Amid the overwhelming volume of security notifications generated by modern cloud infrastructures, a recent year-long study has revealed a groundbreaking method for distinguishing the subtle, yet distinct, operational patterns of sophisticated threat actors from the background noise of benign activity. This research pivots away from the conventional view that the challenge lies in monitoring resources, proposing instead that the key to proactive defense is recognizing the unique “fingerprints” adversaries leave behind in security alert data. The study’s core hypothesis posits that a direct and observable correlation exists between known cybercriminal and nation-state groups, the specific set of MITRE ATT&CK® tactics they favor, and the predictable pattern of alerts these actions trigger within a victim’s cloud environment. By meticulously analyzing these alert patterns, security teams can effectively move beyond reactive incident response and begin to identify compromises by specific, known adversaries, often in the earliest stages of an attack. This approach was validated through an extensive analysis of cloud alerting data collected across 22 different industries, focusing on two operationally distinct threat groups: the financially motivated cybercrime syndicate Muddled Libra and the nation-state affiliated group Silk Typhoon. The findings demonstrate that each group possesses a unique and distinguishable alerting pattern, opening significant possibilities for developing automated, predictive defense capabilities tailored to the threats most relevant to a specific industry.
Foundational Concepts and Research Methodology
Defining the Fingerprints Core Concepts
To provide a clear framework for the analysis, the research established a precise methodology and a glossary of key terms for interpreting the data, ensuring a consistent understanding of how threat actor techniques translate into observable security events. The relationship between a specific MITRE ATT&CK technique and a security alert is not always a direct one-to-one correlation. A single advanced technique, such as “Steal Application Access Token,” could trigger multiple distinct alerts across different security tools. Conversely, a single generic alert, like “Unusual resource modification,” could map back to several different MITRE techniques and tactics, spanning from Initial Access and Persistence to Defense Evasion. This inherent complexity is central to the research, as the unique combination and frequency of these alerts form the fundamental basis of a threat actor’s operational fingerprint. By understanding this many-to-many relationship, security analysts can begin to assemble a more holistic picture of an attacker’s behavior rather than chasing isolated, low-context alerts that often lead to dead ends or alert fatigue. This nuanced perspective is what allows for the differentiation between automated, opportunistic scans and a deliberate, multi-stage intrusion by a known adversary.
Two primary metrics were developed to quantify these patterns and measure the unique characteristics of each threat group’s activity. The first, “Unique Alert Count,” quantifies the variety and breadth of techniques an attacker employs. For the purposes of this study, each specific alert rule was counted only once per industry over the analysis period, regardless of how many times it was triggered. For example, Muddled Libra’s 11 known cloud-related MITRE techniques were found to correlate with a potential set of nearly 70 different unique alert rules, while Silk Typhoon’s 12 techniques correlated with just over 50. The second metric, “Average Daily Occurrences,” measures the intensity and persistence of an attacker’s operations. If a single alert rule, such as “Suspicious identity downloaded multiple objects from a bucket,” triggers 1,000 times within a single day in one organization, it still counts as just one “unique alert.” However, those 1,000 instances are factored into the “average daily occurrences.” This metric, calculated by averaging the total daily alert triggers for each organization within a specific industry, provides critical insight into the relentless frequency of an attack, distinguishing a persistent campaign from a fleeting one.
The Study’s Approach
The research was conducted by collecting and meticulously analyzing security alerts generated between June 2024 and June 2025. The data was sourced from an extensive and diverse range of cloud platforms, ensuring a comprehensive view of modern enterprise environments. This included alerts from major cloud service providers, container orchestration systems, various cloud-hosted applications, and an array of Software-as-a-Service (SaaS) platforms. Each alert was carefully dissected based on several key data points: its unique name, the platform of origin, the precise date of the alert, and associated metadata such as the targeted organization’s industry and geographic region. This broad data collection strategy was essential for building a dataset robust enough to identify subtle patterns that might otherwise be missed within the logs of a single organization or a limited set of cloud services. The richness of this data provided the raw material needed to test the central hypothesis that threat actor activity leaves behind a detectable, industry-specific signature in cloud security telemetry.
