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://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
references/testing.md
YARA-X Rule Testing
Testing is non-negotiable. Untested rules cause alert fatigue (false positives) or missed detections (false negatives).
Testing Philosophy
Every rule needs three validation stages:
Positive validation — Matches all target samples
Negative validation — Zero matches on goodware
Edge case validation — Handles variants, packed versions, fragments
Validation Workflow
┌──────────────────────┐
│ Write initial rule │
└──────────┬───────────┘
│
▼
┌──────────────────────┐
│ yr check (validate) │──── Fix issues ────┐
└──────────┬───────────┘ │
│ │
▼ │
┌──────────────────────┐ │
│ Lint (style checks) │──── Fix issues ────┤
└──────────┬───────────┘ │
│ │
▼ │
┌──────────────────────┐ │
│ Test vs. samples │──── Missing? ──────┤
└──────────┬───────────┘ (widen rule) │
│ │
▼ │
┌──────────────────────┐ │
│ Test vs. goodware │──── FPs? ──────────┤
└──────────┬───────────┘ (tighten rule) │
│ │
▼ │
┌──────────────────────┐ │
│ Peer review │──── Issues? ───────┘
└──────────┬───────────┘
│
▼
┌──────────────────────┐
│ Deploy to production │
└──────────────────────┘Validation with yr check
Always validate rules before testing:
# Basic validation
yr check rule.yar
# Validate directory
yr check rules/
# Migration mode (identifies legacy YARA compatibility issues)
yr check --relaxed-re-syntax rules/Note: Use
--relaxed-re-syntaxonly as a temporary diagnostic tool during migration. Fix all identified issues rather than relying on relaxed mode permanently.
YARA-X provides better error messages than legacy YARA, with precise source locations for issues.
Goodware Testing
Platform-Specific Goodware
Test against legitimate software in your target ecosystem, not just Windows binaries:
| Platform | Goodware Corpus |
|---|---|
| PE files | VirusTotal goodware, clean Windows installs |
| JavaScript/Node | Popular npm packages (lodash, react, express, axios) |
| VS Code extensions | Top 100 marketplace extensions by installs |
| Browser extensions | Chrome Web Store popular extensions |
| npm packages | Top 100+ packages by weekly downloads |
| Python packages | Top PyPI packages (requests, django, flask) |
Critical: A rule that fires on legitimate software in your target ecosystem is useless. VT's goodware corpus is PE-centric — supplement with ecosystem-appropriate files.
Goodware Corpus Selection
Not all goodware is equal. Choose corpus that matches your rule's target:
| Rule Target | Minimum Goodware Corpus |
|---|---|
| PE files | Chrome, Firefox, Adobe Reader, Microsoft Office, Python installer |
| JavaScript | lodash, react, express, webpack, electron |
| npm packages | Top 100 by weekly downloads + packages with postinstall scripts |
| Chrome extensions | Top 50 marketplace extensions |
Expert baseline: "Test against Chrome, Firefox, and Adobe Reader" — Kaspersky Applied YARA
Interpreting Goodware Matches
Rule matched goodware — now what?
├─ Matched 1-2 files?
│ └─ Investigate: is the match legitimate? Add exclusion or tighten string
├─ Matched 3-5 files?
│ └─ Pattern is too common — find different indicators
├─ Matched 6+ files?
│ └─ Rule is fundamentally broken — start over
└─ Matched only one vendor's software?
└─ Add vendor exclusion: `not $fp_vendor`VirusTotal Goodware Corpus (Recommended)
The gold standard. VirusTotal maintains a corpus of 1M+ clean files from major software vendors.
Upload your rule to VirusTotal Intelligence
Select "Goodware" corpus
Run retrohunt
Review any matches — each is a potential false positive
Interpreting results:
| Matches | Assessment | Action |
|---|---|---|
| 0 | Excellent | Proceed to deployment |
| 1-2 | Investigate | Review matches, add exclusions or tighten strings |
| 3-5 | Too common | Find different indicators |
| 6+ | Broken | Start over with different indicators |
Local Testing
# Should return zero matches
yr scan -r rules/ /path/to/goodware/
# Count matches (quiet mode)
yr scan -c rules/ /path/to/goodware/yarGen Database Lookup
Before deployment, check strings against yarGen's goodware database:
# Query strings against goodware database
uv run --no-project --with-requirements requirements.txt python db-lookup.py -f strings.txtStrings appearing in the database are likely to cause false positives.
