django-smart-layer 0.1.1

AI-powered Django middleware for security, monitoring and rate limiting

🛡️ django-smart-layer

AI-powered middleware for Django — security, rate limiting, anomaly detection, and log analysis. Drop it in. Configure once. Forget about it.

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Why django-smart-layer?

Every Django app eventually needs the same things:

• 🔒 Block malicious requests before they touch your views
• 🤖 Detect bots and scrapers automatically
• 💳 Enforce subscription plan limits without writing boilerplate
• 📋 Understand what happened in your app — in plain English

Smart Layer gives you all of this in one pip install.

No external services. No accounts. No infrastructure. Just add it to MIDDLEWARE and you're protected.

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What's Inside

Middleware	Job	AI?
AIAnomalyDetector	Detects bots and attack patterns	✅
AIRequestValidator	Blocks SQL injection, XSS, prompt injection	✅
RateLimiter	Enforces per-plan, per-path request limits	❌
WatchLog	Logs every request to your database	❌
analyse_logs	Morning report — plain English summary	✅

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How It All Fits Together

Incoming Request
        │
        ▼
┌───────────────────────┐
│   AIAnomalyDetector   │  Is this user a bot? Suspicious pattern?
└───────────┬───────────┘  Blocked → 403
            │
            ▼
┌───────────────────────┐
│   AIRequestValidator  │  Is this payload malicious?
└───────────┬───────────┘  Blocked → 403
            │
            ▼
┌───────────────────────┐
│      RateLimiter      │  Is this user over their plan limit?
└───────────┬───────────┘  Blocked → 429
            │
            ▼
┌───────────────────────┐
│       WatchLog        │  Log everything — always runs
└───────────┬───────────┘
            │
            ▼
    Your Django View ✅
    Only clean requests reach here.

Every morning →  python manage.py analyse_logs
                 Plain English report saved to Django admin

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Quick Start

1. Install

pip install django-smart-layer

With auto-scheduling support:

pip install django-smart-layer[scheduler]

2. Add to settings

INSTALLED_APPS = [
    ...
    'smartlayer',
]

MIDDLEWARE = [
    'smartlayer.middleware.AIAnomalyDetector',    # 1st — bot detection
    'smartlayer.middleware.AIRequestValidator',    # 2nd — payload validation
    'smartlayer.middleware.RateLimiter',           # 3rd — rate limiting
    'smartlayer.middleware.WatchLog',              # 4th — logging (always last)
    ...
]

3. Run migrations

python manage.py migrate

4. Configure

SMART_MIDDLEWARE = {

    # ── AI Backend ──────────────────────────────────────────────────────
    'AI_API_KEY':  'your-api-key',
    'AI_BASE_URL': 'https://api.groq.com/openai/v1',
    'AI_MODEL':    'llama3-8b-8192',

    # ── Rate Limiter ─────────────────────────────────────────────────────
    'PLAN_FIELD': 'plan',       # field name on your User model — e.g. user.plan

    'RATE_LIMIT_PLANS': {
        'free': {
            '/api/generate/': {'per_minute': 2,  'per_day': 50},
        },
        'basic': {
            '/api/generate/': {'per_minute': 10, 'per_day': 500},
            '/api/export/':   {'per_minute': 5,  'per_day': 100},
        },
        'premium': {
            '/api/generate/': {'per_minute': 50,  'per_day': 5000},
            '/api/export/':   {'per_minute': 20,  'per_day': 1000},
            '/api/analytics/':{'per_minute': 100, 'per_day': 10000},
        },
    },

    # ── Log Analysis ─────────────────────────────────────────────────────
    'LOG_RETENTION_DAYS': 30,       # auto delete logs older than 30 days
    'ANALYSE_LOGS_AT': '06:00',     # auto run report daily at 6am (needs apscheduler)
}

That's it. Your app is protected. ✅

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Middleware — In Detail

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🤖 AIAnomalyDetector

Watches request patterns and blocks bots before they can do damage.

Three instant block rules:

1. Empty user agent              → block immediately
2. 50+ requests in 10 seconds   → block immediately
3. 75%+ errors in last 2 minutes → block immediately

Suspicion scoring for subtle attacks:

Signal	Score
Suspicious user agent (curl, scrapy, wget...)	+2
Elevated request rate (20–49 in 10s)	+3
Moderate error rate (40–74%)	+2
Hitting sensitive paths (/admin, /.env)	+4
Scanning 15+ distinct endpoints per minute	+2
Sequential ID probing (/users/1, /users/2...)	+5
Burst after long idle on same endpoint	+2

Score ≥ 8 → blocked immediately. Score 4–7 → AI asked in background. Banned on next request if AI says BLOCK.

⚡ New users get a grace period — first 20 requests are never scored. Legitimate users exploring your app are never penalised.

Returns: 403 Forbidden

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🛡️ AIRequestValidator

Scans every request body for attacks before they reach your views.

