Red Hat AI Inference Server 3.4 vulnerabilities
3 known vulnerabilities in Red Hat AI Inference Server 3.4 from Red Hat. 3 are rated high or critical. Each entry lists the affected versions and the release that fixes it, where the vendor has published one.
Latest first
- 7.5 High severity
vllm: Improper Control of Generation of Code
vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.22.0, an assert-based security check in vLLM's activation function loading allows any unauthenticated attacker to achieve arbitrary code execution on the server by publishing
- 7.5 High severity
urllib3: Improper Handling of Highly Compressed Data (Data Amplification)
urllib3 is an HTTP client library for Python. From 2.6.0 to before 2.7.0, urllib3 could decompress the whole response instead of the requested portion (1) during the second HTTPResponse.read(amt=N) call when the response was decompressed using the official Bro
- 7.5 High severity
Pillow: Uncontrolled Resource Consumption
Pillow is a Python imaging library. Versions 10.3.0 through 12.1.1 did not limit the amount of GZIP-compressed data read when decoding a FITS image, making them vulnerable to decompression bomb attacks. A specially crafted FITS file could cause unbounded memor