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 marduk191/qwen3_mcp --skill fuzzing-dictionarygit clone --depth 1 https://github.com/marduk191/qwen3_mcpWrote 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/marduk191/qwen3_mcp/fuzzing-dictionary)<a href="https://agentmods.dev/skills/marduk191/qwen3_mcp/fuzzing-dictionary"><img src="https://agentmods.dev/badge/skills/marduk191/qwen3_mcp/fuzzing-dictionary/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/marduk191/qwen3_mcp/fuzzing-dictionary"><img src="https://agentmods.dev/badge/skills/marduk191/qwen3_mcp/fuzzing-dictionary.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 | $0.00032 | $0.02372 |
| Opus 5 | $0.00016 | $0.01186 |
| Sonnet 5 | $0.00006 | $0.00474 |
| Haiku 4.5 | $0.00003 | $0.00237 |
Grade A, and why
fuzzing-dictionary scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
man curl | grep -oP '^\s*(--|-)\K\S+' | sed 's/[,.]$//' | sed 's/^/"&/; s/$/&"/' | sort -u > man.dict This is a copy
94% identical to fuzzing-dictionary — 5 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 — 298 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Fuzzing Dictionary
A fuzzing dictionary provides domain-specific tokens to guide the fuzzer toward interesting inputs. Instead of purely random mutations, the fuzzer incorporates known keywords, magic numbers, protocol commands, and format-specific strings that are more likely to reach deeper code paths in parsers, protocol handlers, and file format processors.
Overview
Dictionaries are text files containing quoted strings that represent meaningful tokens for your target. They help fuzzers bypass early validation checks and explore code paths that would be difficult to reach through blind mutation alone.
Key Concepts
| Concept | Description |
|---|---|
| Dictionary Entry | A quoted string (e.g., "keyword") or key-value pair (e.g., kw="value") |
| Hex Escapes | Byte sequences like "\xF7\xF8" for non-printable characters |
| Token Injection | Fuzzer inserts dictionary entries into generated inputs |
| Cross-Fuzzer Format | Dictionary files work with libFuzzer, AFL++, and cargo-fuzz |
When to Apply
Apply this technique when:
- Fuzzing parsers (JSON, XML, config files)
- Fuzzing protocol implementations (HTTP, DNS, custom protocols)
- Fuzzing file format handlers (PNG, PDF, media codecs)
- Coverage plateaus early without reaching deeper logic
- Target code checks for specific keywords or magic values
Skip this technique when:
- Fuzzing pure algorithms without format expectations
- Target has no keyword-based parsing
- Corpus already achieves high coverage
Quick Reference
| Task | Command/Pattern |
|---|---|
| Use with libFuzzer | ./fuzz -dict=./dictionary.dict ... |
| Use with AFL++ | afl-fuzz -x ./dictionary.dict ... |
| Use with cargo-fuzz | cargo fuzz run fuzz_target -- -dict=./dictionary.dict |
| Extract from header | grep -o '".*"' header.h > header.dict |
| Generate from binary | strings ./binary | sed 's/^/"&/; s/$/&"/' > strings.dict |
Step-by-Step
Step 1: Create Dictionary File
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.
- 10d ago First seen · 298 lines · 32 tokens per session scan A 3247064b931f
fuzzing-dictionary is a skill published in the GitHub repository marduk191/qwen3_mcp (13 stars, last pushed 7mo ago), licensed MIT. It adds 32 tokens to every session and 2,372 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 94% identical to fuzzing-dictionary, differing in 5 lines, and is treated as a copy.
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