본문으로 건너뛰기
cccskills
무료GitHub에 공개

binary-re-triage

Use when first encountering an unknown binary, ELF file, executable, or firmware blob. Fast fingerprinting via rabin2 - architecture detection (ARM, x86, MIPS), ABI identification, dependency mapping, string extraction. Keywords - "what is this binary", "identify architecture", "check file type", "rabin2", "file analysis", "quick scan"

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

설치 방법 보기

포함된 파일(2)

  • SKILL.md6.6 KB
  • skill-report.json46.8 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Binary Triage (Phase 1)

Purpose

Quick fingerprinting to establish baseline facts before deeper analysis. Runs in seconds, not minutes.

When to Use

  • First contact with an unknown binary
  • Need architecture/ABI info for tool selection
  • Quick capability assessment
  • Before committing to expensive analysis

Key Principle

Gather facts fast, defer analysis.

This phase identifies WHAT the binary is, not HOW it works.

Triage Sequence

Step 1: File Identification

# Basic identification
file binary

# Expected output patterns:
# ELF 32-bit LSB executable, ARM, EABI5 version 1 (SYSV), dynamically linked, interpreter /lib/ld-linux-armhf.so.3
# ELF 64-bit LSB pie executable, ARM aarch64, version 1 (SYSV), dynamically linked, interpreter /lib/ld-linux-aarch64.so.1

Extract:

  • Architecture (ARM, ARM64, x86_64, MIPS)
  • Bit width (32/64)
  • Endianness (LSB/MSB)
  • Link type (static/dynamic)
  • Interpreter path (libc indicator)

Step 2: Structured Metadata (rabin2)

# All metadata as JSON
rabin2 -q -j -I binary | jq .

# Key fields:
# .arch     - "arm", "x86", "mips"
# .bits     - 32 or 64
# .endian   - "little" or "big"
# .os       - "linux", "none"
# .machine  - "ARM", "AARCH64"
# .stripped - true/false
# .static   - true/false

Step 3: ABI Detection

# Interpreter detection
readelf -p .interp binary 2>/dev/null

# Or via rabin2
rabin2 -I binary | grep interp

# ARM-specific: float ABI
readelf -A binary | grep "Tag_ABI_VFP_args"
# hard-float: "VFP registers"
# soft-float: missing or "compatible"

Interpreter → Libc mapping:

InterpreterLibcNotes
/lib/ld-linux-armhf.so.3glibcARM hard-float
/lib/ld-linux.so.3glibcARM soft-float
/lib/ld-musl-arm.so.1muslARM 32-bit
/lib/ld-musl-aarch64.so.1muslARM 64-bit
/lib/ld-uClibc.so.0uClibcEmbedded
/lib64/ld-linux-x86-64.so.2glibcx86_64

Step 4: Dependencies

# Library dependencies
rabin2 -q -j -l binary | jq '.libs[]'

# Common patterns:
# libcurl.so.* → HTTP client
# libssl.so.* → TLS/crypto
# libpthread.so.* → Threading
# libz.so.* → Compression
# libsqlite3.so.* → Local database

Step 5: Entry Points & Exports

# Entry points
rabin2 -q -j -e binary | jq .

# Exports (for shared libraries)
rabin2 -q -j -E binary | jq '.exports[] | {name, vaddr}'

Step 6: Quick String Scan

# All strings with metadata
rabin2 -q -j -zz binary | jq '.strings | length'  # Count first

# Filter interesting strings (URLs, paths, errors)
rabin2 -q -j -zz binary | jq '
  .strings[] |
  select(.length > 8) |
  select(.string | test("http|ftp|/etc|/var|error|fail|pass|key|token"; "i"))
'

Step 7: Import Analysis

# All imports
rabin2 -q -j -i binary | jq '.imports[] | {name, lib}'

# Group by capability
rabin2 -q -j -i binary | jq '
  .imports | group_by(.lib) |
  map({lib: .[0].lib, functions: [.[].name]})
'

Capability Mapping

Import PatternCapability
socket, connect, sendNetwork client
bind, listen, acceptNetwork server
open, read, writeFile I/O
fork, exec*, systemProcess spawning
pthread_*Multi-threading
SSL_*, EVP_*Cryptography
dlopen, dlsymDynamic loading
mmap, mprotectMemory manipulation

Output Format

After triage, record structured facts:

{
  "artifact": {
    "path": "/path/to/binary",
    "sha256": "abc123...",
    "size_bytes": 245760
  },
  "identification": {
    "arch": "arm",
    "bits": 32,
    "endian": "little",
    "os": "linux",
    "stripped": true,
    "static": false
  },
  "abi": {
    "interpreter": "/lib/ld-musl-arm.so.1",
    "libc": "musl",
    "float_abi": "hard"
  },
  "dependencies": [
    "libcurl.so.4",
    "libssl.so.1.1",
    "libz.so.1"
  ],
  "capabilities_inferred": [
    "network_client",
    "tls_encryption",
    "compression"
  ],
  "strings_of_interest": [
    {"value": "https://api.vendor.com/telemetry", "type": "url"},
    {"value": "/etc/config.json", "type": "path"}
  ],
  "complexity_estimate": {
    "functions": "unknown (stripped)",
    "strings": 847,
    "imports": 156
  }
}

