Detection Engineering for Ukraine: Sigma Rules and Threat Hunting

Detection engineering is the discipline of developing, testing, and continuously improving the rules and algorithms that identify attacker behavior within monitored systems. In Ukraine's conflict environment, detection engineering is mission-critical work: the adversary constantly updates techniques to evade existing detections, requiring continuous rule development. Ukraine's detection engineering teams—staffed by CERT-UA analysts, government SOC engineers, and international partners—have built one of the most operationally tested detection rule libraries in the world.

Sigma Format Adoption

Sigma is a generic, platform-neutral rule format for SIEM detection rules, analogous to what YARA is for malware detection. A Sigma rule describes a detection logic once, and conversion tools (sigmaHQ's sigma-cli) translate it into the query syntax of any supported SIEM platform—Splunk SPL, Microsoft Sentinel KQL, QRadar ARIEL, Elastic EQL—without rewriting the detection logic. This platform-agnostic approach has been central to Ukraine's detection engineering strategy: rules developed by CERT-UA analysts can be shared with international partners running different SIEM platforms without format translation overhead.

CERT-UA has contributed Sigma rules derived from Ukrainian incident analysis to the public SigmaHQ repository—the community library for shared detection rules. These contributions allow security teams globally to benefit from Ukraine's front-line detection experience, while Ukraine benefits from rules contributed by other community members detecting Russian techniques observed in non-Ukrainian campaigns. The public Sigma rules specific to Russian threat actor techniques represent a growing library of community intelligence directly derived from Ukraine's operational experience.

Threat Hunting Team Operations

Where detection rules identify known attack patterns, threat hunters actively search for evidence of attacks that have not yet triggered automated alerts—whether because they use novel techniques, deliberately avoid known detection signatures, or operate below the noise threshold of automated rules. Ukraine's government threat hunting program maintains dedicated teams within CERT-UA and in the SOCs of each Tier-1 sector, conducting hypothesis-driven hunts at regular intervals.

Hunt hypotheses are generated from multiple sources: new intelligence about Russian threat actor campaigns, ATT&CK technique coverage gap analysis showing which techniques lack detection rules, and anomalous but sub-threshold activity patterns identified in log analytics dashboards. Each hunt is documented with its hypothesis, search methodology, results, and outcomes—whether detection rules were created, incidents were escalated, or the hunt produced negative results that themselves provide assurance.

Detection Coverage Against Known Russian Techniques

Hypothesis-Driven Detection Methodology

Ukraine's formal hypothesis-driven detection process follows a structured framework: identify a technique or adversary behavior of interest; form a specific hypothesis about how that behavior would manifest in available log data; design a search query testing that hypothesis; execute the search and review results; analyze findings and either escalate incidents found, create new detection rules for confirmed behavioral signatures, or document negative results. This rigorous methodology prevents threat hunting from becoming unfocused data exploration and ensures that hunter effort generates tangible artifacts—either found incidents or new detection rules—that improve the overall security posture.

ATT&CK Technique Coverage Gap Analysis

Regular coverage gap analysis—comparing the ATT&CK techniques documented in CERT-UA's adversary profiles against the detection rules in the government SIEM stack—identifies which techniques lack coverage and should be prioritized for new rule development or additional logging. For the Russian threat actor groups primarily targeting Ukraine, coverage gap analysis conducted in 2023–2024 identified Living-off-the-Land techniques and cloud-specific post-access behaviors as under-detected relative to their observed usage frequency. Both areas became priority targets for new Sigma rule development funded through US technical assistance programs.

FAQ

What is Sigma and why has it become the standard for Ukrainian detection rules?

Sigma is a platform-agnostic SIEM rule format allowing one rule to be converted to any supported SIEM platform's native query language. Ukraine adopted it because it enables rule sharing with international partners running different SIEM platforms and because the public SigmaHQ library provides a massive library of community-contributed rules to start from.

What is threat hunting and how does it differ from detection alert response?

Alert response reacts to automated detections of known patterns. Threat hunting proactively searches for attacker behaviors that automated detections have not flagged—novel techniques, low-profile persistence, or pre-attack reconnaissance. Hunting finds threats the automated system missed; alert response handles threats the automated system found.

How does MITRE ATT&CK coverage gap analysis work?

Analysts map each rule in their SIEM detection library to the ATT&CK technique(s) it detects, then overlay this coverage map against the techniques used by priority threat actors. Techniques used by priority adversaries that have no corresponding detection rule represent gaps requiring either new rule development or additional logging to make rule development possible.

Why are LOLBin techniques particularly challenging to detect?

Living-off-the-Land attack techniques use legitimate Windows tools (PowerShell, WMI, certutil) for malicious purposes. Detection must distinguish malicious from legitimate use of these tools by context—which process launched them, what parameters were used, who initiated them—rather than by tool identity alone.

How do threat hunters prioritize which hypotheses to investigate?

Prioritization factors include adversary relevance (techniques used by currently active threat actors posing highest risk), detection coverage gaps (techniques with no existing automated detection), recent intelligence (new CERT-UA advisories introducing novel techniques), and organizational context (specific systems or users of elevated concern).

Sources

1. SigmaHQ — "Sigma Rules Repository and Ukraine Threat Actor Detection Rules," github.com/SigmaHQ, 2024
2. CERT-UA — "Detection Engineering Program: Technical Guidelines," 2024
3. MITRE — "ATT&CK Coverage Gap Analysis Methodology," attack.mitre.org, 2023
4. Mandiant — "Detection Engineering Best Practices Informed by Ukraine Campaign Analysis," 2024
5. Florian Roth, Thomas Patzke — "Sigma: Generic Signature Format for SIEM Systems," original paper, 2017 (foundational reference)