Yara Rule Authoring
Trail of BitsOfficialPublished by Trail of Bits
- Skill
- Guidelines
- Security
- CC-BY-SA-4.0
- Medium risk
- Has scripts
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
This skill provides a framework for creating and maintaining YARA-X detection rules. It covers best practices for string selection, condition design, and metadata, while offering specific guidance for analyzing Windows, macOS, JavaScript, Chrome extensions, and Android DEX files. The skill includes instructions for using provided scripts to lint rules, analyze string atoms, and perform comprehensive reviews to ensure rules meet established authoring standards.
What it does
- Provides conventions for naming, metadata, and rule structure.
- Offers techniques for string selection and false positive reduction.
- Details how to use YARA-X modules for CRX and DEX file analysis.
- Includes scripts for linting, atom analysis, and rule validation.
- Explains how to migrate legacy YARA rules to the YARA-X format.
- Outlines methods for testing rules against goodware corpora.
When to use it
- When writing new YARA-X rules for malware detection.
- When reviewing or optimizing existing YARA-X rulesets.
- When converting threat intelligence or IOCs into detection signatures.
- When debugging false positives in existing detection rules.
- When analyzing Chrome extensions or Android applications for malicious patterns.
Advantages
- Standardizes rule quality through linting and atom analysis.
- Reduces false positives by enforcing specific string and condition requirements.
- Provides clear guidance on YARA-X module usage for complex file formats.
- Facilitates consistent rule maintenance and peer review.
Usage examples
- “How do I check my YARA-X rule for syntax errors and formatting?”
- The agent will instruct you to use 'yr check rule.yar' for syntax validation and 'yr fmt -w rule.yar' to standardize the rule's formatting.
- “What is the best way to review a YARA-X rule for performance and style?”
- The agent will guide you to use the provided review script, which runs linting and atom analysis to identify issues like short strings or unbounded regex.
- “How can I detect malicious Chrome extensions using YARA-X?”
- The agent will explain how to import the 'crx' module and use fields like 'crx.permissions' to flag high-risk extension behaviors.
- “How do I migrate a legacy YARA rule to YARA-X?”
- The agent will provide steps to use 'yr check --relaxed-re-syntax' to identify compatibility issues and explain how to fix them manually.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/trailofbits/yara-rule-authoring/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip yara-rule-authoring.zip -d .agents/skills
Documentation by Trail of Bits
YARA-X Rule Authoring
Write detection rules that catch malware without drowning in false positives.
Resolve the linter, atom analyzer,
and review helper from this installed SKILL.md's directory.
In commands below, replace each <resolved-...-path> with that script's absolute
path and keep the quotes. The rule file or directory is still relative to your
working directory unless you pass an absolute input path.
This skill targets YARA-X, the Rust-based successor to legacy YARA — 5-10x faster regex, better errors, built-in formatter, stricter validation, new modules (crx, dex), 99% rule compatibility. It powers VirusTotal's production systems. Install with brew install yara-x or cargo install yara-x; the CLI is yr. See Migrating from Legacy YARA for existing rules.
Core Principles
Strings must generate good atoms — YARA extracts 4-byte subsequences for fast matching. Strings with repeated bytes, common sequences, or under 4 bytes force slow bytecode verification on too many files.
Target specific families, not categories — "Detects ransomware" catches everything and nothing. "Detects LockBit 3.0 configuration extraction routine" catches what you want.
Test against goodware before deployment — A rule that fires on Windows system files is useless. Validate against VirusTotal's goodware corpus or your own clean file set.
Short-circuit with cheap checks first —
filesize(instant), then magic bytes (nearly instant), then strings (cheap), then modules (expensive).Metadata is documentation — Future you (and your team) need to know what this catches, why, and where the sample came from.
