Subjective and Contextual Anomaly Detection in Threat Hunting

Joshua Horton

The digital world is rife with lurking cyber threats. Often, these threats go undetected, silently infiltrating the vulnerable corners of our systems and datasets. 

Threat hunting emerges as a vanguard in this cyber environment, proactively sniffing out these elusive threats that evade even the most stringent of our security measures. 

This article unveils the intricacies behind subjective and contextual anomaly detection, two critical elements of a threat hunting service. Distinguishing between these anomalies is of paramount importance for a resilient digital future, forming the bedrock for effective detection and response.

Proactive defense, unlike its reactive counterpart, doesn’t wait for cyber incidents to stir the waters. Threat hunting, a gem in the crown of proactive cyber threat hunting, is our foray into the unexplored terrain of network threats. 

As skilled security professionals traverse through a sea of data, they manually and synthetically unearth hidden adversaries, thereby protecting assets ahead of an imminent cyber attack.

Defending the gates to your organization’s precious reserves is not a menial task. One’s to-do list brims with endless data points. A daily dive into data overload is warranted to detect subtle abnormal activities that could mark a stealth attack on the network. Among these anomalies are subjective and contextual anomalies, each set apart by its characteristics:

  • Subjective Anomalies: These unexpected nuggets of data are out of place within the evidence they arise from. They might not be threatening to your cybersecurity posture by themselves, but their inexplicable presence begs an investigation. Security analytics often reveal their potential to sprout into cyber threats that may harm the organization’s digital well-being.

  • Contextual Anomalies: Weathering the storm of data overload are these anomalies, which make sense only when analyzed concerning other data sources. The art of hunting for these anomalies lies in understanding their relationship with accompanying data to unearth hidden patterns or irregularities.

This inspection through the microscope of cybersecurity community tools and technology, such as machine learning, artificial intelligence, and advanced analytics, reveals potential weak points. 

These nascent vulnerabilities, patched early, can effectively prevent a cyber breach, enhancing your overall security posture. Unraveling this layered world of anomalies plays a significant role in the art of hunting for cyber threats.

Subjective Anomaly Detection

Picture a battalion of security professionals meticulously sifting out data points within troves of network traffic. They are on a quest for subjective anomalies — errant and unexpected data points that stand out oddly from the usual patterns. Not all who wander are lost, and similarly, not all anomalies are malicious. However, their unpredictable presence amid the regular tempo of data is cause enough for speculation.

Subjective anomaly detection lies at the crossroads of human capital, powered by a combination of skilled hunters and cybersecurity industry’s best practices, and tech-heavy artillery of detection capabilities. High on their list are encryption, signature-based detection, SIEM (Security Information and Event Management), EDR (Endpoint Detection and Response), and tools such as GRR Rapid Response and TheHive.

Considered sorcerers of cybersecurity, these hunters weave magic, sprinkling early detection and response across the network landscape. Observe a twinkling in their eye when they leverage open-source threat hunting tools like OSQuery and Redline to sieve out undetectable threats, or when they sharpen their defenses with Uptycs or MozDef to weave a customizable and cost-effective security network.

Deploying hypothesis-driven investigations, they painstakingly separate the wheat from the chaff. Incident Response Teams use advanced techniques, sorting out known Indicators of Compromise (IoCs) from an influx of data points, analyzing hidden trends and patterns; or routinely scouring their systems for any Indicator of Attack (IoA) traces.

Such comprehensive defensive measures solidify the security system’s bedrock, paving the way for a proactive and adaptable approach to cybersecurity. Subjective anomaly detection is indeed a commendable feat, steeped in determination, vigilance, and the relentless pursuit of a secure digital terrain.

Contextual Anomaly Detection

Unveiling the world of contextual anomalies uncovers unforeseen threats nested within the very fabric of our data. These stealth attacks force us to look beyond isolated anomalies, urging a deep-dive into network traffic to identify relationships among disparate data points. Specific tools and technology, including advanced analytics and machine learning, prove instrumental in uncovering these sophisticated threats lurking in the shadows of an organization’s wealth of data.

Network segmentation and Behavioral analysis form a formidable pair to spot adversarial behaviors, often indicative of advanced persistent threats (APTs). Artificial Intelligence noticeably accelerates threat detection, diligently working 24/7, which alleviates the burden of sifting through a data overload.

Automation in threat hunting augments human capital, with platforms like Uptycs concentrating on cloud-native detection and response. Notably, IBM Security Managed Detection and Response (MDR) provides a unique blend of advanced techniques and experienced security professionals responsible for detecting suspicious behaviors and swiftly initiating incident response.

Reliability is key to proactive defense, allowing the cybersecurity community to trust in the tools they employ. Detection solutions such as Intrusion Prevention Systems (IPS) and Intrusion Detection Systems (IDS) can step over the line, leading to false positives and negatives, obscuring the true nature of the cyber environment. 

Contextual anomaly detection curates a responsible approach, minimizing potential harm without hurling the system into panic mode. This methodology forms the crux of a resilient digital future.

Types of Anomalies

No two anomalies are alike. Obfuscation, missing information, and one-to-many relationships exemplify the myriad of forms anomalies can take. 

Unexpected obfuscation in a data source might reveal an attempt by threat actors to misdirect or cloak their presence, while missing information could signal a stealth intrusion or damage to the network. One-to-many relationships, more often than not, are a sign of distributed attacks orchestrated by skilled threat actors.

Approaches to tackle these anomalies must be as diverse as the anomalies themselves. Tools such as YARA, popular for classifying malware samples, and Redline make threat hunting an achievable venture even for lesser-skilled professionals. 

Employing detection capabilities and encryption methods spot subjective anomalies, whereas adopting practices such as patch management and regular updates lend a certain scalability to the overall security posture.

The Art Of Threat Hunting

When the art of threat hunting is distilled to its core, it unveils an impressively extensive arsenal for detecting and resolving advanced attackers. A proactive and adaptable approach sets a higher standard in the cybersecurity landscape, scaling to address new and evolving threats. Employee training programs and continuous improvement initiatives further bridge the gap between organizational models and best practices.

Pathways to a robust cybersecurity posture are not without challenges. So, while we continue to leverage tools, technology, and investigative procedures, we must remain cognizant of subtle nuances that contextual and subjective anomalies bring. Deciphering these anomalies empowers threat hunters, strengthening existing security operations centers (SOCs) and reinforcing our collective will to future-proof the digital terrain. It emphasizes the importance of threat intelligence, shaping proactive measures in the face of an ever-evolving threat landscape.

Threat hunting and anomaly detection are not mere subpoints in a cybersecurity checklist. They embody a narrative of resilience and determination, drawing a line in the sand against cyber threats and making cybersecurity less of a reactive measure and more of a strategic action. Triumphant, we emerge – protecting assets, minimizing damage, and carving out a resilient digital future in our proactive cyber threat hunting journey.

Joshua Horton