Borrowing it
Nothing to install: this file belongs to luisfurquim/wings. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/luisfurquim/wings/main/.claude/skills/sec-fuzzing/SKILL.mdgit clone --depth 1 https://github.com/luisfurquim/wingsWrote 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/luisfurquim/wings/sec-fuzzing)<a href="https://agentmods.dev/skills/luisfurquim/wings/sec-fuzzing"><img src="https://agentmods.dev/badge/skills/luisfurquim/wings/sec-fuzzing.svg" alt="Measured on agentmods" 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 | $0.00067 | $0.00906 |
| Opus 5 | $0.00034 | $0.00453 |
| Sonnet 5 | $0.00013 | $0.00181 |
| Haiku 4.5 | $0.00007 | $0.00091 |
Grade A, and why
sec-fuzzing 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.
How it starts
The opening of the file, as written. The whole thing — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Continuous Fuzzing (Go native)
djb minimized parsers because parsers are where bugs live; Apollo verified exhaustively because there was no patching after launch. Fuzzing is the modern tool that serves both: machine-generated hostile input, continuously, against every parser that survived minimization.
Where the parsers are (priority order)
| Target | Why | Harness note |
|---|---|---|
expr.ParseFlexBlock, expr.TokenizeFlexContent, expr.ParseReference, splitSymbols |
hand-written string parsers; webdev-authored input; the leniency/passthrough contract must hold for ALL inputs | pure Go, fuzz natively |
cmd/gen_i18n catalog align/remap (align.go: exact map + anchored Levenshtein) |
merges old+new catalogs; corruption here silently destroys translations | fuzz the pure functions; fixture HTML via f.Add seeds |
codec |
de/serialization | classic round-trip target |
wi18n catalog load + verify.go |
runtime-fetched JSON + ed25519 .sig; must refuse, never panic, on garbage |
structure as portable funcs if needed |
wi18n/fmt*, currency parsing |
locale data → formatting |
Go fuzzing runs on native targets only — another reason parsing logic stays
in portable packages (expr/ already is; see sec-wasm-go).
Writing targets
func FuzzParseFlexBlock(f *testing.F) {
f.Add("{{@gender %qt #0}}") // seeds: real syntax from docs/demo
f.Add("{{%qt *flexer ~$produto}}")
f.Add("{{=cesta @gender %n}}")
f.Fuzz(func(t *testing.T, s string) {
blk, err := expr.ParseFlexBlock(s) // property 1: never panics
if err != nil { return }
_ = blk.Render(...) // property 2: accepted input renders
})
}
Properties worth asserting beyond "no panic":
- Round-trip: tokenize → reassemble ≍ input (modulo documented space
collapse in
TokenizeFlexContent). - Fail-closed: for verify.go, a mutated body or sig NEVER verifies; flipping any byte of a known-good pair must yield an error.
- Idempotence: running align/remap twice equals running it once (the restart-protection property from sec-fail-operational, made testable).
- No index out of range: any catalog index arriving from fuzzed JSON is bounds-checked, returns error.
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 · 71 lines · 67 tokens per session scan A 427aca2e84f8
sec-fuzzing is a skill published in the GitHub repository luisfurquim/wings (29 stars, last pushed 1mo ago), licensed MPL-2.0. It adds 67 tokens to every session and 906 once invoked, about $0.0003 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 2026-08-30.
Other skills, from other repositories
research-engineer
An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.
tika-eval-compare
Compare extracts from two Tika builds over a corpus to detect regressions in content, encoding, exceptions, and embedded-document handling. Use for "compare before/after extracts", "eval this change against the corpus".
neuron-evaluation-engineer
Create and run AI evaluations with datasets, assertions, and output drivers in Neuron AI. Use this skill whenever the user mentions evaluation, testing AI systems, creating evaluators, dataset-driven testing, assertion-based validation, or wants to measure AI system performance. Also trigger for tasks involving…
jetson-validate-image
Use after jetson-flash-image to run static BSP checks, on-target smoke/regression tests on a flashed DUT, or both. Not for build or flash steps. Triggers: validate bsp, on-target validation.
atmos-validation
Validate Atmos projects, components, arbitrary JSON Schema inputs, EditorConfig, and GitHub Actions; use affected-file selection and native CI annotations.
skill-benchmark
Benchmark AI skill effectiveness by measuring implementation quality against legacy constraints.