When to Use
Writing new YARA-X rules for malware detection
Reviewing existing rules for quality or performance issues
Optimizing slow-running rulesets
Converting IOCs or threat intel into detection signatures
Debugging false positive issues
Preparing rules for production deployment
Migrating legacy YARA rules to YARA-X
Analyzing Chrome extensions (crx module) or Android apps (dex module)
When NOT to Use
Static analysis requiring disassembly → use Ghidra/IDA skills
Dynamic malware analysis → use sandbox analysis skills
Network-based detection → use Suricata/Snort skills
Memory forensics with Volatility → use memory forensics skills
Simple hash-based detection → just use hash lists
Platform Considerations
YARA works on any file type. Adapt patterns to your target:
| Platform | Magic Bytes | Bad Strings | Good Strings |
|---|---|---|---|
| Windows PE | uint16(0) == 0x5A4D | API names, Windows paths | Mutex names, PDB paths |
| macOS Mach-O | uint32(0) == 0xFEEDFACE (32-bit), 0xFEEDFACF (64-bit), uint32be(0) == 0xCAFEBABE (universal) | Common Obj-C methods | Keylogger strings, persistence paths |
| JavaScript/Node | (none needed) | require, fetch, axios | Obfuscator signatures, eval+decode chains |
| npm/pip packages | (none needed) | postinstall, dependencies | Suspicious package names, exfil URLs |
| Office docs | uint32(0) == 0x04034B50 | VBA keywords | Macro auto-exec, encoded payloads |
| VS Code extensions | (none needed) | vscode.workspace | Uncommon activationEvents, hidden file access |
| Chrome extensions | Use crx module | Common Chrome APIs | Permission abuse, manifest anomalies |
| Android apps | Use dex module | Standard DEX structure | Obfuscated classes, suspicious permissions |
uintNN()reads little-endian. Write the constant as the bytes reversed, or useuintNNbe()and write them in file order. A ZIP/OOXML file starts with bytes50 4B 03 04, so it isuint32(0) == 0x04034B50—uint32(0) == 0x504B0304compiles cleanly and never matches anything. The same trap catches Mach-O universal binaries: on disk they areCA FE BA BE, souint32(0) == 0xCAFEBABEis a dead branch; writeuint32be(0) == 0xCAFEBABEoruint32(0) == 0xBEBAFECA. Verify withyr scanagainst one known-good sample before trusting any magic-byte check.
macOS Malware Detection
No dedicated Mach-O module exists yet — use magic bytes plus string patterns. Good indicators:
Keylogger artifacts:
CGEventTapCreate,kCGEventKeyDownSSH tunnel strings:
ssh -D,tunnel,socksPersistence paths:
~/Library/LaunchAgents,/Library/LaunchDaemonsCredential theft:
security find-generic-password,keychain
// Pattern from Airbnb BinaryAlert
rule SUSP_Mac_ProtonRAT
{
strings:
$lib1 = "SRWebSocket" ascii // Library indicators
$lib2 = "SocketRocket" ascii
$behav1 = "SSH tunnel not launched" ascii // Behavioral indicators
$behav2 = "Keylogger" ascii
condition:
(uint32(0) == 0xFEEDFACF or uint32be(0) == 0xCAFEBABE) and
any of ($lib*) and any of ($behav*)
}JavaScript Detection
| Target | Approach |
|---|---|
| npm package | package.json patterns, postinstall/preinstall hooks, exfil combination: fetch + env access + credential paths |
| Chrome extension | crx module |
| Other extension | Manifest patterns, background script behaviors |
| Standalone JS | Obfuscation markers (eval+atob, fromCharCode chains), unique function/variable names, packed payloads |
| Minified/webpack bundle | Unique strings that survive bundling (URLs, magic values); avoid function names — they get mangled |
Good JS strings: Ethereum function selectors — { a9 05 9c bb } (transfer(address,uint256)), { 70 a0 82 31 } (balanceOf(address)); zero-width characters for steganography — { E2 80 8B E2 80 8C }; obfuscator signatures — _0x, var _0x; specific C2 domains and webhook URLs.
Bad JS strings: require, fetch, axios (too common); Buffer, crypto (legitimate uses everywhere); process.env alone (need specific env var names).
String Selection
Value ranking: mutex names are gold, C2 paths silver, error messages bronze. Stack strings are almost always unique. If you need more than 6 strings, you're over-fitting.
Reject a candidate string when any of these holds:
| Test | Why it fails | Do instead |
|---|---|---|
| Under 4 bytes | No atom | Find a longer string |
Repeated bytes (0000, 9090) | Weak atom | Add surrounding context |
API name (VirtualAlloc, CreateRemoteThread) | Every packer and installer calls it | Hex pattern of the call site plus a unique marker |
| Appears in Windows system files | Guaranteed FPs | Find something family-specific |
Common path (C:\Windows\, cmd.exe) | Ubiquitous | Find malware-specific paths |
| Appears in other malware families | Not identifying this family | Combine with a family-specific marker |
Everything left — unique to this family — is what the rule should rest on.
Choosing a String Type
| Need | Use |
|---|---|
| Exact ASCII/Unicode text | $s = "MutexName" ascii wide |
| Specific byte sequence | $h = { 4D 5A 90 00 } |
| Byte sequence with variation | Hex wildcards: { 4D 5A ?? ?? 50 45 } |
| Pattern with structure (URLs, paths) | Bounded regex: /https:\/\/[a-z]{5,20}\.onion/ |
| Unknown encoding (XOR, base64) | Modifier: $s = "config" xor(0x00-0xFF) |
Modifier discipline: never use nocase or wide speculatively — only with confirmed evidence that case or encoding varies across samples. nocase doubles atom generation; wide doubles string matching. "If you don't have a clear reason for using those modifiers, don't do it" — Kaspersky Applied YARA.
