PT-2025-31216 · Unknown · Langchain-Ai +1

Name of the Vulnerable Software and Affected Versions: langchain-ai version 0.3.51 Description: langchain-ai version 0.3.51 contains an indirect prompt injection vulnerability in the GmailToolkit component. This vulnerability allows attackers to execute arbitrary code and compromise the applicati...

CVE-2025-46059

CVE-2025-46059 involves langchain-ai v0.3.51 with an indirect prompt injection in the GmailToolkit component that could enable code execution via a crafted email. The supplier disputes the code-execution claim, noting the issue stemmed from user-written code not following LangChain security pract...

Hacker Added Prompt to Amazon Q to Erase Files and Cloud Data

A hacker injected a malicious prompt into Amazon Q via GitHub, aiming to delete user files and wipe AWS data, exposing a major security flaw...

PromptArmor: Simple yet Effective Prompt Injection Defenses

Despite their potential, recent research has demonstrated that LLM agents are vulnerable to prompt injection attacks, where malicious prompts are injected into the agent's input, causing it to perform an attacker-specified task rather than the intended task provided by the user. In this paper, we...

MAD-Spear: a Conformity-Driven Prompt Injection Attack on Multi-Agent Debate Systems

Multi-agent debate MAD systems leverage collaborative interactions among large language models LLMs agents to improve reasoning capabilities. While recent studies have focused on increasing the accuracy and scalability of MAD systems, their security vulnerabilities have received limited attention...

Prompt Injection 2.0: Hybrid AI Threats

Prompt injection attacks, where malicious input is designed to manipulate AI systems into ignoring their original instructions and following unauthorized commands instead, were first discovered by Preamble, Inc. in May 2022 and responsibly disclosed to OpenAI. Over the last three years, these...

The Dark Side of LLMs Agent-Based Attacks for Complete Computer Takeover

The rapid adoption of Large Language Model LLM agents and multi-agent systems enables unprecedented capabilities in natural language processing and generation. However, these systems have introduced unprecedented security vulnerabilities that extend beyond traditional prompt injection attacks. Th...

May I Have Your Attention? Breaking Fine-Tuning Based Prompt Injection Defenses Using Architecture-Aware Attacks

A popular class of defenses against prompt injection attacks on large language models LLMs relies on fine-tuning the model to separate instructions and data, so that the LLM does not follow instructions that might be present with data. There are several academic systems and production-level...

Defending against Prompt Injection with a Few DefensiveTokens

When large language model LLM systems interact with external data to perform complex tasks, a new attack, namely prompt injection, becomes a significant threat. By injecting instructions into the data accessed by the system, the attacker is able to override the initial user task with an arbitrary...

Inside the AI Threat Landscape: From Jailbreaks to Prompt Injections and Agentic AI Risks

AI has officially moved out of the novelty phase. What began with people messing around with LLM-powered GenAI tools for content creation has rapidly evolved into a complex web of agentic AI systems that form a critical part of the modern corporate landscape. However, this transformation has give...

Bridging AI and Software Security: a Comparative Vulnerability Assessment of LLM Agent Deployment Paradigms

Large Language Model LLM agents face security vulnerabilities spanning AI-specific and traditional software domains, yet current research addresses these separately. This study bridges this gap through comparative evaluation of Function Calling architecture and Model Context Protocol MCP deployme...

A Systematization of Security Vulnerabilities in Computer Use Agents

Computer Use Agents CUAs, autonomous systems that interact with software interfaces via browsers or virtual machines, are rapidly being deployed in consumer and enterprise environments. These agents introduce novel attack surfaces and trust boundaries that are not captured by traditional threat...

CVE-2025-53098

Roo Code is an AI-powered autonomous coding agent. The project-specific MCP configuration for the Roo Code agent is stored in the .roo/mcp.json file within the VS Code workspace. Because the MCP configuration format allows for execution of arbitrary commands, prior to version 3.20.3, it would hav...

CVE-2025-53097

Roo Code is an AI-powered autonomous coding agent. Prior to version 3.20.3, there was an issue where the Roo Code agent's searchfiles tool did not respect the setting to disable reads outside of the VS Code workspace. This means that an attacker who was able to inject a prompt into the agent coul...

CVE-2025-53098

Roo Code is an AI-powered autonomous coding agent. The project-specific MCP configuration for the Roo Code agent is stored in the .roo/mcp.json file within the VS Code workspace. Because the MCP configuration format allows for execution of arbitrary commands, prior to version 3.20.3, it would hav...

CVE-2025-53097

Roo Code is an AI-powered autonomous coding agent. Prior to version 3.20.3, there was an issue where the Roo Code agent's searchfiles tool did not respect the setting to disable reads outside of the VS Code workspace. This means that an attacker who was able to inject a prompt into the agent coul...

CVE-2025-53097 Roo Code extension vulnerable to Potential Information Leakage via JSON Schema

Roo Code is an AI-powered autonomous coding agent. Prior to version 3.20.3, there was an issue where the Roo Code agent's searchfiles tool did not respect the setting to disable reads outside of the VS Code workspace. This means that an attacker who was able to inject a prompt into the agent coul...

CVE-2025-53097

Roo Code extension (pre-3.20.3) allowed read access via the search_files tool outside the VS Code workspace, enabling potential data exposure if an attacker injects prompts. The attacker could exfiltrate data by writing to a JSON schema when the schema-fetch feature is enabled by default, trigger...

CVE-2025-53097 Roo Code extension vulnerable to Potential Information Leakage via JSON Schema

Roo Code is an AI-powered autonomous coding agent. Prior to version 3.20.3, there was an issue where the Roo Code agent's searchfiles tool did not respect the setting to disable reads outside of the VS Code workspace. This means that an attacker who was able to inject a prompt into the agent coul...

CVE-2025-53097 Roo Code extension vulnerable to Potential Information Leakage via JSON Schema

Roo Code is an AI-powered autonomous coding agent. Prior to version 3.20.3, there was an issue where the Roo Code agent's searchfiles tool did not respect the setting to disable reads outside of the VS Code workspace. This means that an attacker who was able to inject a prompt into the agent coul...