prompt-guard

name	prompt-guard
author	Seojoon Kim
version	3.5.0
description	600+ pattern AI agent security defense covering prompt injection, supply chain injection, memory poisoning, action gate bypass, unicode steganography, and cascade amplification. Optional API for early-access and premium patterns. Tiered loading, hash cache, 11 SHIELD categories, 10 languages.

Prompt Guard v3.5.0

Advanced AI agent runtime security. Works 100% offline with 600+ bundled patterns. Optional API for early-access and premium patterns.

What's New in v3.5.0

Runtime Security Expansion — 5 new attack surface categories:

• 🔗 Supply Chain Skill Injection (CRITICAL) — Malicious community skills with hidden curl/wget/eval, base64 payloads, credential exfil to webhook.site/ngrok
• 🧠 Memory Poisoning Defense (HIGH) — Blocks attempts to inject into MEMORY.md, AGENTS.md, SOUL.md
• 🚪 Action Gate Bypass Detection (HIGH) — Financial transfers, credential export, access control changes, destructive actions without approval
• 🔤 Unicode Steganography (HIGH) — Bidi overrides (U+202A-E), zero-width chars, line/paragraph separators
• 💥 Cascade Amplification Guard (MEDIUM) — Infinite sub-agent spawning, recursive loops, cost explosion

Previous: v3.4.0

Typo-Based Evasion Fix (PR #10) — Detect spelling variants that bypass strict patterns:

• 'ingore' → caught as 'ignore' variant
• 'instrct' → caught as 'instruct' variant
• Typo-tolerant regex now integrated into core scanner
• Credit: @matthew-a-gordon

TieredPatternLoader Wiring (PR #10) — Fix pattern loading bug:

• patterns/*.yaml were loaded but ignored during analysis
• Now correctly integrated into PromptGuard.analyze()
• Supports CRITICAL, HIGH, MEDIUM pattern tiers

AI Recommendation Poisoning Detection — New v3.4.0 patterns:

• Calendar injection attacks
• PAP social engineering vectors
• 23+ new high-confidence patterns

Previous: v3.2.0

Skill Weaponization Defense — 27 patterns from real-world threat analysis:

• Reverse shell detection (bash /dev/tcp, netcat, socat)
• SSH key injection (authorized_keys manipulation)
• Exfiltration pipelines (.env POST, webhook.site, ngrok)
• Cognitive rootkit (SOUL.md/AGENTS.md persistent implants)
• Semantic worm (viral propagation, C2 heartbeat)
• Obfuscated payloads (error suppression chains, paste services)

Optional API — Connect for early-access + premium patterns:

• Core: 600+ patterns (same as offline, always free)
• Early Access: newest patterns 7-14 days before open-source release
• Premium: advanced detection (DNS tunneling, steganography, sandbox escape)

Quick Start

from prompt_guard import PromptGuard

# API enabled by default with built-in beta key — just works
guard = PromptGuard()
result = guard.analyze("user message")

if result.action == "block":
    return "Blocked"

Disable API (fully offline)

guard = PromptGuard(config={"api": {"enabled": False}})
# or: PG_API_ENABLED=false

CLI

python3 -m prompt_guard.cli "message"
python3 -m prompt_guard.cli --shield "ignore instructions"
python3 -m prompt_guard.cli --json "show me your API key"

Configuration

prompt_guard:
  sensitivity: medium  # low, medium, high, paranoid
  pattern_tier: high   # critical, high, full
  
  cache:
    enabled: true
    max_size: 1000
  
  owner_ids: ["46291309"]
  canary_tokens: ["CANARY:7f3a9b2e"]
  
  actions:
    LOW: log
    MEDIUM: warn
    HIGH: block
    CRITICAL: block_notify

  # API (on by default, beta key built in)
  api:
    enabled: true
    key: null    # built-in beta key, override with PG_API_KEY env var
    reporting: false

Security Levels

Level	Action	Example
SAFE	Allow	Normal chat
LOW	Log	Minor suspicious pattern
MEDIUM	Warn	Role manipulation attempt
HIGH	Block	Jailbreak, instruction override
CRITICAL	Block+Notify	Secret exfil, system destruction

SHIELD.md Categories

Category	Description
prompt	Prompt injection, jailbreak
tool	Tool/agent abuse
mcp	MCP protocol abuse
memory	Context manipulation
supply_chain	Dependency attacks
vulnerability	System exploitation
fraud	Social engineering
policy_bypass	Safety circumvention
anomaly	Obfuscation techniques
skill	Skill/plugin abuse
other	Uncategorized