Condition Design
Order for short-circuit: filesize <, magic bytes, strings, modules. If the condition runs past 5 lines, split into multiple rules.
all of vs any of
| Situation | Use |
|---|---|
| Strings are individually unique to the malware | any of them — each alone is suspicious |
| Strings are common but the combination is suspicious | all of them — require the full pattern |
| Strings have different confidence levels | Group: all of ($core_*) and any of ($variant_*) |
| Seeing false positives | Tighten: any → all, add more required strings |
Lesson from production: rules using any of ($network_*) where the strings included fetch, axios, and http matched virtually all web applications. Switching to require a credential path AND a network call AND an exfil destination eliminated the FPs.
Grouping by Confidence
Different indicator types carry different weight — a C2 domain might be definitive while library imports need corroboration. Grouping by prefix lets you express graduated requirements:
strings:
$a1 = "SRWebSocket" ascii // Category A: library indicators
$a2 = "SocketRocket" ascii
$b1 = "SSH tunnel" ascii // Category B: behavioral
$b2 = "keylogger" ascii nocase
$c1 = /https:\/\/[a-z0-9]{8,16}\.onion/ // Category C: C2
condition:
filesize < 10MB and
any of ($a*) and any of ($b*) // Evidence from BOTH categoriesModules vs Byte Checks
| Need | Use |
|---|---|
| imphash, rich header, authenticode | PE module — too complex to replicate |
| Magic bytes or simple offsets | uint16/uint32 — faster, no module overhead |
| Section names/sizes | PE module, but put the magic-byte filter FIRST |
| Chrome extension permissions | crx module — string parsing is fragile |
| LNK target paths | lnk module — the format is complex |
"Avoid the magic module — use explicit hex checks instead" — Neo23x0. Generalize it: if uint32() can do the job, don't load a module.
Performance
Regex must be anchored to a 4+ byte literal. Without one it evaluates at every file offset — catastrophic. Write
/mshta\.exe http:\/\/.../, not/http:\/\/.../. If you can't anchor, use a hex pattern with wildcards.Bound every regex quantifier —
.{0,30}, never.*. Unbounded regex is both a performance disaster and a memory explosion.Bound loops with filesize —
filesize < 100KB and for all i in (1..#a) : .... Unbounded#acan reach thousands in large files.Prefer hex over regex where the bytes are fixed.
Before Writing: Is the Sample Packed?
| Signal | What to do |
|---|---|
| Entropy > 7.0 | Likely packed — find the unpacked layer first |
| Few or no readable strings | Likely packed — use entropy, PE structure, or packer signatures |
| UPX/MPRESS/custom packer detected | Target the unpacked payload OR detect the packer itself |
| Readable strings available | Proceed with string-based detection |
Don't write rules against packed layers. The packing changes; the payload doesn't.
When Strings Fail, Pivot to Structure
If extraction returns only API names and generic paths:
| Available signal | Use |
|---|---|
| High entropy sections | math.entropy() on specific sections |
| Unusual import pattern | pe.imphash() for import-hash clustering |
| PE structure anomalies | Section names, sizes, characteristics |
| Metadata present | Version info, timestamps, resources |
| Nothing unique | This sample may not be detectable with YARA alone |
"One can try to use other file properties, such as metadata, entropy, import hashes or other data which stays constant." — Kaspersky Applied YARA Training
Debugging False Positives
Which string matched? —
yr scan -s rule.yar false_positive.exeIn a legitimate library? — add a
not $fp_vendor_stringexclusionA common development pattern? — replace the string with something more specific
Multiple generic strings matching together? — tighten to require all, plus a unique marker
Malware using a common technique? — target its specific implementation details, not the technique
When to Abandon the Approach
Extraction returns only API names and paths → pivot to structure
Can't find 3 unique strings → probably packed; target the unpacked version or detect the packer
Rule matches goodware → 1-2 matches: investigate and tighten; 3-5: find different indicators; 6+: start over
Performance is terrible after optimization → architecture problem; split into focused rules or add strict pre-filters
The description is hard to write → the rule is too vague. If you can't explain what it catches, it catches too much
Rationalizations to Reject
When you catch yourself thinking these, stop and reconsider.
