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 RedHatProductSecurity/prodsec-skills --skill harness-writinggit clone --depth 1 https://github.com/RedHatProductSecurity/prodsec-skillsWrote 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/redhatproductsecurity/prodsec-skills/harness-writing)<a href="https://agentmods.dev/skills/redhatproductsecurity/prodsec-skills/harness-writing"><img src="https://agentmods.dev/badge/skills/redhatproductsecurity/prodsec-skills/harness-writing/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/redhatproductsecurity/prodsec-skills/harness-writing"><img src="https://agentmods.dev/badge/skills/redhatproductsecurity/prodsec-skills/harness-writing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00028 | $0.05160 |
| Opus 5 | $0.00014 | $0.02580 |
| Sonnet 5 | $0.00006 | $0.01032 |
| Haiku 4.5 | $0.00003 | $0.00516 |
Grade A, and why
harness-writing 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 8d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- harness-writing — 97% identical, 11 lines differ
How it starts
The opening of the file, as written. The whole thing — 618 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Writing Fuzzing Harnesses
A fuzzing harness is the entrypoint function that receives random data from the fuzzer and routes it to your system under test (SUT). The quality of your harness directly determines which code paths get exercised and whether critical bugs are found. A poorly written harness can miss entire subsystems or produce non-reproducible crashes.
Overview
The harness is the bridge between the fuzzer's random byte generation and your application's API. It must parse raw bytes into meaningful inputs, call target functions, and return early for invalid or out-of-range inputs without crashing the harness. The most important part of any fuzzing setup is the harness—if written poorly, critical parts of your application may not be covered.
Key Concepts
| Concept | Description |
|---|---|
| Harness | Function that receives fuzzer input and calls target code under test |
| SUT | System Under Test—the code being fuzzed |
| Entry point | Function signature required by the fuzzer (e.g., LLVMFuzzerTestOneInput) |
| FuzzedDataProvider | Helper class for structured extraction of typed data from raw bytes |
| Determinism | Property that ensures same input always produces same behavior |
| Interleaved fuzzing | Single harness that exercises multiple operations based on input |
When to Apply
Apply this technique when:
- Creating a new fuzz target for the first time
- Fuzz campaign has low code coverage or isn't finding bugs
- Crashes found during fuzzing are not reproducible
- Target API requires complex or structured inputs
- Multiple related functions should be tested together
Skip this technique when:
- Using existing well-tested harnesses from your project
- Tool provides automatic harness generation that meets your needs
- Target already has comprehensive fuzzing infrastructure
Quick Reference
| Task | Pattern |
|---|---|
| Minimal C++ harness | extern "C" int LLVMFuzzerTestOneInput(const uint8_t* data, size_t size) |
| Minimal Rust harness | `fuzz_target!( |
| Size validation | if (size < MIN_SIZE) return 0; |
| Cast to integers | uint32_t val = *(uint32_t*)(data); |
| Use FuzzedDataProvider | FuzzedDataProvider fuzzed_data(data, size); |
| Extract typed data (C++) | auto val = fuzzed_data.ConsumeIntegral<uint32_t>(); |
| Extract string (C++) | auto str = fuzzed_data.ConsumeBytesWithTerminator<char>(32, 0xFF); |
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.
- 8d ago First seen · 618 lines · 28 tokens per session scan A a110bff87ceb
harness-writing is a skill published in the GitHub repository RedHatProductSecurity/prodsec-skills (52 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 28 tokens to every session and 5,160 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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