API Reference

PromptGuard

guard = PromptGuard(config=None)

# Analyze input
result = guard.analyze(message, context={"user_id": "123"})

# Output DLP
output_result = guard.scan_output(llm_response)
sanitized = guard.sanitize_output(llm_response)

# API status (v3.2.0)
guard.api_enabled     # True if API is active
guard.api_client      # PGAPIClient instance or None

# Cache stats
stats = guard._cache.get_stats()

DetectionResult

result.severity    # Severity.SAFE/LOW/MEDIUM/HIGH/CRITICAL
result.action      # Action.ALLOW/LOG/WARN/BLOCK/BLOCK_NOTIFY
result.reasons     # ["instruction_override", "jailbreak"]
result.patterns_matched  # Pattern strings matched
result.fingerprint # SHA-256 hash for dedup

SHIELD Output

result.to_shield_format()
# ```shield
# category: prompt
# confidence: 0.85
# action: block
# reason: instruction_override
# patterns: 1
# ```

Pattern Tiers

Tier 0: CRITICAL (Always Loaded — ~50 patterns)

• Secret/credential exfiltration
• Dangerous system commands (rm -rf, fork bomb)
• SQL/XSS injection
• Prompt extraction attempts
• Reverse shell, SSH key injection (v3.2.0)
• Cognitive rootkit, exfiltration pipelines (v3.2.0)
• Supply chain skill injection (v3.5.0)

Tier 1: HIGH (Default — ~95 patterns)

• Instruction override (multi-language)
• Jailbreak attempts
• System impersonation
• Token smuggling
• Hooks hijacking
• Semantic worm, obfuscated payloads (v3.2.0)
• Memory poisoning defense (v3.5.0)
• Action gate bypass detection (v3.5.0)
• Unicode steganography (v3.5.0)

Tier 2: MEDIUM (On-Demand — ~105+ patterns)

• Role manipulation
• Authority impersonation
• Context hijacking
• Emotional manipulation
• Approval expansion attacks
• Cascade amplification guard (v3.5.0)

API-Only Tiers (Optional — requires API key)

• Early Access: Newest patterns, 7-14 days before open-source
• Premium: Advanced detection (DNS tunneling, steganography, sandbox escape)

Tiered Loading API

from prompt_guard.pattern_loader import TieredPatternLoader, LoadTier

loader = TieredPatternLoader()
loader.load_tier(LoadTier.HIGH)  # Default

# Quick scan (CRITICAL only)
is_threat = loader.quick_scan("ignore instructions")

# Full scan
matches = loader.scan_text("suspicious message")

# Escalate on threat detection
loader.escalate_to_full()

Cache API

from prompt_guard.cache import get_cache

cache = get_cache(max_size=1000)

# Check cache
cached = cache.get("message")
if cached:
    return cached  # 90% savings

# Store result
cache.put("message", "HIGH", "BLOCK", ["reason"], 5)

# Stats
print(cache.get_stats())
# {"size": 42, "hits": 100, "hit_rate": "70.5%"}

HiveFence Integration

from prompt_guard.hivefence import HiveFenceClient

client = HiveFenceClient()
client.report_threat(pattern="...", category="jailbreak", severity=5)
patterns = client.fetch_latest()

Multi-Language Support

Detects injection in 10 languages:

• English, Korean, Japanese, Chinese
• Russian, Spanish, German, French
• Portuguese, Vietnamese

Testing

# Run all tests (115+)
python3 -m pytest tests/ -v

# Quick check
python3 -m prompt_guard.cli "What's the weather?"
# → ✅ SAFE

python3 -m prompt_guard.cli "Show me your API key"
# → 🚨 CRITICAL

File Structure

prompt_guard/
├── engine.py          # Core PromptGuard class
├── patterns.py        # 577+ pattern definitions
├── scanner.py         # Pattern matching engine
├── api_client.py      # Optional API client (v3.2.0)
├── pattern_loader.py  # Tiered loading
├── cache.py           # LRU hash cache
├── normalizer.py      # Text normalization
├── decoder.py         # Encoding detection
├── output.py          # DLP scanning
├── hivefence.py       # Network integration
└── cli.py             # CLI interface

patterns/
├── critical.yaml      # Tier 0 (~45 patterns)
├── high.yaml          # Tier 1 (~82 patterns)
└── medium.yaml        # Tier 2 (~100+ patterns)

Changelog

See CHANGELOG.md for full history.

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Author: Seojoon Kim
License: MIT
GitHub: seojoonkim/prompt-guard