| Rationalization | Expert Response |
|---|---|
| "This generic string is unique enough" / "This hex pattern is unique" | Unique in one sample ≠ unique across the ecosystem. Test against goodware; your intuition is wrong. |
| "yarGen gave me these strings" | yarGen suggests, you validate. Check each one manually — expect to discard 80%. |
| "It works on my 10 samples" | 10 samples ≠ production. Use a goodware corpus. |
| "One rule to catch all variants" | Causes FP floods. Target specific families. |
| "I'll make it more specific if we get FPs" / "I'll add more conditions later" | Write tight rules upfront. A weak rule deployed is damage done, and FPs burn trust. |
| "This is just for hunting" | Hunting rules become detection rules. Same quality bar. |
| "The API name makes it malicious" | Legitimate software uses the same APIs. Need behavioral context. |
"any of them is fine for these common strings" | Common strings + any = FP flood. Use any of only for individually unique strings. |
| "This regex is specific enough" | /fetch.*token/ matches all auth code. Add an exfil destination requirement. |
"I'll use .* for flexibility" | Unbounded regex = performance disaster plus memory explosion. Use .{0,30}. |
| "The JavaScript looks clean" | Attackers poison legitimate code with injects. Check for eval+decode chains. |
| "Performance doesn't matter" | One slow rule slows the entire ruleset. Optimize atoms. |
"I'll use --relaxed-re-syntax everywhere" | Masks real bugs. Fix the regex instead of hiding the problem. |
| "PEiD rules still work" | Obsolete. 32-bit packers aren't relevant. |
Toolkit
| Tool | Purpose |
|---|---|
| yr CLI | yr check (validate), yr fmt (format), yr scan -s (scan, show strings), yr dump -m pe (inspect structure) |
| yarGen | Extract candidate strings: yarGen.py -m samples/ --excludegood |
| FLOSS | Extract obfuscated/stack strings: floss sample.exe — when yarGen comes up empty |
| signature-base | Study quality examples |
| YARA-CI | Goodware corpus testing before deployment |
Master these five. Don't get distracted by tool catalogs.
Development cycle:
yr check rule.yar # syntax, with precise line numbers
yr fmt -w rule.yar # standardize formatting
yr dump -m pe sample.exe --output-format yaml # inspect structure, no dummy rule needed
time yr scan -s rule.yar corpus/ # scan with timingReach for yr dump when investigating which module fields are available, debugging why a module condition isn't matching, or exploring a new module (crx, lnk, dotnet) before writing against it. YARA-X error messages carry precise source locations — if yr check says line 15, the problem is on line 15.
Version-gated features: private $helper = "pattern" matches but stays out of output (v1.3.0+); // suppress: slow_pattern silences a specific warning inline (v1.4.0+); filesize < 10_000_000 numeric underscores (v1.5.0+). $_unused also suppresses unused-string warnings.
Chrome Extension Analysis (crx module)
Requires YARA-X v1.5.0+, or v1.11.0+ for permhash().
Key APIs: crx.is_crx, crx.permissions, crx.permhash()
Red flags: nativeMessaging + downloads, debugger permission, content scripts on <all_urls>
import "crx"
rule SUSP_CRX_HighRiskPerms {
condition:
crx.is_crx and
for any perm in crx.permissions : (perm == "debugger")
}See crx-module.md for the full API, permission risk assessment, and example rules.
Android DEX Analysis (dex module)
Requires YARA-X v1.11.0+. Not compatible with legacy YARA's dex module — the API is completely different.
Key APIs: dex.is_dex, dex.contains_class(), dex.contains_method(), dex.contains_string()
Red flags: single-letter class names (obfuscation), DexClassLoader reflection, encrypted assets
import "dex"
rule SUSP_DEX_DynamicLoading {
condition:
dex.is_dex and
dex.contains_class("Ldalvik/system/DexClassLoader;")
}See dex-module.md for the full API, obfuscation detection, and example rules.
Migrating from Legacy YARA
99% rule compatibility, but stricter validation:
yr check --relaxed-re-syntax rules/ # identify issues
# fix each one, then verify without relaxed mode:
yr check rules/| Issue | Legacy | YARA-X Fix |
|---|---|---|
Literal { in regex | /{/ | /\{/ |
| Invalid escapes | \R silently literal | \\R or R |
| Base64 strings | Any length | 3+ chars required |
| Negative indexing | @a[-1] | @a[#a - 1] |
| Duplicate modifiers | Allowed | Remove duplicates |
--relaxed-re-syntax is a diagnostic, not a destination. Fix the regex.
Naming and Metadata
{CATEGORY}_{PLATFORM}_{FAMILY}_{VARIANT}_{DATE} e.g. MAL_Win_Emotet_Loader_Jan25Categories: MAL_ (malware), HKTL_ (hacking tool), WEBSHELL_, EXPL_, SUSP_ (suspicious), GEN_ (generic). Platforms: Win_, Lnx_, Mac_, Android_, CRX_.
Every rule needs description (starting with "Detects"), author, reference, and date:
meta:
description = "Detects Example malware via unique mutex and C2 path"
author = "Your Name <[email protected]>"
reference = "https://example.com/analysis"
date = "2025-01-29"See style-guide.md for full conventions.
