Borrowing it
Nothing to install: this file belongs to mtnyilmaz/agents. 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/mtnyilmaz/agents/main/.agents/skills/sast-sqli/SKILL.mdgit clone --depth 1 https://github.com/mtnyilmaz/agentsWrote 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/mtnyilmaz/agents/sast-sqli)<a href="https://agentmods.dev/skills/mtnyilmaz/agents/sast-sqli"><img src="https://agentmods.dev/badge/skills/mtnyilmaz/agents/sast-sqli/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/mtnyilmaz/agents/sast-sqli"><img src="https://agentmods.dev/badge/skills/mtnyilmaz/agents/sast-sqli.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 | $0.00081 | $0.05284 |
| Opus 5 | $0.00041 | $0.02642 |
| Sonnet 5 | $0.00016 | $0.01057 |
| Haiku 4.5 | $0.00008 | $0.00528 |
Grade A, and why
sast-sqli 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.
> [sqlmap command or manual curl payload to confirm this finding. How it starts
The opening of the file, as written. The whole thing — 486 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SQL Injection (SQLi) Detection
You are performing a focused security assessment to find SQL injection vulnerabilities in a codebase. This skill uses a two-phase approach with subagents: construction (find all places where SQL queries are built unsafely) then taint (confirm whether user-supplied input reaches those construction sites).
Prerequisites: sast/architecture.md must exist. Run the analysis skill first if it doesn't.
What is SQL Injection
SQL injection occurs when user-supplied input is incorporated into SQL queries through string concatenation or interpolation rather than parameterized binding. This allows attackers to alter query logic, bypass authentication, extract sensitive data, modify or delete records, and in some configurations execute OS commands.
The core pattern: unvalidated, unparameterized user input reaches a SQL query execution call.
What SQLi IS
- Concatenating user input directly into a SQL string:
"SELECT * FROM users WHERE name = '" + username + "'" - Using string formatting to build queries:
f"SELECT * FROM orders WHERE id = {order_id}" - Dynamic
ORDER BY/GROUP BY/ table/column names from user input with no allowlist validation - ORM raw query methods with unsanitized input:
User.objects.raw(f"SELECT * WHERE id={id}"),$queryRawUnsafe(input) - Second-order injection: input is stored in the DB and later used in a raw query without re-sanitization
What SQLi is NOT
Do not flag these as SQLi:
- IDOR: Changing
?id=1to?id=2to access another user's data — that's Insecure Direct Object Reference, a separate class - Mass assignment: Setting extra ORM model fields from user input — different vulnerability
- XSS via database: Storing a
<script>tag in the DB that's later rendered unescaped — that's XSS, not SQLi - NoSQL injection: Injecting into MongoDB operators — similar concept but a distinct vulnerability class
- Safe ORM queries: Parameterized ORM lookups like
User.objects.filter(id=user_id)orUser.find(params[:id])— do not flag these
What ships with it
1 file 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.
- 10d ago First seen · 486 lines · 81 tokens per session scan A 54c88efabdee
sast-sqli is a skill published in the GitHub repository mtnyilmaz/agents (6 stars, last pushed 3mo ago), licensed MIT. It adds 81 tokens to every session and 5,284 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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