AgenticSCR: An Autonomous Agentic Secure Code Review for Immature Vulnerabilities Detection

Secure code review is critical at the pre-commit stage, where vulnerabilities must be caught early under tight latency and limited-context constraints. Existing SAST-based checks are noisy and often miss immature, context-dependent vulnerabilities, while standalone Large Language Models LLMs are...

From runtime risk to real‑time defense: Securing AI agents

AI agents, whether developed in Microsoft Copilot Studio or on alternative platforms, are becoming a powerful means for organizations to create custom solutions designed to enhance productivity and automate organizational processes by seamlessly integrating with internal data and systems. From a...

EUVD-2025-28908

Malicious code in bioql PyPI...

Exploit Tool Invocation Prompt for Tool Behavior Hijacking in LLM-Based Agentic System

LLM-based agentic systems leverage large language models to handle user queries, make decisions, and execute external tools for complex tasks across domains like chatbots, customer service, and software engineering. A critical component of these systems is the Tool Invocation Prompt TIP, which...

Improving LLM Agents with Reinforcement Learning on Cryptographic CTF Challenges

Large Language Models LLMs still struggle with the structured reasoning and tool-assisted computation needed for problem solving in cybersecurity applications. In this work, we introduce "random-crypto", a cryptographic Capture-the-Flag CTF challenge generator framework that we use to fine-tune a...

Network Reconnaissance & Vulnerability Assessment Tool: ReconScan

Network Reconnaissance & Vulnerability Assessment Tool The project currently consists of two major components: a script invoking and aggregating the results of existing tools, and a second script for automated analysis of the aforementioned results from the perspective of exploitability. In terms...