[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71F9ASBX1NF2PXFWMEAB83P":3,"skill-same:01M71F9ASBX1NF2PXFWMEAB83P":87},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":18,"publishedAt":39,"linkOnly":40,"markdownContent":41,"markdownBody":42,"frontMatter":43,"refName":60,"commitSha":61,"skillDirectory":62,"forksCount":14,"repositoryHtmlUrl":63,"repositoryHomepageUrl":6,"ownerHtmlUrl":64,"ownerBlogUrl":6,"ownerDescription":65,"updatedAt":66,"install":67,"resources":80},"01M71F9ASBX1NF2PXFWMEAB83P","reversing-rust-analyze",null,"Reverse engineer Rust-compiled malware using IDA Pro and Ghidra with techniques for handling non-null-terminated strings, crate dependency extraction, and Rust-specific control flow analysis.","DCx7C5\u002Fai-marketplace","DCx7C5","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F42419559?v=4","01M71C01G2AZV3NTNGWAWSHJPP","DC","01M71C01GQW6G50S2BYMS7PP3E",0,"MIT","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fmalware\u002Freversing\u002Frust\u002Fanalyze\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"reversing rust analyze","analyze","rust","de","control","id","with","analysis","Bash","cybersecurity","techniques","engineer","reverse engineer","strings","cm","for","reverse-engineering","reverse","binary-analysis","ghidra","2026-11-10 10:12:30",false,"---\nname: reversing-rust-analyze\ndescription: Reverse engineer Rust-compiled malware using IDA Pro and Ghidra with techniques for handling non-null-terminated strings, crate dependency extraction, and Rust-specific control flow analysis.\ndomain: cybersecurity\nsubdomain: malware-analysis\ntags:\n- rust\n- reverse-engineering\n- malware-analysis\n- ghidra\n- ida-pro\n- binary-analysis\n- rust-malware\nnist_csf:\n- DE.AE-02\n- RS.AN-03\n- ID.RA-01\n- DE.CM-01\nmodel: sonnet\nmaxTurns: 20\ntools: [Read, Bash, Glob, Grep]\ncapec: []\n---\n\n# Reverse Engineering Rust Malware\n\n## Overview\n\nRust has become increasingly popular for malware development due to its cross-compilation, memory safety guarantees, and the complexity it introduces for reverse engineers. Rust binaries contain the entire standard library statically linked, producing large binaries with extensive boilerplate code. Key challenges include non-null-terminated strings (Rust uses fat pointers with pointer+length), monomorphization generating duplicated generic code, complex error handling (Result\u002FOption unwrap chains), and unfamiliar calling conventions. Decompiling Rust to C produces unhelpful output compared to C\u002FC++ binaries. Tools like Ghidra scripts for crate extraction, and training focused on Rust-specific patterns (2024-2025) help address these challenges. Notable Rust malware includes BlackCat\u002FALPHV ransomware, Hive ransomware variants, and Buer Loader.\n\n\n## When to Use\n\n- When performing authorized security testing that involves reverse engineering rust malware\n- When analyzing malware samples or attack artifacts in a controlled environment\n- When conducting red team exercises or penetration testing engagements\n- When building detection capabilities based on offensive technique understanding\n\n## Prerequisites\n\n- IDA Pro 8.0+ or Ghidra 11.0+\n- Rust toolchain for reference compilation\n- Python 3.9+ for helper scripts\n- Understanding of Rust memory model (ownership, borrowing)\n- Familiarity with Rust string types (String, &str, CString)\n\n## Workflow\n\n### Step 1: Identify and Parse Rust Binary Metadata\n\n```python\n#!\u002Fusr\u002Fbin\u002Fenv python3\n\"\"\"Analyze Rust malware binary metadata and extract crate dependencies.\"\"\"\nimport re\nimport sys\nimport json\n\n\ndef identify_rust_binary(data):\n    \"\"\"Check if binary is Rust-compiled and extract version info.\"\"\"\n    indicators = {\n        \"rust_panic_strings\": bool(re.search(rb'panicked at', data)),\n        \"rust_unwrap\": bool(re.search(rb'called.*unwrap.*on.*None', data)),\n        \"core_panic\": bool(re.search(rb'core::panicking', data)),\n        \"std_rt\": bool(re.search(rb'std::rt::lang_start', data)),\n        \"cargo_path\": bool(re.search(rb'\\.cargo[\u002F\\\\]registry', data)),\n        \"rustc_version\": None,\n    }\n\n    version = re.search(rb'rustc\\s+(\\d+\\.\\d+\\.