Workflow
Gather samples — multiple; single-sample rules are brittle
Extract candidates —
yarGen -m samples/ --excludegoodValidate quality — apply the string selection tests; expect to discard 80% of yarGen output
Write the rule — proper metadata, cheap checks first
Lint and test —
yr check,yr fmt, the linter scriptGoodware validation — VirusTotal corpus or local clean files
Deploy — full metadata, then monitor for FPs
Quality signals along the way: a rule matching under 50% of known variants is too narrow; one matching goodware is too broad.
Reviewing a rule someone else wrote — run both scripts before reading the rule by eye, and quote the codes they emit:
uv run "<resolved-yara-lint-path>" suspect.yar # style, metadata, YARA-X compatibility
uv run "<resolved-atom-analyzer-path>" suspect.yar # atom quality per stringShortcut: "<resolved-review-path>" suspect.yar (a rule file or a directory)
runs yr check, yr fmt --check, the linter and the atom analyzer in one call
and prints one JSON object, {"target": ..., "checks": {"yr_check", "yr_format", "lint", "atoms"}}, each with status (the tool's exit code) and its output.
It exits 0 when every check passes, 1 when any check fails, and 2 for a missing,
empty or unreadable input (nothing was inspected). Quote the codes from
checks.lint.output exactly as with the separate scripts.
They catch the mechanical faults — short strings, FP-prone substrings, unbounded quantifiers, expensive terms ahead of cheap ones — so your attention goes to the judgement calls they cannot make: whether the strings identify this family, and whether the condition can fire on generic strings alone. Report findings by code (E002, W009) so the author can look each one up in style-guide.md.
See testing.md for the validation workflow and rule-development.md for the full step-by-step guide.
Common Mistakes
| Mistake | Bad | Good |
|---|---|---|
| API names as indicators | "VirtualAlloc" | Hex pattern of call site + unique mutex |
| Unbounded regex | /https?:\/\/.*/ | /https?:\/\/[a-z0-9]{8,12}\.onion/ |
| Missing file type filter | pe.imports(...) first | uint16(0) == 0x5A4D and filesize < 10MB first |
| Short strings | "abc" (3 bytes) | "abcdef" (4+ bytes) |
| Unescaped braces (YARA-X) | /config{key}/ | /config\{key\}/ |
| Wrong-endian magic bytes | uint32(0) == 0xCAFEBABE | uint32be(0) == 0xCAFEBABE |
Quality Checklist
Before deploying any rule:
[ ] Name follows
{CATEGORY}_{PLATFORM}_{FAMILY}_{VARIANT}_{DATE}[ ] Description starts with "Detects" and explains what/how
[ ] All required metadata present (author, reference, date)
[ ] Strings are unique — not API names, common paths, or format strings
[ ] All strings 4+ bytes with good atom potential
[ ] Base64 modifier only on strings with 3+ characters
[ ] Regex bounded, anchored to a literal, with
{escaped[ ] Condition starts with cheap checks (filesize, magic bytes)
[ ] Magic-byte constants verified against a known-good sample
[ ] Rule matches all target samples
[ ] Rule produces zero matches on the goodware corpus
[ ]
yr checkandyr fmt --checkpass[ ] Linter passes with no errors
[ ] Peer review completed
Scripts
uv run "<resolved-yara-lint-path>" rule.yar # validate style/metadata
uv run "<resolved-atom-analyzer-path>" rule.yar # check string quality
"<resolved-review-path>" rule.yar # all four checks, one JSON resultSee README.md for detailed script documentation.
Further Reading
| Topic | Document |
|---|---|
| Naming and metadata conventions | style-guide.md |
| Performance and atom optimization | performance.md |
| String types and judgment | strings.md |
| Testing and validation | testing.md |
| Chrome extension module (crx) | crx-module.md |
| Android DEX module (dex) | dex-module.md |
| Complete rule development process | rule-development.md |
The examples/ directory holds real, attributed rules worth reading before writing your own:
| Example | Demonstrates | Source |
|---|---|---|
| MAL_Win_Remcos_Jan25.yar | PE malware: graduated string counts, multiple rules per family | Elastic Security |
| MAL_Mac_ProtonRAT_Jan25.yar | macOS: Mach-O magic bytes, multi-category grouping | Airbnb BinaryAlert |
| MAL_NPM_SupplyChain_Jan25.yar | npm supply chain: real attack patterns, ERC-20 selectors | Stairwell Research |
| SUSP_JS_Obfuscation_Jan25.yar | JavaScript: obfuscator detection, density-based matching | imp0rtp3, Nils Kuhnert |
| SUSP_CRX_SuspiciousPermissions.yar | Chrome extensions: crx module, permissions | Educational |
Rule repositories to learn from: Neo23x0/signature-base (17,000+ production rules), elastic/protections-artifacts (endpoint-tested), imp0rtp3/js-yara-rules (JavaScript), InQuest/awesome-yara (curated index).
