Key Trends in Threat Hunting Services and XDR Telemetry Exploitation

This report presents an updated analysis of Threat Hunting trends focused on the exploitation of XDR (Extended Detection and Response) telemetry. The goal is to demonstrate how expert Threat Hunting teams can significantly enhance security services beyond automatic detection based on rules or built-in mechanisms provided by standard security solutions, by leveraging the wealth of available data to uncover malicious patterns before they escalate into critical incidents.

With the technological growth of new security solutions, combined with the analytical capabilities offered by AI models and data analytics, organizations have expanded their defensive capabilities. At the same time, however, new threats and exploitation techniques used by Threat Actors always seem one step ahead of defensive mechanisms.

Threat Hunting services have become a key component in organizations’ advanced defense models. Identifying a known threat, malware, or malicious indicator recognized by signature or hash is no longer the optimal defense model. Threat Hunting focuses on identifying threats in their earliest stages, assuming compromise and searching for patterns that expose it.

In the evolution of Threat Hunting service models, we identify new trends to assess current service capabilities and ensure alignment with emerging types of threats.

Identity and Login as Priority Vectors

Identity is currently one of the most exploited vectors by attackers, especially in hybrid environments where local and cloud resources are accessed (Azure AD, Microsoft 365, AWS IAM, etc.). Credential theft, persistent tokens, MFA abuse, and privilege escalation are common techniques.

Identity telemetry hunting does not seek “alerts,” but rather anomalous patterns and out-of-norm behaviors that indicate a legitimate identity has been compromised or is being used maliciously.

Modern attack techniques against identities focus on credential theft, session hijacking, and abuse of privileged accounts—tactics that often evade traditional detection systems.

A fourfold increase in identity-related threats was observed in 2024, with techniques such as fake CAPTCHAs, simulated updates, and manipulation of email/login rules standing out.

Globally observed use cases in production environments include:

• Detection of anomalous MFA logins from unusual locations.
• Exploitation of methods such as MFA Fatigue.
• Hunting for repetitive login attempts without corresponding logout events.
• Identification of persistent tokens reused by malicious actors.

Enriched and Multi-directional Telemetry

Modern XDR goes beyond the capabilities of an Endpoint Management System, collecting data from processes, memory, files, network, identity, and email.

Security models are increasingly oriented toward a “multi-directional” approach, not only exploiting endpoint telemetry but also integrating memory activity analysis, log inspection, and file system analysis, reducing dwell time.

A strong threat hunting approach leverages the cross-visibility offered by modern XDR platforms (endpoint, network, memory, files, identity, and cloud) to detect malicious behaviors that automated detection systems might miss.

Hunters can correlate activities across different layers to build hypotheses and identify evasive actions or early Kill Chain stages, using specific queries, behavior analysis, and mapping to MITRE ATT&CK TTPs.

The concept of “Open XDR” consolidates telemetry from multiple sources for advanced hunting, expanding defenders’ visibility and detection capabilities.

Threat Hunting opportunities with enriched multi-source telemetry include:

• Identifying legitimate processes with malicious arguments (LOLBins):
  • Legitimate processes launching obfuscated or unrelated commands, downloading payloads, or making remote connections.
  • Detecting these patterns enables threat discovery without relying on hashes or IOCs.
• Hunting for executables loaded into memory with anomalous behavior:
  • Attackers inject payloads directly into process memory (reflective DLL injection, process hollowing) without writing to disk, evading AV/EDR.
  • This advanced malware hunting method detects implants (Cobalt Strike, Sliver, Meterpreter) in active phases.
• Persistence after removal of the initial artifact:
  • Attackers execute a malicious file, and even if it is removed or neutralized, the environment remains compromised via persistence techniques (scheduled tasks, registry keys, hijacked DLLs, modified services).
  • These hunting methods ensure remediation is complete and not superficial.

Managed Services: Threat Hunting vs MDR → MXDR → Managed XDR

Managed Threat Hunting services have become a critical extension for cybersecurity teams, especially in environments using XDR platforms. These services expand detection capacity beyond automated alerts, through active human intervention leveraging XDR telemetry to identify subtle, evasive, or emerging threats.

The market offers a variety of models depending on the hunting approach, ranging from reactive mechanisms to continuous offensive operations.

• Campaign-based Hunting (MDR/MXDR): Predefined, scheduled hunts (weekly, monthly, or topical) focused on known TTPs or active threat campaigns (ransomware, APTs). Limited by campaign scope and schedule.
• RetroHunting with preloaded IoCs (Managed XDR): Searches historical presence/activity of known IoCs (hashes, IPs, domains). Limited to previously available IoCs and blind to IOC-less threats.
• Proactive, continuous offensive Hunting (Advanced Threat Hunting / Blue Team): Hunters act as persistent adversaries, continuously simulating and detecting offensive TTPs. Requires high technical skill and strong client integration.
• Pattern correlation without known IoCs: Behavior-driven analysis to identify emerging threats, generating and validating hypotheses. Strongly dependent on hunter expertise and tools (SIEM + XDR).
• Contextual Hunting with proprietary intelligence: Intelligence generated by the provider, often correlated across clients (cross-tenant), combining tactical, strategic, and operational context. Dependent on provider maturity; may involve intelligence lag.

