Turns reverse-engineering findings into durable YARA detections: selecting stable code constructs and constants over volatile strings, extracting opcode/byte patterns with wildcards, and validating rules for low false positives. Activates for requests to write a YARA rule from reversed code, create a detection signature, or convert RE findings into hunting rules.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
Do not use volatile artifacts (file paths, mutex names that change per build, packer stubs shared across unrelated families) as your primary anchor — they cause drift and false hits.
yara engine (and ideally yara-python) for testing.Prefer, in order: a unique algorithm's opcode sequence (decryptor, hashing loop), embedded magic constants (API hashes, XOR keys, S-box), then distinctive strings only if intrinsic.
Pull the relevant opcodes and wildcard volatile operands (addresses, immediates) so the rule survives relocation/recompilation:
$dec = { 8A 04 ?? 34 ?? 88 04 ?? 41 3B ?? 7? ?? } ; xor-decrypt loop, regs/disp wildcarded
Combine 2–3 independent anchors with a condition requiring enough of them, plus a cheap
prefilter (file size, PE magic) to keep scanning fast:
python scripts/analyst.py scaffold --name family_xyz --hash 0xABCDEF12
Run the rule across true positives and the clean control set; require all TPs match and zero FPs on the control.
yara -r rules/family_xyz.yar ./corpus
Adjust thresholds, add meta (author, date, reference, hash), and record which construct each
string anchors so future analysts can maintain it.
meta documents source samples and the reasoning for each pattern.references/api-reference.md for the rule scaffolder.还没有评价。欢迎分享你的使用感受。
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Reverses Android malware: unpacking APKs, decompiling DEX bytecode to readable Java, auditing the manifest for abused permissions and components, and locating dynamically loaded or native payloads. Activates for requests to analyze an APK, decompile DEX, or investigate a suspicious Android app.
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Analyzes API call traces from a sandbox or API monitor (JSON) to group calls by category, reconstruct high-level behaviors (process injection, file drops, network, crypto), and flag suspicious call sequences. Activates for requests to analyze an API trace, interpret sandbox API logs, or identify behavior from Win32/Native API calls.
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Analyzes Windows Authenticode signatures on PE files: checking for a signature, reading the signer certificate chain, detecting revoked/expired/stolen certs, and recognizing signature-stripping and catalog-signing abuse. Activates for requests to analyze a code signature, verify Authenticode, or assess signer trust on a PE.
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Analyzes banking trojan webinject configurations to extract targeted institutions, injected JavaScript/HTML, and data-theft hooks, mapping the fraud workflow. Activates for requests to analyze banking trojan webinjects, parse a webinject config, or map targeted banks and credential-theft injections.
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Analyzes Python-based malware packaged as PyInstaller/py2exe executables by detecting the packer, locating the embedded archive, and identifying bundled .pyc modules for extraction and decompilation. Activates for requests to analyze compiled Python malware, unpack a PyInstaller binary, or extract pyc modules from a frozen Python executable.
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Analyzes cryptojacking/coinminer malware by extracting mining pool endpoints (stratum), wallet addresses, algorithm and miner identifiers (XMRig and forks), and persistence or resource-control settings from static strings and config. Activates for requests to analyze a cryptominer, extract mining pool and wallet IOCs, or identify coinminer configuration.
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