Guides: YARA Style Guide and YARA Performance Guidelines (Neo23x0), YARA-X documentation.
macOS specifics: Apple's own production rules ship at /System/Library/CoreServices/XProtect.bundle/; objective-see publishes macOS malware research and samples.
Files
- ATTRIBUTION.mdAdded by AutoGineer946 B
- LICENSELicence file added by AutoGineer19.7 KiB
- SKILL.md24.2 KiB
- agents/openai.yaml236 B
- assets/trail-of-bits-mark.svg3.0 KiB
- examples/MAL_Mac_ProtonRAT_Jan25.yar3.2 KiB
- examples/MAL_NPM_SupplyChain_Jan25.yar5.3 KiB
- examples/MAL_Win_Remcos_Jan25.yar3.1 KiB
- examples/SUSP_CRX_SuspiciousPermissions.yar4.2 KiB
- examples/SUSP_JS_Obfuscation_Jan25.yar5.7 KiB
- references/crx-module.md7.3 KiB
- references/dex-module.md10.1 KiB
- references/performance.md8.7 KiB
- references/strings.md11.6 KiB
- references/style-guide.md9.3 KiB
- references/testing.md13.1 KiB
- scripts/atom_analyzer.pyScript4.6 KiB
- scripts/pyproject.toml553 B
- scripts/review.shScript2.9 KiB
- scripts/test_yara_rules.pyScript17.7 KiB
- scripts/uv.lock3.4 KiB
- scripts/yara_lint.pyScript4.7 KiB
- scripts/yara_rules.pyScript30.4 KiB
- workflows/rule-development.md13.2 KiB
workflows/rule-development.md
YARA Rule Development Workflow
This guide walks through the complete process of developing a production-quality YARA-X rule, from sample collection to deployment.
Resolve <resolved-yara-lint-path> to the absolute path of the
linter in the installed skill before using the command below.
Overview
┌─────────────────┐
│ Sample Collection│
└────────┬────────┘
▼
┌─────────────────┐
│ String Extraction│
└────────┬────────┘
▼
┌─────────────────┐
│ Rule Writing │
└────────┬────────┘
▼
┌─────────────────┐
│ Validation │
└────────┬────────┘
▼
┌─────────────────┐
│ Goodware Testing │
└────────┬────────┘
▼
┌─────────────────┐
│ Deployment │
└─────────────────┘Phase 1: Sample Collection
Minimum Requirements
| Sample Count | Confidence Level | Recommended For |
|---|---|---|
| 1 sample | Low (fragile rule) | Urgent threat, will refine later |
| 3-5 samples | Medium | Standard detection |
| 10+ samples | High | Stable, long-term rule |
Single-sample rules are brittle. The malware author changes one string and your rule is useless.
Gathering Variants
Hash pivot — Search VT for related hashes (imphash, ssdeep, TLSH)
Behavior pivot — Search for samples with same C2, mutex, or dropped files
Infrastructure pivot — Samples communicating with related domains/IPs
Time pivot — Samples submitted around the same campaign window
Packed vs. Unpacked
Check before proceeding:
# Check entropy
yr dump -m math sample.exe --output-format yaml | grep entropy
# Check strings count
strings sample.exe | wc -l| Indicator | Likely Packed | Action |
|---|---|---|
| Entropy > 7.0 | Yes | Unpack first or detect packer |
| < 50 readable strings | Probably | Unpack first |
| UPX/MPRESS signatures | Yes | Unpack with upx -d |
Expert rule: Don't write string-based rules against packed samples. Either unpack first or write a rule targeting the packer itself.
Using yr dump for File Analysis
Before writing rules, inspect the sample's structure with YARA-X's native yr dump:
# Inspect PE structure (imports, exports, sections, resources)
yr dump -m pe sample.exe --output-format yaml
# Check entropy (indicates packing)
yr dump -m math sample.exe --output-format yaml | grep entropy
# For Chrome extensions
yr dump -m crx extension.crx --output-format yaml
# For Android apps
yr dump -m dex classes.dex --output-format yamlyr dump shows exactly what YARA-X modules can see. Use this to:
Understand available fields before writing conditions
Debug why module conditions aren't matching
Find unique structural indicators when strings fail
Phase 2: String Extraction
Using yarGen
yarGen extracts candidate strings but generates legacy YARA syntax. Always validate output for YARA-X compatibility.
