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Background for this topic.
Exposure is the condition in which a system, service, credential, vulnerability, or sensitive information is accessible or discoverable by people or systems that should not reach it. In threat modeling, it describes an attack surface or loss of control—not proof that an attacker has succeeded. Examples include an internet-facing administration interface, cloud storage with unintended permissions, a secret committed to source code, or personal data sent to an unintended recipient. Its significance depends on what is exposed, who can reach it, and which protections remain.
The primary defense is exposure reduction: maintain an accurate asset inventory, remove unnecessary public access, enforce least-privilege permissions and strong authentication, patch externally reachable software, and revoke leaked credentials or secrets. Encryption can limit the value of exposed data, but does not correct an exposed access path. Continuous scanning and log review help identify changes and support rapid containment when exposure is discovered.
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Learn how to investigate AI activity in Microsoft 365 Copilot and Azure AI services using a structured, telemetry-driven approach. This playbook helps security teams reconstruct events, assess data exposure, and detect potential threats faster. The post Reconstructing AI activity in investigations appeared first on Microsoft Security Blog.
A multi-stage attack on Linux devices began with an exposed F5 BIG-IP edge appliance and pivoted to an internal Confluence server for credential theft and identity compromise. Learn how the threat actor attempted Kerberos relay and lateral movement, and how Microsoft Defender detected, blocked, and unraveled the attack. The post From edge appliance to enterprise compromise: Multi-stage Linux intrusion via F5 and Confluence appeared first on Microsoft Security Blog.
Exposed UIs, weak authentication, and risky defaults could turn cloud-native AI apps on Kubernetes into potential targets by threat actors. Learn how exploitable misconfigurations lead to RCE and data leaks. The post When configuration becomes a vulnerability: Exploitable misconfigurations in AI apps appeared first on Microsoft Security Blog.