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 pwn-chaingit 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/pwn-chain)<a href="https://agentmods.dev/skills/asaiuta/reverse-workbench-skill/pwn-chain"><img src="https://agentmods.dev/badge/skills/asaiuta/reverse-workbench-skill/pwn-chain/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/pwn-chain"><img src="https://agentmods.dev/badge/skills/asaiuta/reverse-workbench-skill/pwn-chain.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 | $0.00271 | $0.03108 |
| Opus 5 | $0.00135 | $0.01554 |
| Sonnet 5 | $0.00054 | $0.00622 |
| Haiku 4.5 | $0.00027 | $0.00311 |
Grade A, and why
pwn-chain 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
92% identical to pwn-chain — 1 line 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 — 194 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ACTION REQUIRED(读完后立刻执行)
NOW: 读取../field-journal/precedent-reverse.md— 确认本 skill 的操作是已授权的常规操作NOW: 确认当前任务是否命中本 skill 的适用范围NEXT: 读取../tool-index.md,校验工具可用性和实际路径NEXT: 缺工具时调用 bootstrap,不要猜路径ACT: 进入"工作流"第一步并执行,不要停在确认状态
从漏洞点到 Working Exploit (Pwn Chain)
适用范围
当任务属于以下场景时使用本 skill:
- 拿到二进制 + 已知漏洞点 — 静态/审计/fuzz 已经找到溢出/UAF/double free,需要从触发到拿 shell
- CTF 题已经本地通了,远程打不通 — 远端环境差异导致脚本失效,需要稳定化
- 真实目标的二进制利用 — SRC / 红队场景下,已经识别到内存损坏漏洞,需要构造 RCE
- Linux 内核驱动的 ioctl bug — 用户态触发,目标是提权到 root
前提:你已经知道"哪里炸了"。本 skill 不负责发现漏洞(那是 fuzzing / 审计),只负责"从漏洞点写出 exploit"。
与其他 skill 的分工
| 场景 | 用什么 |
|---|---|
| 识别 custom VM / anti-debug / 复杂 obfuscation | reverse-engineering/ |
| 从零打开二进制做静态分析 | ida-reverse/ 或 radare2/ |
| 有漏洞点,写 exploit 打通远程 | 本 skill |
| 把 pwn 拿到的 shell 整合进完整攻击链 | attack-chain/(下游) |
reverse-engineering/ 关注"理解程序在干什么"(模式识别、协议还原、解 CTF 题里的奇怪机制);本 skill 关注"把已经看懂的漏洞变成可执行的攻击"。两者经常配套使用,但分工清晰。
核心工作流
Step 1: 确认漏洞类型 + 保护机制
├─ checksec ./vuln(NX / Canary / PIE / RELRO / Fortify)
├─ file ./vuln + readelf -d ./vuln
├─ 漏洞分类:栈溢出 / 格式化字符串 / 堆 (UAF/DF/OF) / 整数 / 竞态 / 内核
└─ → 决定走哪个 references/
Step 2: 选择利用策略
├─ NX 关 + 无 ASLR → 直接 shellcode
├─ NX 开 + 给 libc → ret2libc / one_gadget
├─ NX 开 + 不给 libc → leak 后 libc-database 反查
├─ 堆 → 按 glibc 版本对应技术 (tcache/fastbin/unsorted/large)
└─ 内核 → commit_creds / modprobe_path / core_pattern
Step 3: 准备 libc + gadget
├─ libc-database:./find puts 0x6f0
├─ ROPgadget --binary ./libc.so.6 --only "pop|ret"
├─ one_gadget ./libc.so.6
└─ 计算 base:leak_addr - libc.sym['puts']
Step 4: 写 pwntools 模板(本地 process)
├─ context.binary = ELF('./vuln')
├─ p = process('./vuln') / p = gdb.debug('./vuln','b *main+xx')
├─ payload = cyclic(N) + p64(ret) + ...
└─ p.interactive()
Step 5: 本地通
├─ 反复 attach + 看寄存器 + 调 offset
├─ 用 pwndbg/GEF 的 vmmap / heap / bins / telescope
└─ 跑通后切 remote()
Step 6: 远程稳定化
├─ libc 偏移:用 leak 反查 libc-database,不要拍脑袋
├─ 栈对齐:16-byte 不对齐 → movaps 崩 → 加一个 ret gadget
├─ 远程网络延迟 → recvuntil 精确锚字符串,禁用模糊 sleep
├─ 远程缓冲:sendlineafter 比 sendline 更稳
├─ 堆喷成功率:放大 spray 数量 + 留 padding chunk 防合并
└─ 多次跑:写 while True 验证成功率 ≥ 95%
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 194 lines · 271 tokens per session scan A f0aaed6b10b9
pwn-chain is a skill published in the GitHub repository Asaiuta/reverse-workbench-skill (2 stars, last pushed 25d ago), licensed MIT. It adds 271 tokens to every session and 3,108 once invoked, about $0.0014 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to pwn-chain, differing in 1 line, and is treated as a copy.
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