\\d+)', data)\n    if version:\n        indicators[\"rustc_version\"] = version.group(1).decode()\n\n    is_rust = sum(1 for v in indicators.values() if v) >= 2\n    return is_rust, indicators\n\n\ndef extract_crates(data):\n    \"\"\"Extract Rust crate (dependency) names from binary strings.\"\"\"\n    crate_pattern = re.compile(\n        rb'(?:crates\\.io-[a-f0-9]+\u002F|\\.cargo\u002Fregistry\u002Fsrc\u002F[^\u002F]+\u002F)'\n        rb'([\\w-]+)-(\\d+\\.\\d+\\.\\d+)'\n    )\n    crates = {}\n    for match in crate_pattern.finditer(data):\n        name = match.group(1).decode()\n        version = match.group(2).decode()\n        crates[name] = version\n\n    # Also check for common malware-relevant crates\n    suspicious_crates = {\n        \"reqwest\": \"HTTP client\",\n        \"hyper\": \"HTTP library\",\n        \"tokio\": \"Async runtime\",\n        \"aes\": \"AES encryption\",\n        \"chacha20\": \"ChaCha20 encryption\",\n        \"rsa\": \"RSA encryption\",\n        \"ring\": \"Crypto library\",\n        \"base64\": \"Base64 encoding\",\n        \"winapi\": \"Windows API bindings\",\n        \"winreg\": \"Registry access\",\n        \"sysinfo\": \"System information\",\n        \"screenshots\": \"Screen capture\",\n        \"clipboard\": \"Clipboard access\",\n        \"keylogger\": \"Key logging\",\n    }\n\n    capabilities = []\n    for crate_name, description in suspicious_crates.items():\n        if crate_name in crates:\n            capabilities.append({\n                \"crate\": crate_name,\n                \"version\": crates[crate_name],\n                \"capability\": description,\n            })\n\n    return crates, capabilities\n\n\ndef extract_rust_strings(data):\n    \"\"\"Extract strings handling Rust's non-null-terminated format.\"\"\"\n    # Rust strings are stored as pointer+length, but string literals\n    # are often in .rodata as contiguous sequences\n    strings = []\n    ascii_pattern = re.compile(rb'[\\x20-\\x7e]{8,500}')\n    for match in ascii_pattern.finditer(data):\n        s = match.group().decode('ascii')\n        # Filter for malware-relevant strings\n        keywords = ['http', 'socket', 'encrypt', 'decrypt', 'shell',\n                    'exec', 'cmd', 'upload', 'download', 'persist',\n                    'registry', 'mutex', 'pipe', 'inject']\n        if any(kw in s.lower() for kw in keywords):\n            strings.append(s)\n\n    return strings\n\n\nif __name__ == \"__main__\":\n    if len(sys.argv) \u003C 2:\n        print(f\"Usage: {sys.argv[0]} \u003Crust_binary>\")\n        sys.exit(1)\n\n    with open(sys.argv[1], 'rb') as f:\n        data = f.read()\n\n    is_rust, indicators = identify_rust_binary(data)\n    print(f\"[{'+'if is_rust else '-'}] Rust binary: {is_rust}\")\n    print(json.dumps(indicators, indent=2, default=str))\n\n    crates, capabilities = extract_crates(data)\n    print(f\"\\n[+] Crates ({len(crates)}):\")\n    for name, ver in sorted(crates.items()):\n        print(f\"  {name} v{ver}\")\n\n    if capabilities:\n        print(f\"\\n[!] Suspicious capabilities:\")\n        for cap in capabilities:\n            print(f\"  {cap['crate']} -> {cap['capability']}\")\n\n    strings = extract_rust_strings(data)\n    if strings:\n        print(f\"\\n[+] Suspicious strings ({len(strings)}):\")\n        for s in strings[:20]:\n            print(f\"  {s}\")\n```\n\n## Validation Criteria\n\n- Binary correctly identified as Rust-compiled with version info\n- Crate dependencies extracted revealing malware capabilities\n- Rust-specific string extraction handles fat pointer format\n- Main entry point and core logic functions identified\n- Encryption, networking, and persistence code located\n\n## References\n\n- [Binary Defense - Extracting Secrets from Rust Malware](https:\u002F\u002Fbinarydefense.com\u002Fresources\u002Fblog\u002Fdigging-through-rust-to-find-gold-extracting-secrets-from-rust-malware)\n- [Ghidra Extension for Rust Analysis](https:\u002F\u002Fcir.nii.ac.jp\u002Fcrid\u002F1050302237609671296)\n- [Fuzzing Labs - Reversing Modern Binaries](https:\u002F\u002Ffuzzinglabs.com\u002Freversing-modern-binaries\u002F)\n- [Bishop Fox - Rust for Malware Development](https:\u002F\u002Fbishopfox.com\u002Fblog\u002Frust-for-malware-development)\n","# Reverse Engineering Rust Malware\n\n## Overview\n\nRust has become increasingly popular for malware development due to its