exacerbated by the agent's ability to take action on their...

Centralized Trust in Decentralized Systems: Unveiling Hidden Contradictions in Blockchain and Cryptocurrency

Blockchain technology promises to democratize finance and promote social equity through decentralization, but questions remain about whether current implementations advance or hinder these goals. Through a mixed-methods study combining semi-structured interviews with 13 diverse blockchain...