# Basic extraction
cd yarGen # run from the yarGen checkout, where requirements.txt lives
uv run --no-project --with-requirements requirements.txt python yarGen.py -m samples/ --excludegood -o candidate_rule.yar
# Recommended flags
uv run --no-project --with-requirements requirements.txt python yarGen.py -m samples/ \
--excludegood \ # Filter against known goodware strings
-g /path/to/good/files \ # Add custom goodware
--nosimple \ # Exclude simple strings
--nomagic \ # Don't add magic header checks (do manually)
-o candidate_rule.yar
# CRITICAL: Validate for YARA-X compatibility
yr check candidate_rule.yar
yr fmt -w candidate_rule.yar # Apply YARA-X formattingCommon yarGen → YARA-X fixes:
Escape literal
{in regex:/{/→/\{/Fix invalid escapes:
\R→\\RorRRemove duplicate modifiers
FLOSS for Packed/Obfuscated Samples
When yarGen returns only API names or the sample appears packed, use FLOSS:
# Extract all string types (static, stack, tight, decoded)
floss sample.exe -o strings.txt
# Quick extraction (faster, less thorough)
floss --only static sample.exe
# For Go/Rust binaries (special handling)
floss --only go sample.exeFLOSS extracts:
Static strings — Same as
stringscommandStack strings — Built character-by-character at runtime
Tight strings — Small decoding loops
Decoded strings — From common encoding routines
Expert tip: Stack strings are often the most unique indicators. If FLOSS finds them, prioritize those over static strings.
# Look for unique patterns in FLOSS output
sort strings.txt | uniq -c | sort -rn | head -50Filtering Criteria
Reject 80% of yarGen output. Apply these filters:
| Category | Reject | Reason |
|---|---|---|
| API names | VirtualAlloc, CreateRemoteThread | Present in legitimate software |
| Common paths | C:\Windows\, %TEMP% | Too generic |
| Format strings | %s, %d\n, Error: %s | Present everywhere |
| Single words | config, data, error | Not specific enough |
| Short strings | < 4 bytes | Poor atom quality |
| Category | Keep | Reason |
|---|---|---|
| Mutex names | Global\\MyMutex123 | Unique to family |
| PDB paths | C:\Users\dev\project\x.pdb | Reveals dev environment |
| C2 paths | /api/beacon.php | Specific to campaign |
| Stack strings | Built char-by-char | Unique patterns |
| Error messages | Custom error text | Not library errors |
| Config markers | [CONFIG_START] | Family-specific format |
Phase 3: Rule Writing
Template
rule {CATEGORY}_{PLATFORM}_{FAMILY}_{VARIANT}_{DATE}
{
meta:
description = "Detects {WHAT} via {HOW}"
author = "Your Name <[email protected]>"
reference = "{URL to analysis or report}"
date = "{YYYY-MM-DD}"
modified = "{YYYY-MM-DD}"
hash = "{sample hash for reference}"
score = {confidence 0-100}
strings:
// Group 1: High-confidence unique indicators
$unique_mutex = "Global\\UniqueString123" ascii wide
$unique_pdb = "C:\\Dev\\Malware\\Release\\loader.pdb" ascii
// Group 2: Behavioral patterns (hex for specificity)
$decrypt_routine = { 8B 45 ?? 33 C1 C1 C0 0D }
// Group 3: Configuration/C2 patterns
$c2_path = "/api/v1/beacon" ascii
// Exclusions for known FPs (if needed)
$fp_legitimate = "Legitimate Vendor Inc" ascii
condition:
// 1. Cheap filters first
filesize < 5MB and
uint16(0) == 0x5A4D and
// 2. String matching logic
(
$unique_mutex or // Definitive alone
($unique_pdb and $c2_path) or // Two medium = high
(2 of ($decrypt_*, $c2_*)) // Behavioral combo
) and
// 3. Exclusions last
not $fp_legitimate
}Metadata Checklist
[ ]
descriptionstarts with "Detects" and explains what AND how[ ]
authorincludes contact info[ ]
referencelinks to analysis (not just "internal")[ ]
datein YYYY-MM-DD format[ ]
hashof at least one sample[ ]
scorereflects confidence (< 50 suspicious, 50-75 likely, > 75 confirmed malware)
Condition Ordering
Order by cost:
filesize < X— Instantuint16(0) == 0x5A4D— Near-instantString matches — Cheap with good atoms
forloops — Medium costModule calls — More expensive
Regex patterns — Most expensive
Bad:
condition:
pe.imports("kernel32.dll", "VirtualAlloc") and
$mutex and
filesize < 5MBGood:
condition:
filesize < 5MB and
uint16(0) == 0x5A4D and
$mutex and
pe.imports("kernel32.dll", "VirtualAlloc")Phase 4: Validation
Syntax Check
# Validate syntax
yr check rule.yar
# Validate entire directory
yr check rules/
# If migrating from legacy YARA, identify issues first
yr check --relaxed-re-syntax rule.yar
# Then fix each issue and validate without relaxed modeFormat Consistency
# Check formatting
yr fmt --check rule.yar
# Auto-format
yr fmt -w rule.yarLinter Check
# Run the skill's linter
uv run "<resolved-yara-lint-path>" rule.yarAll three must pass before proceeding.
