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	"sha1_hash": "d8563fa877bf29a223f91b8c74c649e4b5f85956",
	"title": "Understanding BumbleBee: BumbleBee’s malware configuration and clusters",
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	"authors": "",
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	"plain_text": "Understanding BumbleBee: BumbleBee’s malware configuration\r\nand clusters\r\nBy VMRay Labs\r\nPublished: 2023-08-18 · Archived: 2026-04-05 22:37:17 UTC\r\nIntroduction\r\nIn our ongoing exploration of the enigmatic BumbleBee malware, we’ve previously dissected its delivery\r\ntechniques, unraveled its malicious behavior, and delved into the ever-evolving nature of its evasion techniques.\r\nNow, in this latest installment, we uncover the secrets hidden within the BumbleBee’s malware configuration,\r\nshedding light on the methods it employs to safeguard its operations. Moreover, we’ll take a comprehensive look\r\ninto the clusters, where we’ll connect the dots between different BumbleBee samples and missions.\r\nJoin us as we explore BumbleBee’s operations, revealing the hidden patterns that drive this malware’s malicious\r\nactivities.\r\nBumbleBee Blog Series – 3\r\nDOWNLOAD THE E-BOOK\r\nConfig Extractor\r\nWe have identified a number of differences between BumbleBee samples in terms of functionality but also how\r\nthe config is processed. While some samples use no encryption at all, some use the RC4 algorithm to encrypt the\r\nconfiguration data.\r\nTo determine the encryption algorithm, we first had to locate the encrypted data as well as where it is further\r\nprocessed which allowed us to locate one function that looked promising. There are usually a few methods to\r\nidentify which encryption algorithm a function implements. First, one can try to find magic constants strongly\r\nassociated with certain encryption algorithms. For example, AES uses a so-called S-box filled with fixed constants\r\nto perform substitutions. These constants can easily be used to identify the algorithm. In BumbleBee’s case, no\r\nsuch unique constants could be found. However, one commonly used encryption algorithm by malware, RC4,\r\nincidentally also contains no unique constants, making this a likely candidate.\r\nIn addition to the approach involving constants, another method is to compare the decompiled function to a list of\r\nknown encryption algorithms, which in our case showed striking similarities to RC4 (see Figure 1).\r\nhttps://www.vmray.com/cyber-security-blog/understanding-bumblebee-the-malware-configuration-and-clusters/\r\nPage 1 of 6\n\nFinally, one can confirm the findings by decrypting the encrypted content via RC4 (using the extracted key) and\r\ninvestigating the output, e.g., via CyberChef or similar tools. While this confirmed our findings in this case, this\r\nmethod is of limited value if the malware authors decide to manipulate the encryption algorithm.\r\nInvestigating the decrypted configuration, we determined that BumbleBee generally has these configuration fields\r\nthat we can export (see Figure 2):\r\nAn RC4 key, if the config is encrypted\r\nA mission ID which can be freely set by the attacker, e.g., to distinguish different operations\r\nA list of C2 addresses, some of which are decoy addresses\r\nAn “Identifier” often set to either 444 or 443, the main purpose of which is still undetermined – there is\r\nevidence that this is the port used to filter out the decoy addresses\r\nhttps://www.vmray.com/cyber-security-blog/understanding-bumblebee-the-malware-configuration-and-clusters/\r\nPage 2 of 6\n\nRead the Ebook: Malware Configurations\r\nClustering\r\nBased on this information, we tried to identify different samples and missions likely belonging to the same threat\r\nactors. For this purpose, we have randomly collected about a hundred BumbleBee samples that were seen for the\r\nfirst time in the wild from March to May 2023, extracted their configuration and plotted the relationship between\r\nthem in clusters. While some of the samples seemed to be unique, i.e., they had a key and mission ID which were\r\nnot shared with other samples, most samples had crossovers and shared mostly the same configuration.