Knowledge Journaling

After triage completes, record findings for episodic memory:

[BINARY-RE:triage] {filename} (sha256: {hash})

Identification:
  Architecture: {arch} {bits}-bit {endian}
  Libc: {glibc|musl|uclibc} ({interpreter_path})
  Stripped: {yes|no}
  Size: {bytes}

FACT: Links against {library} (source: rabin2 -l)
FACT: Contains {N} strings of interest (source: rabin2 -zz)
FACT: Imports {function} from {library} (source: rabin2 -i)

Capabilities inferred:
  - {capability_1} (evidence: {import/string})
  - {capability_2} (evidence: {import/string})

HYPOTHESIS: {what binary likely does} (confidence: {0.0-1.0})

QUESTION: {open unknown that needs investigation}

Next phase: {static-analysis|dynamic-analysis}
Sysroot needed: {path or "extract from device"}

Example Journal Entry

[BINARY-RE:triage] thermostat_daemon (sha256: a1b2c3d4...)

Identification:
  Architecture: ARM 32-bit LE
  Libc: musl (/lib/ld-musl-arm.so.1)
  Stripped: yes
  Size: 153,600 bytes

FACT: Links against libcurl.so.4 (source: rabin2 -l)
FACT: Links against libssl.so.1.1 (source: rabin2 -l)
FACT: Contains string "api.thermco.com" (source: rabin2 -zz)
FACT: Imports curl_easy_perform (source: rabin2 -i)

Capabilities inferred:
  - HTTP client (evidence: libcurl import)
  - TLS encryption (evidence: libssl import)
  - Network communication (evidence: URL string)

HYPOTHESIS: Telemetry client that reports to api.thermco.com (confidence: 0.6)

QUESTION: What data does it collect and transmit?

Next phase: static-analysis
Sysroot needed: musl ARM (extract from device or Alpine)

Decision Points

After triage, determine:

  1. Sysroot selection - Based on arch + libc
  2. Analysis tool chain - r2 vs Ghidra vs both
  3. Dynamic analysis feasibility - QEMU viability based on arch
  4. Initial hypotheses - What does this binary likely do?

Next Steps

→ Proceed to binary-re-static-analysis for function enumeration → Or binary-re-dynamic-analysis if behavior observation is priority

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

Stop and check this skill before finishing any reply to a question about how to use Claude or a Claude product — it recommends matching courses, tutorials, and use cases from Claude Academy (academy.claude.com), Anthropic's learning hub. Trigger on: "how do I", "how can I", "getting started with", "what can Claude do", "teach me", "learn to use"; questions about artifacts, projects, skills, plugins, connectors, MCP; requests about rolling Claude out to a team, class, or organization; and any ask for training materials, onboarding content, or learning resources. Use it when the user is learning how to use a feature or product — not when they are mid-task and just want the task done. This skill composes with other skills: after consulting product documentation to answer how a Claude feature works, also check here for a matching course or tutorial — a docs-grounded answer and an Academy recommendation belong together. Only recommend on a strong match; never invent Academy content.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

aiskillstore/marketplace4402026년 10월 21일 업데이트

Trigger for: explaining current FAR, DFARS, or agency-supplement text; determining documented acquisition-policy status for an agency and FAR part; comparing codified text, RFO model text, and agency deviations; tracing acquisition rulemaking; finding procurement comment periods; analyzing public comments; refreshing prior policy analysis; or producing an Acquisition Policy Impact Brief. Use published federal sources and supplied policy documents without making legal or procurement-specific applicability determinations. Do not use for clause selection, market research execution, opportunities, pricing, grants, or cooperative agreements.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

aiskillstore/marketplace4402026년 10월 21일 업데이트

Systematic framework for extracting actionable items from documents and organizing them into prioritized, trackable checklists. Use when converting reports, meeting notes, audits, or any document with embedded action items into structured TODO lists.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

aiskillstore/marketplace4402026년 10월 21일 업데이트

Browser automation for AI agents via inference.sh. Navigate web pages, interact with elements using @e refs, take screenshots, record video. Capabilities: web scraping, form filling, clicking, typing, drag-drop, file upload, JavaScript execution. Use for: web automation, data extraction, testing, agent browsing, research. Triggers: browser, web automation, scrape, navigate, click, fill form, screenshot, browse web, playwright, headless browser, web agent, surf internet, record video

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

aiskillstore/marketplace4402026년 10월 21일 업데이트

This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

aiskillstore/marketplace4402026년 10월 21일 업데이트

Run AI apps via inference.sh CLI - image generation, video creation, LLMs, search, 3D, Twitter automation. Models: FLUX, Veo, Gemini, Grok, Claude, Seedance, OmniHuman, Tavily, Exa, OpenRouter, and many more. Use when running AI apps, generating images/videos, calling LLMs, web search, or automating Twitter. Triggers: inference.sh, infsh, ai model, run ai, serverless ai, ai api, flux, veo, claude api, image generation, video generation, openrouter, tavily, exa search, twitter api, grok

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

aiskillstore/marketplace4402026년 10월 21일 업데이트

aiskillstore의 스킬 모두 보기

이 스킬의 문제 신고