A critical layer of this methodology involved the deep integration of the MITRE ATT&CK framework. Each collected alert was systematically paired with its corresponding MITRE technique or techniques, creating a powerful dataset that linked observable, low-level security events to known, high-level adversarial behaviors. This mapping process was the analytical core of the research, allowing the team to filter the vast sea of cloud alerts and focus exclusively on those associated with the known operational toolkits of Muddled Libra and Silk Typhoon. By isolating these specific signals, the researchers could effectively cut through the noise of daily operations and benign misconfigurations that plague security teams. The final step involved correlating these filtered, actor-specific alert patterns with the targeted industries. This crucial analysis served to validate the hypothesis, demonstrating that not only do threat actors have unique fingerprints, but these fingerprints also appear more prominently in the industries they are actively targeting, providing a new dimension for threat intelligence and proactive defense.
Profile and Analysis Muddled Libra
The Financially Motivated Intruder
Muddled Libra, also known by aliases such as Scattered Spider and UNC3944, is a prolific cybercrime group that has been highly active since at least 2021. The group is particularly renowned for its sophisticated and often audacious social engineering tactics, which include vishing (voice phishing) calls made directly to corporate help desks and highly targeted smishing (SMS phishing) campaigns aimed at duping employees into giving up their credentials. Muddled Libra has demonstrated a flexible and evolving approach to its operations, frequently partnering with ransomware-as-a-service (RaaS) providers to monetize its intrusions and maximize its financial gains. After gaining initial access, typically through stolen credentials, the group utilizes a variety of tools for reconnaissance and achieving its objectives. These tools include the open-source Active Directory reconnaissance utility ADRecon, which helps them map out the internal network, and destructive ransomware variants like DragonForce, which they deploy to encrypt critical systems and extort their victims.
The group’s targeting has been both broad and strategic, consistently hitting a wide range of sectors. Public reporting has highlighted significant attacks against Aerospace and Defense, Financial Services, High Technology, Hospitality, Media and Entertainment, Professional and Legal Services, Telecommunications, Transportation and Logistics, and the Wholesale and Retail industries. For this research, analysts isolated 11 specific MITRE ATT&CK techniques known to be a core part of Muddled Libra’s cloud operations. This curated set of techniques forms the group’s distinct “fingerprint” and includes methods focused on reconnaissance, privilege escalation, and data theft. Key techniques include T1530 (Data from Cloud Storage) for collection, T1078.004 (Valid Accounts: Cloud Accounts) for initial access and persistence, and a heavy emphasis on discovery techniques like T1526 (Cloud Service Discovery) and T1580 (Cloud Infrastructure Discovery). This focus on discovery highlights the group’s methodical approach to understanding a victim’s cloud environment before escalating their attack.
Deciphering Muddled Libra’s Activity
The analysis of alert data from June 2024 to June 2025 revealed a powerful and direct correlation between the industries Muddled Libra is publicly known to target and those that exhibited the highest number of unique alerts associated with its operational fingerprint. The high technology, wholesale and retail, financial services, and professional and legal services industries consistently showed the greatest variety of Muddled Libra-related alerts. This strong alignment with publicly reported targets serves as a crucial validation of the fingerprinting model’s accuracy. Furthermore, the presence of a significant number of unique alerts, defined as 16 or more, in other sectors like manufacturing or state and local government acts as a potential early warning system, suggesting active but perhaps not yet publicly reported targeting campaigns. For security defenders, a high count of unique alerts signals a sophisticated, multi-stage intrusion attempt, and the research suggests that observing more than 10 unique Muddled Libra-associated alerts within a 30-day period should warrant an immediate and deep forensic investigation.
