| name | yara-rule-authoring |
| description | Guides authoring, review, optimization, and false-positive debugging of YARA-X detection rules for
malware identification across PE, script, npm, Office, Chrome extensions (crx module), and Android
DEX (dex module). Covers string and atom quality, condition short-circuiting, legacy YARA migration,
yarGen/FLOSS workflows, goodware validation, and production deployment—not full malware reverse
engineering, network IDS (Suricata/Snort), or memory forensics (Volatility).
Use when the user asks to write YARA rule, YARA-X, yr check, yr scan, false positive YARA, yarGen,
malware detection rule, crx module, dex module, optimize YARA performance, or migrate legacy YARA.
|
YARA Rule Authoring
Write YARA-X rules that catch the intended family without drowning analysts in false positives.
Target runtime: YARA-X (Rust successor to legacy YARA). Install: brew install yara-x or cargo install yara-x. Essential CLI: yr check, yr scan, yr fmt, yr dump.
When to Use
- Write, review, or optimize YARA-X rules for malware, hacktools, webshells, or supply-chain artifacts
- Convert IOCs or threat intel into maintainable signatures
- Debug false positives or tune
any of / all of logic
- Migrate legacy YARA rules to YARA-X stricter validation
- Author Chrome extension (
crx) or Android DEX (dex) module rules
- Prepare rulesets for production, YARA-CI, or VirusTotal retrohunt
When NOT to Use
- Full malware reverse engineering, disassembly, or unpacker development →
reverse-engineer
- Network intrusion detection (Suricata, Snort, Zeek) → network security / SOC tooling skills
- Memory forensics with Volatility or live RAM analysis →
digital-forensics-analyst
- Hash-only blocklists with no pattern logic → use IOC lists or EDR hash feeds
- Enterprise security strategy, GRC, or audit evidence →
cybersecurity, compliance-engineer
- Embedding YARA in CI/CD pipelines as the primary task →
devsecops
- Adversarial LLM or application red team →
ai-redteam
Related skills
| Need | Skill |
|---|
| Security program, IR strategy, detection philosophy | cybersecurity |
| SIEM/EDR rules, logging, control implementation | information-security-engineer |
| Audit evidence, control mapping, CCM | compliance-engineer |
| Pipeline gates, artifact scanning, SBOM | devsecops |
| Binary RE, unpacking, patch diff | reverse-engineer |
| SOC alert triage and detection tuning (non-YARA) | defensive-security-analyst, soc-analyst |
| Proactive threat hunts and ATT&CK campaigns | threat-hunter |
| CTI briefs, IOC/TTP production | cti-analyst |
| Adversarial AI / prompt injection testing | ai-redteam |
| Disk imaging and forensic reports | digital-forensics-analyst |
Core principles
- Atoms matter — YARA extracts 4-byte subsequences for Aho-Corasick prefilter. Strings with repeated bytes, common sequences, or under 4 bytes force expensive bytecode verification on too many files.
- Family-specific, not category-generic — "Detects ransomware" matches everything and nothing. Target identifiable mutexes, PDB paths, C2 paths, or structural markers for one family or campaign.
- Goodware before production — Validate against ecosystem-appropriate clean corpus (VT goodware for PE; top npm packages for JS; marketplace extensions for CRX).
- Short-circuit cheap checks first —
filesize → magic bytes → strings → modules.
- Metadata is documentation — Name, description, author, reference, and date survive personnel changes.
Essential toolkit
| Tool | Purpose |
|---|
| yarGen | Candidate strings from samples (--excludegood); always yr check output |
| FLOSS | Obfuscated/stack strings when yarGen fails |
| yr | yr check, yr scan -s, yr fmt, yr dump -m pe|crx|dex |
| YARA-CI / VT retrohunt | Goodware corpus testing before deploy |
Core workflows
1. Scope samples and file type
- Collect 3+ variants when possible (single-sample rules are brittle)
- Check packing: entropy > 7.0 or few strings → unpack or target packer/structure, not encrypted layer
- Choose platform path: PE magic / JS / Office ZIP /
import "crx" / import "dex"
See references/yara_x_scope_and_tooling.md for install, CLI workflow, and migration.
