AI-as-a-Service | Breaking Cybersecurity News | The Hacker News

Artificial Intelligence (AI) company Hugging Face on Friday disclosed that it detected unauthorized access to its Spaces platform earlier this week. "We have suspicions that a subset of Spaces' secrets could have been accessed without authorization," it said in an advisory. Spaces offers a way for users to create, host, and share AI and machine learning (ML) applications. It also functions as a discovery service to look up AI apps made by other users on the platform. In response to the security event, Hugging Space said it is taking the step of revoking a number of HF tokens present in those secrets and that it's notifying users who had their tokens revoked via email. "We recommend you refresh any key or token and consider switching your HF tokens to fine-grained access tokens which are the new default," it added. Hugging Face, however, did not disclose how many users are impacted by the incident, which is currently under further investigation. It has

Cybersecurity researchers have discovered a critical security flaw in an artificial intelligence (AI)-as-a-service provider  Replicate  that could have allowed threat actors to gain access to proprietary AI models and sensitive information. "Exploitation of this vulnerability would have allowed unauthorized access to the AI prompts and results of all Replicate's platform customers," cloud security firm Wiz  said  in a report published this week. The issue stems from the fact that AI models are typically packaged in formats that allow arbitrary code execution, which an attacker could weaponize to perform cross-tenant attacks by means of a malicious model. Replicate makes use of an open-source tool called  Cog  to containerize and package machine learning models that could then be deployed either in a self-hosted environment or to Replicate. Wiz said that it created a rogue Cog container and uploaded it to Replicate, ultimately employing it to achieve remote code exec

Shadow apps, a segment of Shadow IT, are SaaS applications purchased without the knowledge of the security team. While these applications may be legitimate, they operate within the blind spots of the corporate security team and expose the company to attackers.  Shadow apps may include instances of software that the company is already using. For example, a dev team may onboard their own instance of GitHub to keep their work separate from other developers. They might justify the purchase by noting that GitHub is an approved application, as it is already in use by other teams. However, since the new instance is used outside of the security team's view, it lacks governance. It may store sensitive corporate data and not have essential protections like MFA enabled, SSO enforced, or it could suffer from weak access controls. These misconfigurations can easily lead to risks like stolen source code and other issues. Types of Shadow Apps  Shadow apps can be categorized based on their interac

New research has found that artificial intelligence (AI)-as-a-service providers such as Hugging Face are susceptible to two critical risks that could allow threat actors to escalate privileges, gain cross-tenant access to other customers' models, and even take over the continuous integration and continuous deployment (CI/CD) pipelines. "Malicious models represent a major risk to AI systems, especially for AI-as-a-service providers because potential attackers may leverage these models to perform cross-tenant attacks," Wiz researchers Shir Tamari and Sagi Tzadik  said . "The potential impact is devastating, as attackers may be able to access the millions of private AI models and apps stored within AI-as-a-service providers." The development comes as machine learning pipelines have emerged as a brand new supply chain attack vector, with repositories like Hugging Face becoming an attractive target for staging adversarial attacks designed to glean sensitive infor