Positive Testing
# Should match all samples
yr scan rule.yar samples/
# With matched strings shown
yr scan -s rule.yar samples/Expected: All target samples match.
If samples don't match:
Strings too specific → Use wildcards or alternatives
Condition too strict → Relax grouping
Packed variants → Create separate unpacked rule
Phase 5: Goodware Testing
Corpus Selection
| Target Platform | Recommended Corpus |
|---|---|
| Windows PE | Chrome, Firefox, Adobe Reader, Office, Python |
| JavaScript | lodash, react, express, webpack |
| npm packages | Top 100 by downloads + postinstall packages |
| Chrome extensions | Top 50 Web Store extensions |
| Android APK | Top 20 Play Store apps |
Local Testing
# Should return zero matches
yr scan rule.yar /path/to/goodware/
# Count matches
yr scan -c rule.yar /path/to/goodware/VirusTotal Retrohunt (Recommended)
Upload rule to VT Intelligence
Select "Goodware" corpus
Run retrohunt
Review every match — each is a potential FP
Interpreting Results
| Goodware Matches | Assessment | Action |
|---|---|---|
| 0 | Excellent | Proceed to deployment |
| 1-2 | Investigate | Check if legitimate FP, add exclusion or tighten |
| 3-5 | Too broad | Find different indicators |
| 6+ | Broken | Start over |
FP Investigation
# See which string matched
yr scan -s rule.yar false_positive.exeCommon fixes:
Add vendor exclusion:
not $fp_vendor_stringAdd distinguishing string: require unique + generic together
Add positional constraint:
$marker in (0..1024)Replace the string entirely with more specific indicator
Phase 6: Deployment
Peer Review Checklist
Before merge, reviewer checks:
[ ] Naming follows convention
[ ] Metadata complete and accurate
[ ] Strings justify confidence score
[ ] Condition ordered by cost
[ ] Tested against goodware
[ ] No obvious FP risks
[ ] Performance acceptable
Version Control
# Add to repo
git add rules/malware/MAL_Win_Example_Jan25.yar
# Commit with meaningful message
git commit -m "Add MAL_Win_Example detection rule
- Targets Example malware family loader component
- Based on samples from Jan 2025 campaign
- Tested against VT goodware (0 matches)
- Reference: https://example.com/analysis"Production Monitoring
After deployment:
Monitor for FPs — Set up alerting for first 48 hours
Track detection rate — Rule should detect new samples in the family
Review periodically — Malware evolves; rules need updates
Decision Points
When to Pivot from Strings to Structure
If yarGen returns only API names and paths:
→ Try pe.imphash() for import clustering
→ Try pe.rich_signature for build environment
→ Try math.entropy() on sections
→ Try pe module for section anomalies
→ If nothing works: sample may not be YARA-detectableWhen to Split vs. Combine Rules
Split when:
Different variants have no common strings
Performance degrades with combined rule
Different confidence levels needed
Combine when:
Variants share core indicators
Single rule can cover family with
any ofvariants
When to Abandon an Approach
Stop and pivot when:
| Situation | Action |
|---|---|
| Can't find 3 unique strings | Target unpacked version or detect packer |
| Goodware matches > 5 | Find completely different indicators |
| Performance > 2s per file | Split into focused rules |
| Can't write clear description | Rule is too vague — reconsider scope |
String Selection Quick Decision
Is this string good enough?
├─ Less than 4 bytes? → NO
├─ API name? → NO
├─ Common path? → NO
├─ In Windows/common libraries? → NO
├─ Unique to malware family? → YES
└─ In other malware too? → MAYBE (combine with unique marker)Quick Reference
Essential Commands
yr check rule.yar # Validate syntax
yr fmt -w rule.yar # Format
yr scan -s rule.yar file # Scan with matched strings
yr dump -m pe file.exe # Inspect PE structureRequired Metadata
meta:
description = "Detects X via Y"
author = "Name <email>"
reference = "URL"
date = "YYYY-MM-DD"Condition Order
filesizeMagic bytes (
uint16/uint32)Strings
Module calls
Goodware Thresholds
0 matches = Deploy
1-2 matches = Investigate
3-5 matches = Find new indicators
6+ matches = Start over
Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Needs Python
Security
What our scanner noticed· Medium risk
- References to credential files
- Scripts that your agent may run
This skill includes scripts that your agent may run. Read them before you use it.
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Published by
- Trail of Bits
- Publisher
- Trail of Bits (Official)
- Source
- trailofbits/skills · plugins/yara-authoring/skills/yara-rule-authoring · commit e4dd0bb
- Licence
- Creative Commons Attribution-ShareAlike 4.0 International (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by Trail of Bits.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download yara-rule-authoring.zip