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 Eliyce/paqad-ai --skill input-validation-reviewgit clone --depth 1 https://github.com/Eliyce/paqad-aiWrote 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/eliyce/paqad-ai/input-validation-review)<a href="https://agentmods.dev/skills/eliyce/paqad-ai/input-validation-review"><img src="https://agentmods.dev/badge/skills/eliyce/paqad-ai/input-validation-review/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/eliyce/paqad-ai/input-validation-review"><img src="https://agentmods.dev/badge/skills/eliyce/paqad-ai/input-validation-review.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 | $0.00035 | $0.00950 |
| Opus 5 | $0.00017 | $0.00475 |
| Sonnet 5 | $0.00007 | $0.00190 |
| Haiku 4.5 | $0.00003 | $0.00095 |
Grade B, and why
input-validation-review scanned grade B with 2 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 9d 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.
Cloud metadata endpointmediumServer-side request forgery
One request to 169.254.169.254 can return temporary IAM credentials.
1. **SSRF scan**: Find all code paths that accept a URL, IP, or hostname and make an outbound request. Check for an explicit allowlist or blocked private-range validation (127.x, 10.x, 169.254.x, 172.16–31.x, `::1`, fd00 Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
- Shell exec with user input (`exec`, `system`, `passthru`, `child_process.exec`, `subprocess.run(shell=True)`) How it starts
The opening of the file, as written. The whole thing — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
What It Does
Reviews all code paths where user-supplied input reaches security-sensitive operations — outbound HTTP calls, database lookups, ORM constructors, shell commands, template renderers, deserializers, file operations, and regex evaluations — and produces findings for each category that lacks proof of safe handling.
Use This When
Use this when module docs or route inventories describe endpoints that accept URLs, resource IDs, request body fields, file uploads, or any user-controlled parameter that flows into a downstream system call.
Inputs
- Read the module docs to identify data flow surfaces.
- Read
references/input-attack-patterns.mdbefore scanning for each category. - Read tests and code evidence that could confirm or refute safe handling.
Procedure
-
SSRF scan: Find all code paths that accept a URL, IP, or hostname and make an outbound request. Check for an explicit allowlist or blocked private-range validation (127.x, 10.x, 169.254.x, 172.16–31.x,
::1, fd00::/8, AWS metadata169.254.169.254). -
IDOR scan: Find resource lookups keyed by a user-controlled ID. Verify an authorization check exists between ID resolution and data return — not just at the route level.
-
Mass assignment scan: Find ORM fill calls, model constructors, or serializers that accept the full request body. Verify an explicit allowlist (
$fillable,attr_accessible,schema.pick()) or blocklist exists. -
Injection vectors: Identify:
- Raw SQL construction or string interpolation in queries
- Shell exec with user input (
exec,system,passthru,child_process.exec,subprocess.run(shell=True)) - Template rendering with unsanitized data (
{!! !!},|raw,dangerouslySetInnerHTML,render_template_string) - Deserialization of untrusted data (
unserialize(),pickle.loads(),yaml.load()withoutLoader=SafeLoader) - LDAP injection in directory lookups
- XPath injection in XML processing
-
File upload abuse: Check MIME type validation, file extension allowlist, path traversal in the filename, storage isolation from the web root, and max-file-size enforcement.
What ships with it
6 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.
- 9d ago First seen · 78 lines · 35 tokens per session scan B 17201dec1a52
input-validation-review is a skill published in the GitHub repository Eliyce/paqad-ai (8 stars, last pushed yesterday), licensed MIT. It adds 35 tokens to every session and 950 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it B with 2 findings (cloud metadata endpoint, runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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