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Find your next superpower If you are an agent, refer to our llms.txt for full access.Reverses .NET/managed malware: decompiling MSIL back to C, defeating common .NET protectors and string encryptors, and tracing reflection-based loaders to recover the real payload. Activates for requests to analyze a .NET sample, decompile MSIL, or unpack a managed loader.
Statically analyzes Linux ELF malware: ELF header and sections, dynamic symbols and imports, segment permissions, embedded strings, and packing indicators to infer capability without execution. Activates for requests to analyze an ELF binary, Linux malware, or shared object.
Analyzes legacy Excel 4.0 (XLM) macro malware by parsing extracted macro-sheet formulas for auto-executing names, obfuscation (FORMULA.FILL, CHAR concatenation), and download or execution primitives (EXEC, CALL, REGISTER). Activates for requests to analyze XLM macros, examine Excel 4.0 macro sheets, or deobfuscate legacy spreadsheet macros.
Analyzes Go-compiled malware by recovering function names from the pclntab, detecting the Go build/version string, and listing embedded package paths to overcome stripped symbols. Activates for requests to analyze Go malware, recover Go function names, or identify a Golang binary build.
Analyzes infostealer samples by mapping the browser, credential store, wallet, and application paths they target, and the exfiltration channel used, from static strings and behavior. Activates for requests to analyze an infostealer, identify targeted credential stores, or map stealer collection and exfiltration behavior.
Analyzes Java/JAR malware (such as Adwind/jRAT-class cross-platform RATs) by inventorying the archive, reading the manifest entry point, detecting obfuscators and string encryption, and flagging suspicious runtime, reflection, and networking class usage. Activates for requests to analyze a malicious JAR, inspect Java malware, or identify a Java RAT.
Analyzes loader and dropper samples by identifying staging behavior — embedded or downloaded next-stage payloads, decode/decrypt routines, and the execution mechanism used to run the next stage. Activates for requests to analyze a loader or dropper, find a staged payload, or map multi-stage delivery behavior.
Statically analyzes macOS Mach-O malware: parsing the header and load commands, handling fat/universal binaries, reading linked dylibs and entitlements, and checking code signatures to infer capability and trust. Activates for requests to analyze a Mach-O binary, inspect macOS malware, or parse load commands and entitlements.
Analyzes malicious ISO, IMG, VHD, and similar container files used to smuggle payloads past email and mark-of-the-web defenses by enumerating contents and flagging hidden executables, LNKs, and scripts. Activates for requests to analyze a malicious ISO/IMG, inspect a container delivery file, or find payloads hidden inside a disk image attachment.
Analyzes weaponized Windows shortcut (.lnk) files: parsing the shell link structure for the target command, arguments, icon, and working directory, and recovering hidden PowerShell/cmd payloads and embedded content used in phishing. Activates for requests to analyze a malicious LNK, parse a shortcut file, or extract a command from a .lnk.
Analyzes malicious Office documents by extracting and reviewing VBA macros and OLE/OOXML structure: auto-exec triggers, obfuscation, dropped payloads, and shell/PowerShell invocation. Activates for requests to analyze a malicious Word/Excel document, VBA macro, or maldoc.
Analyzes two modern delivery techniques: malicious OneNote (.one) attachments with embedded payloads behind fake buttons, and HTML smuggling pages that reconstruct payloads in the browser from embedded blobs. Activates for requests to analyze a malicious OneNote file, detect HTML smuggling, or extract a smuggled/embedded payload.
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Copy the install command from a skill page and run it in your project.
npx skillycli add owner/repo --skill name