DslsDZC
Community@dslsdzc · 中国
Building systems from scratch
Agent Skills by DslsDZC
Showing 120 vetted skills indexed across 1 GitHub repositories.
dslsdzcre-ransomware
Analyzes ransomware samples to identify encryption schemes, extract keys, and plan decryption recovery.
dslsdzcre-arm
Reverse engineer ARM Cortex-M/A firmware including Thumb disassembly, AAPCS conventions, and MMIO register analysis.
dslsdzcre-blockchain
Decompile EVM smart contract bytecode and analyze vulnerabilities using cast, panoramix, and web3.py.
dslsdzcre-java
Decompile and analyze Java bytecode from jar, war, and class files using CFR, JD-GUI, and javap.
dslsdzcre-feedback
Collects, distills, and archives reverse engineering lessons into skill experience files or GitHub issues.
dslsdzcre-address-space
Converts addresses across PIE, ASLR, RVA, VA, and firmware loader offsets for reverse engineering.
dslsdzcre-protocol
Orchestrates network protocol reverse engineering from packet capture through decryption to state machine reconstruction.
dslsdzcre-attribution
Attributes cyber threat activity using diamond model analysis, infrastructure graphing, and confidence grading.
dslsdzcre-format-elf
Parse ELF headers, GOT/PLT, init_array, and dynamic symbols for Linux binary analysis.
dslsdzcre-ios-jb
Analyze iOS jailbreak detection, reverse tweaks, and debug apps on jailbroken devices.
dslsdzcre-dotnet
Decompile and deobfuscate .NET assemblies using dnSpy, ILSpy, and de4dot.
dslsdzcre-memdump
Dump process memory with gcore and extract keys, DEX files, and decrypted data.
dslsdzcre-format-macho
Parse Mach-O binaries including mach_header, load commands, segments, and dyld information.
dslsdzcre-hardware-io
Extract firmware and debug embedded boards via JTAG, UART, and SPI flash interfaces.
dslsdzcre-malware
Orchestrates malware analysis workflows from sandboxing through behavior analysis to IOC reporting.
dslsdzcre-packer-id
Identify packers and obfuscators on PE binaries using signatures, section names, entry point, and entropy.
dslsdzcre-imports
Analyze import and export tables to fingerprint linked libraries and flag suspicious APIs.
dslsdzcre-swift
Reverse engineer Swift binaries by decoding mangled symbols, witness tables, closures, and reflection metadata.
dslsdzcre-game
Reverse engineer Unity, Unreal, Lua bytecode, and GPU shaders in game binaries.
dslsdzcre-lldb
Debug macOS and iOS binaries with lldb using attach, breakpoints, and memory inspection.
dslsdzcre-mem-forensics
Analyze memory dumps with Volatility 3 to extract processes, network connections, injected code, and credential artifacts.
dslsdzcre-fw-rootfs
Analyze extracted firmware root filesystems to locate startup scripts, credentials, and cross-architecture binaries.
dslsdzcre-sample-acquire
Acquire fileless and memory-resident malware samples by locating anomalous executable memory regions at runtime.
dslsdzcre-crash-triage
Reproduce, minimize, and root-cause program crashes using ASAN, gdb, rr, and afl-tmin.
Frequently Asked Questions About DslsDZC
FAQPage SchemaWhat tasks can I accomplish using DslsDZC's reverse engineering skills?▼
You can perform binary decompilation with Ghidra/IDA/radare2, malware behavior analysis and IOC extraction, firmware unpacking and emulation, mobile APK/iOS analysis with Frida, protocol reverse engineering, memory forensics with Volatility, fuzzing with AFL++, and exploit development including ROP chains and heap exploitation.
Who is the target audience for these reverse engineering skills?▼
The skills target security researchers, malware analysts, firmware and embedded engineers, mobile security testers, CTF players, and vulnerability researchers. Gateway skills like re-analyze route tasks to specialized sub-skills covering Windows, Linux, macOS, Android, iOS, and exotic kernels like seL4 and Fuchsia.
How do the gateway and atomic skills work together in practice?▼
The re-analyze entry skill probes the environment, asks analysis preferences, and identifies the task type. It then orchestrates gateway skills (re-binary-core, re-malware, re-firmware, re-mobile, re-vuln) which sequence atomic skills such as format parsers, debuggers, unpackers, and crypto identification into a complete analysis pipeline.
What platforms, architectures, and file formats are supported?▼
Supported formats include PE, ELF, Mach-O, DEX, WASM, and CAP files. Architectures span x86/x64, ARM Cortex-M/A, MIPS, and RISC-V. Coverage extends to UEFI/BIOS, RTOS variants like FreeRTOS and VxWorks, hypervisors, TEE/TrustZone, automotive CAN/AUTOSAR, game consoles, and AI model files like ONNX and Safetensors.
Are there safety or authorization requirements for sensitive skills?▼
Yes. The re-ai-attack skill for model security evaluation declares an explicit guard requiring authorization and forbidding unauthorized API testing, access control bypass, and third-party model theft. Malware analysis skills mandate sandbox isolation via re-sandbox before any dynamic execution of samples.