\r\nDuring this analysis, we noticed that most samples belong to the same mission (“mc1905”), and even more use the\r\nsame encryption key. Connected to this cluster are two other missions, “inst” and “mc1904” (see Figure 3). As all\r\nthree missions share the same encryption key, we believe the same threat actor could be behind all of these\r\nsamples.\r\nhttps://www.vmray.com/cyber-security-blog/understanding-bumblebee-the-malware-configuration-and-clusters/\r\nPage 3 of 6\n\nFurthermore, in Figure 4 we have plotted the samples that are unique or decoupled from the biggest cluster. Here,\r\nwe have identified the missions “mvtm1703” and “0211r” to also likely stem from the same threat actor.\r\nhttps://www.vmray.com/cyber-security-blog/understanding-bumblebee-the-malware-configuration-and-clusters/\r\nPage 4 of 6\n\nThis data reveals that in these three months, likely only one threat actor was dominating the space as most samples\r\nused the same encryption key (over 90% of the samples we looked at).\r\nWith API access to the VMRay Platform, the extraction of the config can be automatized to allow this kind of\r\nclustering and to follow threat actors over some period of time (see here).\r\nConclusion\r\nDeep dives into malware families, as demonstrated in this blog post, help us to find better detection methods,\r\nproactively add VTI’s to trigger on new malicious behavior and protect our customers before a dangerous malware\r\nbecomes a threat.\r\nThis blog post also demonstrates how half a hundred evasion techniques are not enough to evade our dynamic,\r\nbehavior-based analysis engine. Rather, we weaponize these efforts against the malware by trying to detect these\r\nattempts and revealing the malicious intent. As threat actors are always on the lookout for new methods to deliver\r\ntheir malware, regular updates of the VMRay Platform allow us to always be on track when it comes to new\r\ntechniques.\r\nReferences\r\nhttps://research.checkpoint.com/2022/bumblebee-increasing-its-capacity-and-evolving-its-ttps\r\nhttps://www.cloudsek.com/blog/technical-analysis-of-bumblebee-malware-loader\r\nhttps://elis531989.medium.com/the-chronicles-of-bumblebee-the-hook-the-bee-and-the-trickbot-connection-686379311056\r\nIOCs\r\nHashes\r\nJune 2022\r\n62a319d1b88070b6fc996226b2a213944f70f6e9370b89bcf761c6593420ae20\r\nAugust 2022\r\n5c15151a29fab8a2d58fa55aa6c88a58a456b0a6bc959b843e9ceb2295c61885\r\nNovember 2022\r\n2911bdd99140387cbc8761826aacc3c9de0ccb511255aa58790955d8337e2edf\r\nDecember 2022\r\ne81b21d6847961bc31a5446b556bde65234eb51cea23a2f928a2b79d13e35e03\r\nJanuary 2023\r\na41deed7a7bc99f4b45490e4572114b8cc2dd11f2301d954a59dee67fa3cca63\r\nhttps://www.vmray.com/cyber-security-blog/understanding-bumblebee-the-malware-configuration-and-clusters/\r\nPage 5 of 6\n\nFebruary 2023\r\n897e53b648020ab28663240bbbce54546cf6f55b35019fd4aa2a209c4a3b1832\r\nAnalysis Report (February 2023)\r\n51bb71bd446bd7fc03cc1234fcc3f489f10db44e312c9ce619b937fad6912656\r\nISO sample\r\nc3148c6c4b0ecce9c7d07ba57dea96e35acf5f2ef47396c48339bb9a3a07e390\r\nSource: https://www.vmray.com/cyber-security-blog/understanding-bumblebee-the-malware-configuration-and-clusters/\r\nhttps://www.vmray.com/cyber-security-blog/understanding-bumblebee-the-malware-configuration-and-clusters/\r\nPage 6 of 6\n\n https://www.vmray.com/cyber-security-blog/understanding-bumblebee-the-malware-configuration-and-clusters/      \nFurthermore, in Figure 4 we have plotted the samples that are unique or decoupled from the biggest cluster. Here,\nwe have identified the missions “mvtm1703” and “0211r” to also likely stem from the same threat actor.\n    Page 4 of 6",
	"extraction_quality": 1,
	"language": "EN",
	"sources": [
		"Malpedia"
	],
	"origins": [
		"web"
	],
	"references": [
		"https://www.vmray.com/cyber-security-blog/understanding-bumblebee-the-malware-configuration-and-clusters/"
	],
	"report_names": [
		"understanding-bumblebee-the-malware-configuration-and-clusters"
	],
	"threat_actors": [],
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