cross-compilation, memory safety guarantees, and the complexity it introduces for reverse engineers. Rust binaries contain the entire standard library statically linked, producing large binaries with extensive boilerplate code. Key challenges include non-null-terminated strings (Rust uses fat pointers with pointer+length), monomorphization generating duplicated generic code, complex error handling (Result\u002FOption unwrap chains), and unfamiliar calling conventions. Decompiling Rust to C produces unhelpful output compared to C\u002FC++ binaries. Tools like Ghidra scripts for crate extraction, and training focused on Rust-specific patterns (2024-2025) help address these challenges. Notable Rust malware includes BlackCat\u002FALPHV ransomware, Hive ransomware variants, and Buer Loader.\n\n\n## When to Use\n\n- When performing authorized security testing that involves reverse engineering rust malware\n- When analyzing malware samples or attack artifacts in a controlled environment\n- When conducting red team exercises or penetration testing engagements\n- When building detection capabilities based on offensive technique understanding\n\n## Prerequisites\n\n- IDA Pro 8.0+ or Ghidra 11.0+\n- Rust toolchain for reference compilation\n- Python 3.9+ for helper scripts\n- Understanding of Rust memory model (ownership, borrowing)\n- Familiarity with Rust string types (String, &str, CString)\n\n## Workflow\n\n### Step 1: Identify and Parse Rust Binary Metadata\n\n```python\n#!\u002Fusr\u002Fbin\u002Fenv python3\n\"\"\"Analyze Rust malware binary metadata and extract crate dependencies.\"\"\"\nimport re\nimport sys\nimport json\n\n\ndef identify_rust_binary(data):\n    \"\"\"Check if binary is Rust-compiled and extract version info.\"\"\"\n    indicators = {\n        \"rust_panic_strings\": bool(re.search(rb'panicked at', data)),\n        \"rust_unwrap\": bool(re.search(rb'called.*unwrap.*on.*None', data)),\n        \"core_panic\": bool(re.search(rb'core::panicking', data)),\n        \"std_rt\": bool(re.search(rb'std::rt::lang_start', data)),\n        \"cargo_path\": bool(re.search(rb'\\.cargo[\u002F\\\\]registry', data)),\n        \"rustc_version\": None,\n    }\n\n    version = re.search(rb'rustc\\s+(\\d+\\.\\d+\\.\\d+)', data)\n    if version:\n        indicators[\"rustc_version\"] = version.group(1).decode()\n\n    is_rust = sum(1 for v in indicators.values() if v) >= 2\n    return is_rust, indicators\n\n\ndef extract_crates(data):\n    \"\"\"Extract Rust crate (dependency) names from binary strings.\"\"\"\n    crate_pattern = re.compile(\n        rb'(?:crates\\.io-[a-f0-9]+\u002F|\\.cargo\u002Fregistry\u002Fsrc\u002F[^\u002F]+\u002F)'\n        rb'([\\w-]+)-(\\d+\\.\\d+\\.\\d+)'\n    )\n    crates = {}\n    for match in crate_pattern.finditer(data):\n        name = match.group(1).decode()\n        version = match.group(2).decode()\n        crates[name] = version\n\n    # Also check for common malware-relevant crates\n    suspicious_crates = {\n        \"reqwest\": \"HTTP client\",\n        \"hyper\": \"HTTP library\",\n        \"tokio\": \"Async runtime\",\n        \"aes\": \"AES encryption\",\n        \"chacha20\": \"ChaCha20 encryption\",\n        \"rsa\": \"RSA encryption\",\n        \"ring\": \"Crypto library\",\n        \"base64\": \"Base64 encoding\",\n        \"winapi\": \"Windows API bindings\",\n        \"winreg\": \"Registry access\",\n        \"sysinfo\": \"System information\",\n        \"screenshots\": \"Screen capture\",\n        \"clipboard\": \"Clipboard access\",\n        \"keylogger\": \"Key logging\",\n    }\n\n    capabilities = []\n    for crate_name, description in suspicious_crates.items():\n        if crate_name in crates:\n            capabilities.append({\n                \"crate\": crate_name,\n                \"version\": crates[crate_name],\n                \"capability\": description,\n            })\n\n    return crates, capabilities\n\n\ndef extract_rust_strings(data):\n    \"\"\"Extract strings handling Rust's non-null-terminated format.