{"description":"Trending threats, MITRE ATT\u0026CK coverage, and detection metadata — refreshed continuously.","feed_url":"https://feed.craftedsignal.io/tags/airdrop/","home_page_url":"https://feed.craftedsignal.io/","items":[{"_cs_actors":[],"_cs_cves":[],"_cs_exploited":false,"_cs_products":[],"_cs_severities":["low"],"_cs_tags":["data-exfiltration","macos","airdrop"],"_cs_type":"advisory","_cs_vendors":[],"content_html":"\u003cp\u003eThis detection identifies potential data exfiltration attempts via Apple\u0026rsquo;s Airdrop feature. A machine learning job monitors the volume of data transferred to external devices and flags unusual spikes. While Airdrop facilitates legitimate file sharing between Apple devices, it can be abused by malicious actors to exfiltrate sensitive data. This rule leverages the \u0026ldquo;ded_high_bytes_written_to_external_device_airdrop_ea\u0026rdquo; machine learning job and requires the Data Exfiltration Detection integration to be installed, along with network and file events collected by Elastic Defend and Network Packet Capture (for network events only). The rule is designed to detect anomalies in data transfer patterns, providing early warning of potential data breaches.\u003c/p\u003e\n\u003ch2 id=\"attack-chain\"\u003eAttack Chain\u003c/h2\u003e\n\u003col\u003e\n\u003cli\u003eAttacker gains initial access to a macOS system within the target network.\u003c/li\u003e\n\u003cli\u003eAttacker identifies sensitive data stored on the compromised system.\u003c/li\u003e\n\u003cli\u003eAttacker uses Airdrop to initiate a transfer of the identified data to a nearby device.\u003c/li\u003e\n\u003cli\u003eThe receiving device is controlled by the attacker and configured to accept Airdrop transfers.\u003c/li\u003e\n\u003cli\u003eA large volume of data is transferred via Airdrop, triggering the machine learning detection.\u003c/li\u003e\n\u003cli\u003eThe data is received by the attacker, completing the exfiltration process.\u003c/li\u003e\n\u003cli\u003eThe attacker may attempt to cover their tracks by deleting files or logs related to the Airdrop transfer.\u003c/li\u003e\n\u003c/ol\u003e\n\u003ch2 id=\"impact\"\u003eImpact\u003c/h2\u003e\n\u003cp\u003eSuccessful exploitation can lead to the unauthorized disclosure of sensitive data. The impact depends on the nature of the exfiltrated data, potentially leading to financial loss, reputational damage, or legal repercussions. The severity is relatively low as it depends on the data being transferred.\u003c/p\u003e\n\u003ch2 id=\"recommendation\"\u003eRecommendation\u003c/h2\u003e\n\u003cul\u003e\n\u003cli\u003eInstall the Data Exfiltration Detection integration in Elastic, including the preconfigured anomaly detection jobs, as required by the rule setup instructions to enable the machine learning detection (Data Exfiltration Detection integration).\u003c/li\u003e\n\u003cli\u003eInvestigate alerts generated by the \u0026ldquo;Spike in Bytes Sent to an External Device via Airdrop\u0026rdquo; rule, focusing on identifying the involved device, user, and the nature of the transferred data (Spike in Bytes Sent to an External Device via Airdrop).\u003c/li\u003e\n\u003cli\u003eImplement additional monitoring on the affected device and similar devices to detect any further anomalous Airdrop activities, as mentioned in the response and remediation steps (Spike in Bytes Sent to an External Device via Airdrop).\u003c/li\u003e\n\u003c/ul\u003e\n","date_modified":"2024-01-03T15:30:00Z","date_published":"2024-01-03T15:30:00Z","id":"/briefs/2024-01-airdrop-exfiltration/","summary":"A machine learning job has detected a spike in bytes of data written to an external device via Airdrop, potentially indicating illicit data copying or transfer activities.","title":"Spike in Bytes Sent to an External Device via Airdrop","url":"https://feed.craftedsignal.io/briefs/2024-01-airdrop-exfiltration/"}],"language":"en","title":"CraftedSignal Threat Feed — Airdrop","version":"https://jsonfeed.org/version/1.1"}