MemMorph: Tool Hijacking in LLM Agents Via Memory Poisoning

LLM-driven agents are capable of selecting external tools to complete users' tasks. However, attackers could compromise such process, steering agents toward inappropriate/wrong tools and enabling malicious actions. Most existing attacks primarily manipulate the tool metadata, which is easily...

The Hidden Cost of Cybersecurity Specialization: Losing Foundational Skills

Cybersecurity has changed fast. Roles are more specialized, and tooling is more advanced. On paper, this should make organizations more secure. But in practice, many teams struggle with the same basic problems they faced years ago: unclear risk priorities, misaligned tooling decisions, and...

Gaming Tool Preferences in Agentic LLMs

Large language models LLMs can now access a wide range of external tools, thanks to the Model Context Protocol MCP. This greatly expands their abilities as various agents. However, LLMs rely entirely on the text descriptions of tools to decide which ones to use--a process that is surprisingly...