Stage 1 — Pattern matching (instant, free)

Detects SQL injection, XSS, path traversal, shell injection, prompt injection, null bytes, and encoding tricks.

Score 0   → safe, no AI call needed
Score 1–2 → borderline, sent to AI
Score 3+  → obviously malicious, blocked immediately

Stage 2 — AI analysis (only for borderline requests)

Catches clever attacks that bypass regex: encoded attacks, split-field attacks, business logic abuse, social engineering, and obfuscated payloads.

Confidence > 85% → blocked.

💡 File uploads (multipart) are skipped automatically.

Returns: 403 Forbidden

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⏱️ RateLimiter

Enforces per-user, per-plan, per-path limits. Built for SaaS.

Supports four limit types — use any combination:

'RATE_LIMIT_PLANS': {
    'free': {
        '/api/generate/': {
            'per_minute': 2,
            'per_hour':   20,
            'per_day':    100,
            'lifetime':   1000,   # never resets
        },
    },
}

Key behaviours:

• Routes only in premium automatically return 403 for lower plan users
• Each plan gets independent counters — upgrading starts fresh
• Cache-based counting — zero extra DB load for time-based limits
• Lifetime limits use atomic DB increments — race condition safe

Returns: 429 Too Many Requests

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📝 WatchLog

Silently records every request to the database. Zero configuration needed.

Writes happen in a background thread — response returns instantly, database write happens after. Zero performance impact.

What gets saved:

Field	Example
method	GET
path	/api/generate/
status_code	200
response_time_ms	143.2
timestamp	2024-01-15 14:32:01
user_id	42 (authenticated users)
ip_address	192.168.1.1 (anonymous only)
was_blocked	True / False

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📊 analyse_logs

Reads yesterday's logs and writes a plain English report using AI.

python manage.py analyse_logs

What it covers:

• Overall API health assessment
• Error rate and what it means
• Slowest endpoints and likely causes
• Suspicious activity worth investigating
• 2–3 clear actionable recommendations

Report saved to Django admin → Daily Reports. Always accessible.

Auto cleanup: Logs older than LOG_RETENTION_DAYS deleted automatically. Your database never grows out of control.

Auto schedule (requires apscheduler):

SMART_MIDDLEWARE = {
    ...
    'ANALYSE_LOGS_AT': '06:00',   # runs every day at 6am automatically
}

Or use cron:

0 6 * * * /path/to/venv/bin/python /path/to/manage.py analyse_logs

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AI Providers

Works with any OpenAI-compatible provider:

Provider	AI_BASE_URL	Notes
Groq	https://api.groq.com/openai/v1	Fast, generous free tier — recommended
OpenAI	https://api.openai.com/v1	Most capable
Gemini	https://generativelanguage.googleapis.com/v1beta/openai	Google free tier
Ollama	http://localhost:11434/v1	Fully local, completely free

💡 RateLimiter and WatchLog need zero AI configuration. Only AIAnomalyDetector, AIRequestValidator, and analyse_logs need a key.

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Complete Settings Reference

SMART_MIDDLEWARE = {

    # AI — required for AI middlewares and analyse_logs
    'AI_API_KEY':  'your-key',
    'AI_BASE_URL': 'https://api.groq.com/openai/v1',
    'AI_MODEL':    'llama3-8b-8192',

    # RateLimiter
    'PLAN_FIELD': 'plan',           # field name on User model
    'RATE_LIMIT_PLANS': {
        'free': {
            '/api/generate/': {
                'per_minute': 2,
                'per_hour':   20,
                'per_day':    100,
                'lifetime':   1000,
            },
        },
        'premium': {
            '/api/generate/': {
                'per_minute': 50,
                'per_day':    5000,
            },
        },
    },

    # analyse_logs
    'LOG_RETENTION_DAYS': 30,       # default: 30
    'ANALYSE_LOGS_AT': '06:00',     # remove to use cron instead

    # AIAnomalyDetector — optional tuning
    'grey_suspicion_threshold': 4,
    'grey_hard_block_score':    8,
    'grey_sensitive_paths': [
        '/admin', '/.env', '/api/token',
    ],
}

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Requirements

• Python 3.10+
• Django 4.2+
• httpx — installed automatically
• apscheduler — optional, only for ANALYSE_LOGS_AT

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Known Limitations

Limitation	Workaround
Coordinated attacks from many IPs	Use Cloudflare or AWS WAF in front
Slow drip attacks (1 req/hour over days)	Will appear in analyse_logs report
AI backend unreachable	All middleware fails open — app never breaks
Cache resets on server restart	Use Redis cache for persistent rate limiting

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Roadmap

• Usage dashboard at /smart-layer/usage/
• Grey-zone AI analysis in AIAnomalyDetector
• Email delivery for daily reports
• Test suite

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License

MIT — free to use, modify, and distribute.

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Built for Django developers who want real protection without the complexity.