2. Extract and filter strings
- Run yarGen or FLOSS on unpacked samples
- Reject ~80% of yarGen output: API names,
C:\Windows\, format strings, require/fetch alone
- Prefer gold tier: mutex names, PDB paths, stack strings; silver: C2 paths, config markers
See references/string_selection_and_atoms.md for decision trees and modifiers.
3. Write rule with ordered conditions
rule MAL_Win_Example_Loader_Jan26
{
meta:
description = "Detects Example loader via unique mutex and config path"
author = "Team <team@example.com>"
reference = "https://example.com/analysis"
date = "2026-01-15"
strings:
$mutex = "Global\\ExampleMutex" ascii wide
$cfg = "/api/beacon/check" ascii
condition:
filesize < 10MB and
uint16(0) == 0x5A4D and
all of ($mutex, $cfg)
}
Condition order: filesize → magic bytes → string matches → module calls (pe, crx, dex).
See references/conditions_and_performance.md for atom theory, regex bounds, and loops.
4. Validate and test
yr check rule.yar && yr fmt -w rule.yar
yr scan -s rule.yar malware_samples/
yr scan -c rule.yar goodware_corpus/
FP flow: yr scan -s on false positive → identify matching string → tighten, exclude vendor, or pivot to structure.
See references/testing_goodware_and_fp_debugging.md for corpus selection and investigation.
5. Platform modules (when applicable)
- Chrome extensions:
import "crx" — permissions, permhash() (v1.11.0+). Always crx.is_crx first.
- Android:
import "dex" — dex.contains_class(), contains_method(), contains_string(). API differs from legacy YARA dex module.
See references/platform_modules_pe_crx_dex.md.
6. Deploy
- Naming:
{CATEGORY}_{PLATFORM}_{FAMILY}_{VARIANT}_{DATE} (e.g. MAL_Win_Emotet_Loader_Jan26)
- Peer review + quality checklist
- Monitor production FPs; version rules in Git with full metadata
See references/style_metadata_and_deployment.md.
Decision trees (quick reference)
Is this string good enough?
< 4 bytes? → reject
Repeated bytes (0000, 9090)? → reject
API name or common path? → reject
Unique to family? → use
Common across malware? → combine with family-specific marker
any of vs all of
- Individually unique strings →
any of ($a*)
- Common strings that are suspicious only together →
all of ($a*)
- Mixed confidence →
all of ($core_*) and any of ($variant_*)
Production lesson: any of ($network_*) with fetch, axios, http matches most web apps — require credential path and exfil destination and network call.
When strings fail → pivot
Use yr dump -m pe for sections, imports, imphash, resources; math.entropy() on sections; packer signatures. If nothing unique remains, YARA alone may not be the right control.
Legacy YARA migration
yr check --relaxed-re-syntax rules/
yr check rules/
Common fixes: escape \{ in regex; base64 strings need 3+ chars; @a[-1] → @a[#a - 1]; remove duplicate modifiers.
Rationalizations to reject
| Thought | Reality |
|---|
| "yarGen gave me these strings" | yarGen suggests; you validate each string |
| "It works on 10 samples" | Test goodware corpus before deploy |
| "I'll tighten after FPs" | FPs burn trust — write tight rules upfront |
| "This API name is malicious" | Legitimate software uses the same APIs |
| "any of them is fine" | Common strings + any = FP flood |
Quality checklist
When to load references
| Topic | Reference |
|---|
| YARA-X install, CLI, migration, toolkit | references/yara_x_scope_and_tooling.md |
| String quality, types, modifiers | references/string_selection_and_atoms.md |
| Atoms, condition order, regex, loops | references/conditions_and_performance.md |
| PE, macOS, JS, crx, dex patterns | references/platform_modules_pe_crx_dex.md |
| Goodware testing, FP debugging | references/testing_goodware_and_fp_debugging.md |
| Naming, metadata, deployment | references/style_metadata_and_deployment.md |