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HomeCyber SecurityIntel Discloses Max Severity Bug in Its AI Mannequin Compression Software program

Intel Discloses Max Severity Bug in Its AI Mannequin Compression Software program

Intel has disclosed a most severity vulnerability in some variations of its Intel Neural Compressor software program for AI mannequin compression.

The bug, designated as CVE-2024-22476, offers an unauthenticated attacker with a strategy to execute arbitrary code on Intel techniques working affected variations of the software program. The vulnerability is probably the most severe amongst dozens of flaws the corporate disclosed in a set of 41 safety advisories this week.

Improper Enter Validation

Intel recognized CVE-2024-22476 as stemming from improper enter validation, or a failure to correctly sanitize consumer enter. The chip maker has given the vulnerability a most rating of 10 on the CVSS scale as a result of the flaw is remotely exploitable with low complexity and has a excessive affect on information confidentiality, integrity, and availability. An attacker doesn’t require any particular privileges, and neither is consumer interplay required for an exploit to work.

The vulnerability impacts Intel Neural Compressor variations earlier than 2.5.0. Intel has advisable that organizations utilizing the software program improve to model 2.5.0 or later. Intel’s advisory indicated that the corporate realized of the vulnerability from an exterior safety researcher or entity whom the corporate didn’t determine.

Intel Neural Compressor is an open supply Python library that helps compress and optimize deep studying fashions for duties corresponding to laptop imaginative and prescient, pure language processing, suggestion techniques, and a wide range of different use circumstances. Methods for compression embody neural community pruning — or eradicating the least vital parameters; decreasing reminiscence necessities through course of name quantization; and distilling a bigger mannequin to a smaller one with related efficiency. The purpose with AI mannequin compression expertise is to assist allow the deployment of AI functions on numerous {hardware} gadgets, together with these with restricted or constrained computational energy, corresponding to cellular gadgets.

One Amongst Many

CVE-2024-22476 is definitely certainly one of two vulnerabilities in Intel’s Neural Compressor software program that it disclosed — and for which it launched a repair — this week. The opposite is CVE-2024-21792, a time-of-check-time-of-use (TOCTOU) flaw that would lead to data disclosure. Intel assessed the flaw at presenting solely a average threat as a result of, amongst different issues, it requires an attacker to have already got native, authenticated entry to a susceptible system to use it.

Along with the Neural Compressor flaws, Intel additionally disclosed 5 high-severity privilege escalation vulnerabilities in its UEFI firmware for server merchandise. Intel’s advisory listed all of the vulnerabilities (CVE-2024-22382; CVE-2024-23487; CVE-2024-24981; CVE-2024-23980; and CVE-2024-22095) as enter validation flaws, with severity scores starting from 7.2 to 7.5 on the CVSS scale.

Rising AI Vulnerabilities

The Neural Compressor vulnerabilities are examples of what safety analysts have not too long ago described because the increasing — however usually missed — assault floor that AI software program and instruments are creating at enterprise organizations. A variety of the safety issues round AI software program thus far have centered on the dangers in utilizing giant language fashions and LLM-enabled chatbots like ChatGPT. Over the previous yr, researchers have launched quite a few reviews on the susceptibility of those instruments to mannequin manipulation, jailbreaking, and several other different threats.

What has been considerably much less of a spotlight thus far has been the danger to organizations from vulnerabilities in a number of the core software program elements and infrastructure utilized in constructing and supporting AI merchandise and platforms. Researchers from Wiz, as an example, not too long ago discovered weaknesses within the extensively used HuggingFace platform that gave attackers a strategy to tamper with fashions within the registry or to comparatively simply add weaponized ones to it. A latest research commissioned by the UK’s Division for Science, Innovation and Know-how recognized quite a few potential cyber-risks to AI expertise at each life cycle state from the software program design section by means of improvement, deployment, and upkeep. The dangers embody a failure to do enough menace modeling and never accounting for safe authentication and authorization within the design section to code vulnerabilities, insecure information dealing with, insufficient enter validation, and a protracted record of different points.



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