When viewed alongside the unique alert count, the average daily alert volume provides a more nuanced and actionable picture of the threat. The transportation and logistics industry, for instance, ranked sixth in terms of alert variety but surged to first place in daily volume. This specific combination indicates a highly persistent and intense campaign, where the group is not only using a wide array of techniques but is doing so with relentless frequency. In contrast, a high daily average combined with low variety might point to more automated or brute-force activities, such as credential stuffing attacks against a single entry point. The data also revealed what appears to be a “saturation effect.” Industries like telecommunications and media and entertainment, which were primary targets in 2022 and 2023, now rank near the bottom for average daily alerts. This suggests that Muddled Libra may be shifting its focus away from these previously heavily targeted sectors, possibly due to improved defenses or a decision to pursue less hardened targets in other verticals.
A Real-Time Case Study The Aviation Industry
The practical, real-time applicability of this research was demonstrated through a focused analysis of the transportation and logistics sector. In June 2025, public reports began to emerge detailing a concerted campaign by Muddled Libra targeting the aviation industry. By correlating this external threat intelligence with the research data, a monthly analysis of the transportation and logistics category, which includes aviation, revealed a startling 25% increase in the average number of unique alerts per organization from May to June 2025. This significant spike, which saw the sector hit a peak of 15 unique alerts for the year, directly coincided with the public reports. This provided powerful confirmation that the fingerprinting method can not only identify historical trends but can also detect and validate active campaigns as they unfold, offering security teams a near real-time view into adversary activity within their specific industry. This capability transforms threat intelligence from a reactive report into a proactive, actionable signal for defense.
The most frequently observed alerts tied to Muddled Libra’s techniques underscore the group’s heavy focus on reconnaissance and data exfiltration, particularly within Microsoft Azure environments. The top ten alerts provide a clear roadmap of their typical attack path. The list is dominated by discovery-related activities, such as “Azure sensitive resources enumeration activity using Microsoft Graph API,” “Multi region enumeration activity,” and “Cloud infrastructure enumeration activity.” This indicates that once Muddled Libra gains a foothold, its primary objective is to map out the cloud environment, identify valuable data stores, and understand the existing security posture. Following discovery, the alerts pivot to data theft, with “Microsoft 365 storage services exfiltration activity” and “Suspicious identity downloaded multiple objects from a bucket” being prominent indicators of an active compromise. This detailed view of their most common alerts allows organizations to fine-tune their detection rules and prioritize alerts that are most indicative of a Muddled Libra intrusion.
Profile and Analysis Silk Typhoon
The Nation-State Adversary
Silk Typhoon, also known as HAFNIUM, is a nation-state threat actor group with a China-nexus that has been operational since at least 2021. The group first gained global notoriety for its widespread exploitation of vulnerabilities in on-premises Microsoft Exchange Servers. In recent years, however, its operational focus has decisively shifted towards cloud environments, reflecting the broader trend of enterprise migration away from on-premises infrastructure. Silk Typhoon’s typical modus operandi involves obtaining initial credentials from vulnerable public-facing applications or compromised VPNs. Once inside, they use these credentials to move laterally within the target’s cloud infrastructure. They are known to leverage remote monitoring and management (RMM) tools for persistence and make extensive use of Microsoft’s Graph API for comprehensive resource enumeration, allowing them to map out an organization’s cloud assets and identify high-value targets for data exfiltration or disruption.
This group primarily targets organizations within the United States, with a strategic focus on key sectors that align with nation-state intelligence-gathering objectives. These sectors include Education, High Technology, Federal Governments, Financial Services, Nongovernmental Organizations (NGOs), Professional and Legal Services, State and Local Governments, and Utilities and Energy. The research identified 12 cloud-focused MITRE ATT&CK techniques that constitute Silk Typhoon’s distinct fingerprint. Notably, only three of these techniques—T1530 (Data from Cloud Storage), T1078.004 (Valid Accounts: Cloud Accounts), and T1098.001 (Account Manipulation: Additional Cloud Credentials)—overlap with Muddled Libra’s known toolkit. This minimal overlap provides a solid analytical basis for differentiation, allowing security systems to distinguish between an intrusion by a financially motivated criminal and one by a sophisticated nation-state actor based on the specific alerts being generated within their environment.