Enrichment with Threat Intelligence and Machine Learning

The combination of threat intelligence and AI/ML enables predictive and contextual detection.

AI and data analytics models provide enhanced monitoring and proactive hunting capabilities. Integrating CTI services into Threat Hunting boosts defense and response by combining strategic, operational, and tactical intelligence for pattern identification.

Advanced Threat Hunting services can leverage enriched CTI to access:

• Verified leaks in underground forums.
• Active vendors and current campaigns on the dark web.
• Leaked credentials, C2 tools, builders, and kits used by threat groups.
• Live malicious infrastructure in rotation (panels, dynamic DNS, P2P C2 networks).

Crossing this data with AI/ML and XDR telemetry enables:

• Identification of undetected threats.
• Modeling threat actors and predicting actions.
• Investigating pre-exploitation campaigns.
• Generating hunting hypotheses from variants of known APT campaigns.
• Running controlled simulations and validating against existing telemetry.

Telemetry Ingestion and Integration with External Platforms

SIEM and SOAR platforms enable advanced correlation of XDR telemetry with multiple external sources.

SOAR-driven orchestration and automation within Threat Hunting services ensure proper, efficient exploitation of client technologies.

Key components include:

• Centralized SIEM repositories: Telemetry storage and correlation across logs, endpoints, network, and cloud; enabling multidimensional hunting aligned with MITRE ATT&CK and NIST CSF.
• IAM/IGA platforms: Provide critical data on authentication, roles, and account provisioning, helping detect credential misuse and privilege abuse.
• Email management tools and CASBs: Correlate malicious email with SaaS/app activity and endpoints; enforce adaptive access policies based on context and risk.
• NDR sensors/technologies: Provide deep network visibility (including hybrid and multi-cloud) to detect lateral movement, credential abuse, and C2 communications.

The combination of these components with automation and threat intelligence enables proactive and adaptive defense, containing threats in early kill chain phases and reducing exposure windows.

Deep Telemetry: From File to Network and Cloud

Deep telemetry goes beyond surface events like “a process executed” or “a file opened.” It involves collecting and analyzing rich contextual information on system behavior, including:

• Extended file metadata analysis (MOTW, signatures, timestamps).
• Low-latency network activity (C2 beaconing, DNS, HTTP patterns).
• Malware implants injected into memory (code injection, reflective DLLs).
• Persistence in cloud environments without agents (PaaS/SaaS).

This visibility can only be leveraged by expert teams capable of interpreting it and formulating hypotheses independent of static rules or known IOCs.

Added Value of a Dedicated Threat Hunting Team

A specialized Threat Hunting team with enriched XDR telemetry access is not reactive; instead of waiting for alerts, it anticipates, discovers, and neutralizes latent threats through analytical, offensive, and contextual methods.

Key added values include:

• Correlating identity and endpoint events to detect lateral movement before alerts trigger.
• Discovering subtle patterns undetectable by signatures or static rules.
• Applying offensive knowledge to anticipate evasive techniques.
• Projecting malicious behavior before it occurs using intelligence and pattern analysis.
• Validating attack hypotheses across multiple data domains for precision and depth.
• Analyzing enriched logs to detect early malicious activity, even without execution artifacts.

Proactive defense through dedicated Threat Hunting detects evasive techniques, connects dispersed events across multiple layers, and anticipates attacker actions. Its true operational value lies in translating weak signals into early protection decisions.

Threat Hunting XDR HuntOps: Beyond Telemetry

Against an increasingly stealthy, dynamic, and automated threat landscape, the value of proactive, human-driven Threat Hunting multiplies: it stops attacks without alerts and strengthens security where rules cannot.

In an evolved model, telemetry analysis becomes a starting point, not an end, extending into operational capabilities embedded in client environments.

XDR HuntOps defines Alpine Security’s model: integrating multiple telemetry sources, proactive threat hunting, and advanced operational capabilities—including remote script/binary execution.

Led by experts in defense, offensive techniques, advanced pentesting, and system exploitation, this approach anticipates threats from the adversary’s perspective.

Using EDR/XDR deployment capabilities, the service executes custom analysis tools tailored for each environment, enabling:

• Disk and memory artifact analysis.
• Implant detection.
• Decoy binary deployment.
• Forensic artifact collection.
• Automated triage on investigated endpoints.

This exponentially increases active, adaptive hunting operations, uncovering hidden threats even in systems with no prior alerts.

The strategy consolidates Threat Hunting as a tactical defense function, drastically reducing detection, response, and containment times.

Even in environments without recurring incidents, managed Threat Hunting services:

• Extend the value of detection and protection investments (EDR/XDR).
• Detect invisible patterns missed by traditional solutions.
• Apply validated global intelligence for stronger defensive context.
• Reduce future costs and risks by minimizing post-attack response needs.

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