Sigma Rule Writing

What Sigma Rule Writing teaches: write a detection once in Sigma's vendor-neutral YAML and deploy it to any SIEM. The rule anatomy, the detection-logic language, the craft of writing rules that survive production, conversion across Splunk, Sentinel, and Elastic, and the correlation and validation that make a detection pack you keep. The discipline, the toolchain, and how the course is built. Start here.

What a Sigma rule is as an object you author. The full YAML anatomy, the logsource abstraction of category, product, and service that makes a rule portable, the detection block in outline, the metadata that gives a rule identity and a lifecycle, ATT&CK tagging, and reading SigmaHQ rules as a peer rather than a black box.

The detection block in depth. How a selection matches, the full set of field modifiers from contains and startswith through regex, CIDR, base64, and windash, the condition language with its quantifiers and operator precedence, and the exclusion logic that carves known-good activity out of a match. The language you write detections in, taught precisely.

The gap between a rule that is correct and a rule that survives production. Why good rules get switched off, detecting on durable fields instead of fragile indicators, the specificity dial between too broad and too narrow, documenting false positives and tuning, the SigmaHQ quality conventions, and taking a noisy rule to production-ready.

How one Sigma rule becomes a query on any SIEM. The conversion pipeline, the two-part system of target and pipeline, how fields and logsources are mapped to each platform, what converts cleanly and what degrades or breaks, reading and verifying the converted query, and taking a single rule across Splunk, Microsoft, and Elasticsearch.

Turning rules into an operational detection practice. Validating a rule against real data before it ships, the correlation model for detecting across multiple events, the counting and sequence correlation types, shipping detections as code through a lifecycle, and a course capstone that assembles everything from a threat to a deployed detection.

The rule anatomy, the modifiers, what survives conversion, and the correlation types with their limits.

Ordered procedures for writing a rule from a report, adopting a community rule, taking a noisy rule to production, and building a repository.

Four cases reasoned end to end, including the rule that converted perfectly and matched nothing.

sigma-cli, the public rule repository, and log data of your own to validate against.

The full rule anatomy, every modifier, the condition and correlation syntax, the sigma-cli conversion and validation commands, and the rule-quality conventions from the course in one place, organized by task. The working kit you carry out of the course to the rules you write.

The Sigma specification and documentation, the pySigma toolchain and backends, ATT&CK, Atomic Red Team, and the backend platform documentation used throughout the Sigma Rules course, organized by category.

Sigma Rule Writing end-of-course exam: one rule, two backends, clean conversion on both, and only one that ever fires. Testing whether you can tell a syntax success from a semantic failure and measure how far it reaches.