AI Sec Watch

LlamaIndex released version 0.14.9 with updates across multiple components, including bug fixes for vector stores (systems that store converted data in a format AI models can search), support for new AI models like Claude Opus 4.5 and GPT-5.1, and improvements to integrations with services like Azure, Bedrock, and Qdrant. The release addresses issues with memory management, async operations (non-blocking code that runs in parallel), and various database connectors.

vLLM (a tool for running large language models) versions before 0.11.1 have a critical security flaw where loading a model configuration can execute malicious code from the internet without the user's permission. An attacker can create a fake model that appears safe but secretly downloads and runs harmful code from another location, even when users try to block remote code by setting trust_remote_code=False (a security setting meant to prevent exactly this).

The Center for AI Safety launched an AI Dashboard that evaluates frontier AI models (the most advanced AI systems currently available) on capability and safety benchmarks, ranking them across text, vision, and risk categories. The Risk Index specifically measures how likely models are to exhibit dangerous behaviors like dual-use biology assistance (helping with harmful biological research), jailbreaking vulnerability (susceptibility to tricks that bypass safety features), overconfidence, deception, and harmful actions, with Claude Opus 4.5 currently scoring safest at 33.6 on a 0-100 scale (lower is safer). The dashboard also tracks industry progress toward broader automation milestones like AGI (artificial general intelligence, systems that can perform any intellectual task) and self-driving vehicles.

AI-generated image forgeries created by tools like GANs (generative adversarial networks, AI models that create fake images) are hard to detect reliably, especially when facing new types of fakes or noisy images. Researchers found that forgery detectors fail because of frequency bias (a tendency to focus on certain patterns in image data while ignoring others), and they developed a frequency alignment method that can either attack these detectors or strengthen them by removing differences between real and fake images in how they look at the frequency level.

LibreChat, a ChatGPT alternative with extra features, had a vulnerability in versions before 0.8.1-rc2 where an authenticated user could exploit the "Actions" feature by uploading malicious OpenAPI specs (interface documents that describe how to connect to external services) to perform SSRF (server-side request forgery, where the server itself is tricked into accessing restricted URLs on the attacker's behalf). This could allow attackers to reach sensitive services like cloud metadata endpoints that are normally hidden from regular users.

Keras version 3.11.3 has a path traversal vulnerability (a security flaw where attackers can write files outside the intended directory) in the keras.utils.get_file() function when extracting tar archives (compressed file formats). The function fails to properly validate file paths during extraction, allowing an attacker to write files anywhere on the system, potentially compromising it or executing malicious code.

The AI ChatBot with ChatGPT and Content Generator plugin for WordPress (versions up to 2.7.0) has a missing authorization check (a security control that verifies a user has permission to perform an action) in its 'ays_chatgpt_save_wp_media' function, allowing unauthenticated attackers to upload media files without logging in. This vulnerability affects all versions through 2.7.0.

CVE-2025-13378 is a vulnerability in the AI ChatBot with ChatGPT and Content Generator plugin for WordPress that allows SSRF (server-side request forgery, where an attacker tricks a server into making unwanted network requests on their behalf). The vulnerability exists in the plugin code, with references to affected code in versions 2.6.9 and earlier.

Ray, an AI compute engine, had a critical vulnerability before version 2.52.0 that allowed attackers to run code on a developer's computer (RCE, or remote code execution) through Firefox and Safari browsers. The vulnerability exploited a weak security check that only looked at the User-Agent header (a piece of information browsers send to websites) combined with DNS rebinding attacks (tricks that redirect browser requests to unexpected servers), allowing attackers to compromise developers who visited malicious websites or ads.