\"\"\"\n    # Rust strings are stored as pointer+length, but string literals\n    # are often in .rodata as contiguous sequences\n    strings = []\n    ascii_pattern = re.compile(rb'[\\x20-\\x7e]{8,500}')\n    for match in ascii_pattern.finditer(data):\n        s = match.group().decode('ascii')\n        # Filter for malware-relevant strings\n        keywords = ['http', 'socket', 'encrypt', 'decrypt', 'shell',\n                    'exec', 'cmd', 'upload', 'download', 'persist',\n                    'registry', 'mutex', 'pipe', 'inject']\n        if any(kw in s.lower() for kw in keywords):\n            strings.append(s)\n\n    return strings\n\n\nif __name__ == \"__main__\":\n    if len(sys.argv) \u003C 2:\n        print(f\"Usage: {sys.argv[0]} \u003Crust_binary>\")\n        sys.exit(1)\n\n    with open(sys.argv[1], 'rb') as f:\n        data = f.read()\n\n    is_rust, indicators = identify_rust_binary(data)\n    print(f\"[{'+'if is_rust else '-'}] Rust binary: {is_rust}\")\n    print(json.dumps(indicators, indent=2, default=str))\n\n    crates, capabilities = extract_crates(data)\n    print(f\"\\n[+] Crates ({len(crates)}):\")\n    for name, ver in sorted(crates.items()):\n        print(f\"  {name} v{ver}\")\n\n    if capabilities:\n        print(f\"\\n[!] Suspicious capabilities:\")\n        for cap in capabilities:\n            print(f\"  {cap['crate']} -> {cap['capability']}\")\n\n    strings = extract_rust_strings(data)\n    if strings:\n        print(f\"\\n[+] Suspicious strings ({len(strings)}):\")\n        for s in strings[:20]:\n            print(f\"  {s}\")\n```\n\n## Validation Criteria\n\n- Binary correctly identified as Rust-compiled with version info\n- Crate dependencies extracted revealing malware capabilities\n- Rust-specific string extraction handles fat pointer format\n- Main entry point and core logic functions identified\n- Encryption, networking, and persistence code located\n\n## References\n\n- [Binary Defense - Extracting Secrets from Rust Malware](https:\u002F\u002Fbinarydefense.com\u002Fresources\u002Fblog\u002Fdigging-through-rust-to-find-gold-extracting-secrets-from-rust-malware)\n- [Ghidra Extension for Rust Analysis](https:\u002F\u002Fcir.nii.ac.jp\u002Fcrid\u002F1050302237609671296)\n- [Fuzzing Labs - Reversing Modern Binaries](https:\u002F\u002Ffuzzinglabs.com\u002Freversing-modern-binaries\u002F)\n- [Bishop Fox - Rust for Malware Development](https:\u002F\u002Fbishopfox.com\u002Fblog\u002Frust-for-malware-development)\n",{"name":5,"tags":44,"capec":48,"model":49,"tools":50,"domain":28,"maxTurns":54,"nist_csf":55,"subdomain":45,"description":7},[21,35,45,38,46,37,47],"malware-analysis","ida-pro","rust-malware",[],"sonnet",[51,27,52,53],"Read","Glob","Grep",20,[56,57,58,59],"DE.AE-02","RS.AN-03","ID.RA-01","DE.CM-01","main","a91f1293287ffa9f4f1b8f486cd6e835a1568c84","skills\u002Fmalware\u002Freversing\u002Frust\u002Fanalyze","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace","https:\u002F\u002Fgithub.com\u002FDCx7C5","#Python","2026-09-01 11:21:00",{"source":8,"skillName":5,"commands":68,"prompt":78,"zipAvailable":79},[69,72,75],{"tool":70,"command":71},"npx","npx skills add DCx7C5\u002Fai-marketplace --skill reversing-rust-analyze",{"tool":73,"command":74},"bunx","bunx skills add DCx7C5\u002Fai-marketplace --skill reversing-rust-analyze",{"tool":76,"command":77},"pnpm","pnpm dlx skills add 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CreateRemoteThread, QueueUserAPC, NtCreateThreadEx, and thread hijacking via process memory analysis.","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fwindows\u002Fprocesses\u002Fthread\u002Finjection\u002Fdetect\u002FSKILL.md",[],[180,181,96,182,161,163,183,33,184,29,28,110,26,185,186,187,188,172,22,100],"thread","processes thread injection detect","injection","memory","process-injection","api","apc-injection","thread-injection","nt-api",{"skillNo":190,"name":191,"nameZh":6,"description":192,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":193,"categories":194,"keywords":195,"publishedAt":39},"01M71HA7H311V5G14WMX58HQSS","processes-hollow-technique-detect","Detect process hollowing (RunPE) by identifying processes with mismatched image paths between PEB and VAD tree, or unmapped PE headers in memory.","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fwindows\u002Fprocesses\u002Fhollow\u002Ftechnique\u002Fdetect\u002FSKILL.md",[],[196,96,161,197,183,33,198,199,28,110,200,201,202,203,204,25,22,100,205,206],"processes hollow technique detect","tree","memory-forensics","process-hollow","peb","runpe","image","pe-header","in memory","mismatched","headers"]