AI Sec Watch

CVE-2024-48144 is a prompt injection vulnerability (tricking an AI by hiding instructions in its input) in Fusion Chat Chat AI Assistant Ask Me Anything v1.2.4.0 that allows attackers to craft a malicious message in the chatbox to steal all previous and future conversations between the user and the AI assistant. The vulnerability is caused by improper handling of special elements in user input (CWE-77, a weakness in command injection prevention).

CVE-2024-48141 is a prompt injection vulnerability (a technique where an attacker hides malicious instructions in text sent to an AI) in Zhipu AI CodeGeeX version 2.17.0's chatbox. An attacker can craft a message to trick the AI into leaking all previous and future chat conversations between the user and the assistant.

CVE-2024-48139 is a prompt injection vulnerability (a technique where attackers hide malicious instructions in messages sent to an AI) in Blackbox AI version 1.3.95 that allows attackers to steal all chat messages between a user and the AI by sending a specially crafted message. This vulnerability is classified as a command injection flaw (where attackers manipulate input to execute unintended commands).

Cursor is a code editor that uses AI to help with programming. Before September 27, 2024, attackers could trick Cursor's command generation feature into running harmful commands if a user imported a malicious website into the prompt and the attacker used prompt injection (hidden instructions in text that manipulate AI behavior) on that website. A server-side patch was released quickly to block dangerous characters, and Cursor version 0.42 added client-side protections and a new preview box setting that requires manual approval before commands run.

CVE-2024-49361 is a vulnerability in ACON, a machine learning library that performs adaptive correlation optimization. The vulnerability exists in how ACON validates input data, which could allow an attacker to bypass these checks and execute arbitrary code (run commands they shouldn't be able to run) on systems using ACON. Machine learning applications that accept user-provided data are at the highest risk, especially those running on production servers (live systems serving real users).

Gradio, an open-source Python package for building user interfaces, has a cross-site scripting vulnerability (XSS, where malicious code hidden in files runs in users' browsers) that affects servers allowing file uploads. Attackers can upload harmful HTML, JavaScript, or SVG files that execute when other users view or download them, potentially stealing data or compromising accounts.

Gradio, an open-source Python package for building demos, has a vulnerability where the connection between the FRP client and server (fast reverse proxy, a tool that exposes local applications to the internet) isn't encrypted when the `share=True` option is used. This means attackers can intercept and read files uploaded to the server or modify data being sent, putting sensitive information at risk for users sharing Gradio demos publicly online.

Gradio, an open-source Python package for building AI demos, has a race condition (a bug where two operations interfere with each other due to timing) in its configuration function that lets attackers change the backend URL. This could redirect users to a fake server to steal login credentials or uploaded files, especially affecting Gradio servers accessible over the internet.

Gradio, an open-source Python package for building prototypes, has a timing attack vulnerability (a security flaw where an attacker measures how long the system takes to respond to guess different values) in its analytics dashboard hash comparison. An attacker could exploit this by sending many requests and timing the responses to gradually figure out the correct hash and gain unauthorized access to the dashboard.