YARA-CI
YARA-CI provides cloud-based validation:
Connect GitHub repository
Each PR automatically tested
Reports syntax errors and performance issues
Integrates with VT goodware corpus
Free Testing Alternatives
Not everyone has VirusTotal Intelligence access. Here are free alternatives:
Free Online Tools
| Tool | Purpose | Access |
|---|---|---|
| YARA-CI | GitHub App tests PRs against 1M NIST goodware files | Free, github.com/apps/virustotal-yara-ci |
| YaraDbg | Web-based rule debugger with step-through execution | Free, yaradbg.dev |
| Klara | Kaspersky's distributed YARA scanner | Open source, self-hosted |
YARA-CI Setup
YARA-CI is the best free option for automated testing:
# 1. Install GitHub App from github.com/apps/virustotal-yara-ci
# 2. Connect your rules repository
# 3. Each PR automatically tested against 1M+ goodware files
# 4. View results at yara-ci.cloud.virustotal.comResults include:
Syntax validation
Performance warnings
Goodware matches (potential FPs)
Slowloris detection (rules that timeout)
Building a Local Goodware Corpus
For offline testing, build your own corpus:
Windows PE files:
# Fresh Windows 11 VM → export C:\Windows\System32\*.dll
# Download Chrome, Firefox, Adobe Reader installers
# Python/Node installers from official sourcesnpm/JavaScript packages:
# Download top packages
npm pack lodash react express axios webpack
# Extract for scanning
for f in *.tgz; do tar -xzf "$f"; doneChrome extensions:
# Export installed extensions from chrome://extensions (Developer mode)
# Or download .crx files from Chrome Web Store using extension IDmacOS applications:
# Copy from /Applications/ on a fresh macOS install
# System binaries from /usr/bin/, /usr/sbin/NIST NSRL
The NIST National Software Reference Library provides hash sets of known-good files:
Size: ~147GB compressed
Contains: Hashes from legitimate software
Use: Filter known-good files before scanning
# Download RDS (Reference Data Set)
# Available at: https://www.nist.gov/itl/ssd/software-quality-group/nsrl-download-links
# Use to exclude known-good files from your corpusmacOS XProtect
Apple's built-in YARA rules are a good reference:
# Location on macOS
/System/Library/CoreServices/XProtect.bundle/Contents/Resources/XProtect.yara
# View rules (requires SIP disabled or extraction from DMG)
cat /System/Library/CoreServices/XProtect.bundle/Contents/Resources/XProtect.yaraXProtect rules demonstrate Apple's production patterns for macOS malware detection.
Minimum Local Corpus by Platform
| Rule Target | Minimum Local Corpus |
|---|---|
| PE files | Chrome.exe, Firefox.exe, python.exe (10+ files) |
| npm packages | lodash, react, express, webpack (top 50 by downloads) |
| Chrome extensions | uBlock Origin, React DevTools, Grammarly (top 20) |
| macOS | /Applications/* from fresh install |
| Android DEX | Top 10 Play Store apps (extracted APKs) |
Malware Sample Testing
Positive Testing
# Rule should match all target samples
yr scan -r MAL_Win_Emotet.yar samples/emotet/
# With matched strings shown
yr scan -s MAL_Win_Emotet.yar samples/emotet/
# Expected: all files listed
# If any missing: rule too narrowVariant Coverage
Test against:
Multiple versions/builds
Packed variants (UPX, custom packers)
Different configurations
Both 32-bit and 64-bit
False Positive Investigation
When a rule matches goodware:
1. Identify the Match
yr scan -s rule.yar false_positive.exeShows which strings matched.
2. Analyze Why
Common causes:
String too generic ("cmd.exe", API names)
Shared library code
Common development patterns
Legitimate use of same techniques
3. Remediation Options
Option A: Exclude the specific file
strings:
$fp_vendor = "Legitimate Software Inc"
condition:
$malware_string and not $fp_vendorOption B: Add distinguishing string
strings:
$generic = "common_string"
$specific = "unique_malware_marker"
condition:
$generic and $specific // Both requiredOption C: Tighten positional constraints
condition:
$marker in (0..1024) and // Only in first 1KB
filesize < 500KB // Malware-typical sizeOption D: Replace the string
Find a more unique indicator and remove the problematic string.
Supply Chain Package Testing
For npm/PyPI/RubyGems rules, test against ecosystem-appropriate corpora:
Recommended Test Corpora
| Corpus | Source | Purpose |
|---|---|---|
| Top 1000 npm packages | npm search --searchlimit=1000 | Avoid FPs on popular dependencies |
| Packages with postinstall scripts | Filter for scripts.postinstall in package.json | Common attack vector |
| Known malicious packages | npm-shai-hulud-scanner list | Positive validation |
| VS Code top extensions | Marketplace API | Extension-specific rules |
Common Attack Pattern Testing
Critical pattern: postinstall + network call + credential path is the signature of supply chain attacks. Test that your rule catches this combo while ignoring legitimate build scripts.
# Build a test corpus from npm
mkdir -p test_corpus/legitimate test_corpus/suspicious
# Grab legitimate packages with postinstall (build tools)
npm pack webpack && tar -xzf webpack-*.tgz -C test_corpus/legitimate/
npm pack electron-builder && tar -xzf electron-builder-*.tgz -C test_corpus/legitimate/
# Your rule should NOT match legitimate postinstall scripts
yr scan -r supply_chain_rule.yar test_corpus/legitimate/
# Expected: zero matchesKnown Malicious Package Patterns
Rules targeting supply chain attacks should detect patterns from documented incidents:
| Incident | Key Indicators | Reference |
|---|---|---|
| chalk/debug (Sept 2025) | runmask, checkethereumw, ERC-20 selectors | Stairwell |
| os-info-checker-es6 | Variation selectors, eval+atob | Veracode |
| event-stream | Flatmap dependency, Bitcoin wallet targeting | npm advisory |
Positive validation: Test your rule against recreated (defanged) versions of known malicious packages to ensure detection.
Checklist
Before any rule goes to production:
[ ]
yr checkpasses (syntax and YARA-X compatibility)[ ]
yr fmt --checkpasses (consistent formatting)[ ] Linter passes (
uv run yara_lint.py rule.yar)[ ] Matches all target samples (positive testing)
[ ] Zero matches on goodware corpus (negative testing)
[ ] Tested against packed variants if applicable
[ ] Performance acceptable (< 1s per file on average)
[ ] Peer reviewed by second analyst
[ ] Version and changelog updated
Supply Chain Rule Additions
[ ] Tested against top 100 packages in target ecosystem
[ ] Does not match legitimate postinstall scripts (webpack, electron-builder, etc.)
[ ] Validated against known malicious package patterns
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 or Trail of Bits.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download yara-rule-authoring.zip