Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Asaiuta/reverse-workbench-skill --skill dsl-vm-reversegit clone --depth 1 https://github.com/Asaiuta/reverse-workbench-skillWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/asaiuta/reverse-workbench-skill/dsl-vm-reverse)<a href="https://agentmods.dev/skills/asaiuta/reverse-workbench-skill/dsl-vm-reverse"><img src="https://agentmods.dev/badge/skills/asaiuta/reverse-workbench-skill/dsl-vm-reverse/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/asaiuta/reverse-workbench-skill/dsl-vm-reverse"><img src="https://agentmods.dev/badge/skills/asaiuta/reverse-workbench-skill/dsl-vm-reverse.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.03756 |
| Opus 5 | $0.00000 | $0.01878 |
| Sonnet 5 | $0.00000 | $0.00751 |
| Haiku 4.5 | $0.00000 | $0.00376 |
Grade A, and why
dsl-vm-reverse scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
84% identical to dsl-vm-reverse — 11 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 370 lines — stays where its author put it; the contents beside it link to each section on GitHub.
🔄 DSL 自定义虚拟机逆向(DSL VM Reverse Engineering)
用于逆向基于 JavaScript 实现的自定义 WASM 虚拟机/风控引擎
目录
1. 适用范围
当目标文件符合以下 任意特征 时使用本 skill:
| # | 特征 | 说明 |
|---|---|---|
| 1 | IIFE 开头 + 大量单字母变量名 | !function(){var U=void 0,y=parseInt,E0=Function,...} |
| 2 | 包含 DG() 或类似函数含 switch-case 循环 |
解释器主循环,d[7]&31 解码 opcode |
| 3 | 大文件(500KB+)但零字节占比 < 1% | 非标准 WASM,纯 JS |
| 4 | 包含 C[number] 常量表引用 |
C[9][xxx] 函数表/字符串表 |
| 5 | 单行压缩代码 | 583KB 单行,混淆变量名 |
排除规则
| 条件 | 非本 skill | 转至 |
|---|---|---|
文件以 \x00asm 开头 |
标准 WASM 二进制 | reverse-engineering/languages.md |
文件以 Uint8Array([0,97,115,109]) 含 WASM 魔术字 |
WASM 嵌入式 | 提取 .wasm 后转 IDA/Ghidra |
标准 Webpack 打包(function(e,t,n){...}) |
普通 JS | js-reverse/ |
| 零字节占比 > 20% | WASM 二进制 | reverse-engineering/languages.md |
2. DSL VM 识别特征
代码特征
// 特征 1: IIFE 入口,单字母变量映射数字常量
!function(){
var U=void 0, y=parseInt, E0=Function, AN=Uint8Array;
var E=15, l=10, m=12, x=16, S=13, $=11;
// 数字常量映射为变量名,替代原始数字
...
}
// 特征 2: 解释器主循环 DG()
function DG(C, d, ...) {
var d = []; // 数组模拟 WASM stack/locals
for (d[7] = x; d[7] !== U;) {
var aE = d[7] & 31; // 低 5 位 = opcode
var O = d[7] >> 5 & 31; // 高 5 位 = sub-operation
switch (aE) {
case 0: /* ... */ d[7] = 612; break;
case 1: /* ... */
// ... N 个 case
}
}
}
// 特征 3: 常量表 C[9] 存储函数索引和字符串
// C[9][0] = ["pc"] → 函数参数描述
// C[9][667] = "string" → 字符串常量
// C[9][x] = number → 函数索引
// 特征 4: W(C[index], null, ...) 调用模式
// W = Function.prototype.call.bind(call)
// 所有内置函数通过 C[index] 索引调用
// 特征 5: 指令编码格式
// d[7] = opcode(bit 0-4) | subop(bit 5-9) | operand(bit 10+)
Opcode 编码格式
每条指令编码为 32 位整数:
bit 0-4: opcode (0-N)
bit 5-9: sub-operation (0-31)
bit 10-31: operand/立即数
解码:
aE = d[7] & 31 → opcode
O = d[7] >> 5 & 31 → sub-operation
d[other] = d[7] >> 10 → operand
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 370 lines · 0 tokens per session scan A 94c47cf83b90
dsl-vm-reverse is a skill published in the GitHub repository Asaiuta/reverse-workbench-skill (2 stars, last pushed 25d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 3,756 tokens. A static security scan graded it A with 0 findings. It is 84% identical to dsl-vm-reverse, differing in 11 lines, and is treated as a copy.
Other skills, from other repositories
osint-recon
A knowledge guide for open-source intelligence, or OSINT: collecting information from publicly available sources. It covers servers, websites, domains, and, when appropriate, people.
hackerone
A safety wrapper for HackerOne bug-bounty testing that reads a program's allowed targets and rules before handing each allowed asset to a penetration-testing workflow. HackerOne is a platform where companies invite researchers to report security bugs.
crypto-toolkit
A toolkit for encoding, decoding, hashing, and encrypting data in formats such as Base64, hexadecimal, URLs, JWTs, AES, RSA, and common ciphers.
redteam-cve-lookup
CVE lookup and applicability assessment domain card. Use after reconnaissance has identified products, versions, services, or fingerprints and red-team mode needs evidence-based CVE matching before deeper testing.
redteam-cve-validation
CVE validation domain card. Use after CVE lookup has produced applicable or candidate CVEs and red-team mode needs scoped evidence to decide whether to continue, pivot, or report.
secknowledge-skill
A knowledge base for testing the security of websites, software, and AI systems, including agents and language models.