Deciphering Silk Typhoon’s Activity
The analysis of Silk Typhoon’s activity revealed a distinct operational style when compared to Muddled Libra. While its potential alert portfolio is smaller, with just over 50 unique alerts compared to Muddled Libra’s nearly 70, Silk Typhoon tends to use a larger proportion of its available techniques during a single attack campaign. This was evidenced by the fact that the highest number of unique alerts observed in a single industry for Silk Typhoon was 27, significantly higher than the 22 observed for Muddled Libra. This suggests that Silk Typhoon’s operations may be more comprehensive and less opportunistic, employing a wider range of their tools to ensure mission success. The federal government sector presented a particularly insightful case: it ranked last for unique alert variety but first for average daily volume, peaking at 7.28 alerts per day. This pattern suggests a highly focused and persistent attack strategy against government targets, using a narrow but effective set of techniques with relentless frequency to breach hardened defenses.
Similar to the Muddled Libra analysis, the industries with the highest unique alert counts—high technology, financial services, and professional and legal services—aligned perfectly with Silk Typhoon’s known targets. The high technology sector, however, showed a “worst-of-both-worlds” scenario, ranking first in tactical variety and near the top in daily volume. This indicates that campaigns against tech companies are both sophisticated and extremely persistent, posing a significant challenge for defenders in that vertical. For security teams, a high average alert volume, even when coupled with low variety, could signify an adversary attempting to gain initial access but not yet succeeding in deploying their full toolset. As with Muddled Libra, the research suggests a critical threshold for investigation: observing more than 10 unique Silk Typhoon-associated alerts within a one-month period should trigger an immediate and thorough incident response process to contain the potential breach before it escalates further.
Silk Typhoon’s Top 10 Alerts
Silk Typhoon’s most common alerts highlight a strong and consistent emphasis on data collection, exfiltration, and achieving initial access through the exploitation of public-facing vulnerabilities, with a particular focus on Microsoft 365 and cloud storage services. The top alert, “Microsoft O365 storage services exfiltration activity,” directly points to the group’s primary objective of stealing sensitive data housed within SaaS platforms. Another prominent alert, “Process execution with a suspicious command line indicative of the Spring4Shell exploit,” reveals one of their key methods for gaining an initial foothold. The list is heavily populated with alerts related to suspicious downloads from cloud storage, such as “Suspicious identity downloaded multiple objects from a bucket” and its variants targeting backup storage and multiple buckets. This pattern underscores their methodical approach to data theft. Finally, the inclusion of “Deletion of multiple cloud resources” as a top ten alert points to the potential for destructive, impact-oriented operations, a hallmark of nation-state actors seeking to disrupt their targets in addition to exfiltrating data.
A New Paradigm for Proactive Defense
The most compelling finding of this research emerged when the specific threat actor “fingerprints” were compared against general, undifferentiated cloud alert trends. While the high technology industry consistently ranked as the top target across all categories—general alerts, Muddled Libra activity, and Silk Typhoon activity—the rankings for other industries varied dramatically. For example, the wholesale and retail industry ranked a distant 14th for general cloud alerts but was the second-highest target for Muddled Libra and the third-highest for Silk Typhoon. This significant discrepancy proved that the operational patterns of these specific threat actors create their own unique trends, which are entirely distinct from the background noise of general cloud security events. This validation has profound implications for how organizations should approach threat detection and intelligence. It suggests that relying solely on generic, high-volume alert data can lead to a misallocation of security resources and a failure to recognize the most relevant threats.
This research successfully validated the hypothesis that malicious techniques used by known threat actors like Muddled Libra and Silk Typhoon create distinct, detectable “fingerprints” within cloud security alert data. This capability offered a powerful new paradigm for cloud defense. By moving beyond generic alert analysis and focusing on actor-specific patterns, organizations gained the ability to develop predictive and proactive security strategies. The methodology enabled the creation of tailored defensive alerting and early warning systems that could detect reconnaissance or initial access operations before they escalated to data exfiltration or system impact. By understanding the specific techniques used by adversaries most likely to target their industry, defenders were empowered to build a more intelligent, focused, and ultimately more effective security posture for their complex and ever-expanding cloud architectures.
