As these identities are increasingly implemented across Azure services, they present an expanding attack surface that may allow adversaries to pivot across environments, gain unauthorized access to Microsoft Graph, and extract sensitive data from various Azure resources. Beyond detection, the research also details practical guidance for incident investigation and response, including cross-correlation techniques between Azure Sign-in logs, Activity logs, and Microsoft Graph telemetry to trace the full scope of potential compromises. This high-fidelity detection method identifies when a managed identity makes anomalously high numbers of requests to Microsoft Graph API endpoints – behavior consistent with reconnaissance activity by threat actors who have gained unauthorized access to MI tokens. By providing these detection methodologies, security teams gain vital capabilities to identify potential compromises before attackers can fully exploit their access to cloud environments and sensitive resources. Cybersecurity experts have unveiled sophisticated techniques to identify potential abuse of Azure Managed Identities (MIs), addressing a critical but often overlooked security concern in cloud environments. Azure MIs streamline credential management by eliminating the need for manual secret handling, yet this convenience creates new attack vectors that sophisticated threat actors can exploit to escalate privileges and access sensitive resources. These queries range from high-fidelity detections, such as identifying explicit token requests from virtual machines, to broader behavioral analyses that flag when MIs access unusual resources or exhibit anomalous authentication patterns. This detection approach proves particularly effective because legitimate MIs typically display predictable, limited request patterns to Graph resources, making anomalous enumeration attempts stand out. Hunters researchers noted that while MIs offer significant security advantages by eliminating static credentials, their potential misuse can be particularly damaging since they operate with the implicit trust of Azure’s authentication framework. The query establishes behavioral thresholds by analyzing request patterns, flagging cases where managed identities make suspicious numbers of distinct calls to the Graph API within a short timeframe. The techniques, documented in a comprehensive research paper by Team Axon, focus on identifying unauthorized access and malicious use of MIs rather than just detecting their existence. The research builds upon previous work, particularly Karl Fossaen’s DEF CON 32 talk titled “Identity Theft is Not a Joke, Azure!” which initially raised awareness around MI abuse vectors. Cyber Security News is a Dedicated News Platform For Cyber News, Cyber Attack News, Hacking News & Vulnerability Analysis.
This Cyber News was published on cybersecuritynews.com. Publication date: Wed, 14 May 2025 13:35:04 +0000