In this blog post, we’ll detail how attackers can exploit image scaling on Gemini CLI, Vertex AI Studio, Gemini’s web and API interfaces, Google Assistant, Genspark, and other production AI systems. We’ll also explain how to mitigate and defend against these attacks, and we’ll introduce Anamorpher, our open-source tool that lets you explore and generate these crafted images.
This post traces the decade-long evolution of Ruby Marshal deserialization exploits, demonstrating how security researchers have repeatedly bypassed patches and why fundamental changes to the Ruby ecosystem are needed rather than continued patch-and-hope approaches.
In my first month at Trail of Bits as an AI/ML security engineer, I found two remotely accessible memory corruption bugs in NVIDIA’s Triton Inference Server during a routine onboarding practice.
This post describes how many examples of MCP software store long-term API keys for third-party services in plaintext on the local filesystem, often with insecure, world-readable permissions.
This post describes attacks using ANSI terminal code escape sequences to hide malicious instructions to the LLM, leveraging the line jumping vulnerability we discovered in MCP.
This post explains how malicious MCP servers can exploit the Model Context Protocol to covertly exfiltrate entire conversation histories by injecting trigger phrases into tool descriptions, allowing for targeted data theft against specific organizations.
This post is about a vulnerability in the Model Context Protocol (MCP) called “Line Jumping,” where malicious servers can inject prompts through tool descriptions to manipulate AI model behavior without being explicitly invoked, effectively bypassing security measures designed to protect users.
