Here’s a **clean, production-ready system prompt** for that agent:

---

**🛡️ System Prompt – “Secrets Sentinel” Agent**

> **Role & Mission**:
> You are the **Secrets Sentinel**, an autonomous security agent tasked with **monitoring all incoming log entries** for any potential leaks of **API keys, passwords, tokens, or other sensitive credentials**. Your primary goal is to **detect and prevent secret exposure** before it propagates further through the system.
>
> **Core Responsibilities**:
>
> * **Scan all log streams in real-time** for:
>
>   * API keys (common formats: AWS, GCP, Azure, etc.)
>   * OAuth tokens
>   * SSH keys
>   * Passwords (plain text or encoded)
>   * JWTs or other bearer tokens
>   * Database connection strings
> * **Immediately flag** any suspicious entries.
> * **Classify severity** (e.g., HIGH – AWS root key; MEDIUM – temporary token).
> * **Sanitize or redact** leaked secrets before they’re written to persistent storage or shared further.
> * **Notify designated security channels or agents** of leaks, providing minimal necessary context.
>
> **Guidelines**:
>
> * Never expose the full secret in your alerts — redact most of it (e.g., `AKIA************XYZ`).
> * Be cautious of **false positives** (e.g., test data, dummy keys); err on the side of safety but include a “confidence score.”
> * Respect **privacy and operational integrity**: do not log or store the full value of any detected secret.
> * Assume the system may expand; be prepared to recognize **new secret formats** and learn from curator feedback.
>
> **Behavior Under Edge Cases**:
>
> * If unsure whether a string is a secret, flag it as **LOW severity** with a note for human review.
> * If you detect a high-severity leak, **trigger immediate alerts** and halt propagation of the compromised entry.
>
> **Your Output**:
>
> * A **structured alert** (JSON preferred) with:
>
>   * `timestamp`
>   * `source` (which log/agent)
>   * `type` of suspected secret
>   * `redacted_sample`
>   * `confidence_score` (0–1)
>   * `recommended_action` (e.g., “revoke key,” “rotate password,” “ignore dummy”)
>
> **Tone & Style**:
>
> * Precise, neutral, security-minded.
> * Avoid speculation beyond what you can confidently identify.

---
## 📂 **Version-Controlled `patterns.yaml` Format**

This lets you add/update/remove detection patterns **without touching code**.

```yaml
version: 1.2
last_updated: 2025-08-02

patterns:
  AWS_ACCESS_KEY:
    regex: "AKIA[0-9A-Z]{16}"
    description: "AWS Access Key ID"
    severity: HIGH
    confidence: 0.99
    active: true

  AWS_SECRET_KEY:
    regex: "(?i)aws(.{0,20})?(?-i)['\"][0-9a-zA-Z\/+]{40}['\"]"
    description: "AWS Secret Key"
    severity: HIGH
    confidence: 0.99
    active: true

  GITHUB_TOKEN:
    regex: "gh[pousr]_[0-9A-Za-z]{36}"
    description: "GitHub Personal Access Token"
    severity: HIGH
    confidence: 0.97
    active: true

  JWT:
    regex: "eyJ[A-Za-z0-9_-]+?\\.[A-Za-z0-9._-]+?\\.[A-Za-z0-9._-]+"
    description: "JSON Web Token"
    severity: MEDIUM
    confidence: 0.95
    active: true

meta:
  allow_feedback_learning: true
  require_human_review_above_confidence: 0.8
```

✅ **Advantages:**

- Regexes are editable without code changes.
    
- Can be versioned in Git for full audit trail.
    
- Can toggle `active: false` for deprecating broken rules.
    

---

## 🖼 **Flow Diagram (Secrets Sentinel)**

**Secrets Flow**

```
                ┌───────────────┐
   Logs Stream →│ Secrets       │
                │ Sentinel      │
                └──────┬────────┘
                       │
             ┌─────────┼─────────┐
             │                   │
       [Quarantine]        [Sanitized Logs]
             │                   │
      ┌──────┴──────┐       ┌────┴─────┐
      │High Severity│       │ Safe Data│
      │Secrets Only │       │ Storage  │
      └──────┬──────┘       └────┬─────┘
             │                   │
    ┌────────┼─────────┐         │
    │ Revocation Hooks │         │
    │ (AWS, GitHub,    │         │
    │ Slack, etc.)     │         │
    └────────┬─────────┘         │
             │                   │
        ┌────┴─────┐              │
        │ Webhooks │              │
        │ Key Kill │              │
        └────┬─────┘              │
             │
   ┌─────────┼─────────┐
   │ Feedback Loop     │
   │ (Curator/Human)   │
   └─────────┬─────────┘
             │
      ┌──────┴──────┐
      │ Meta-Learner│
      │ (new regex) │
      └──────┬──────┘
             │
      ┌──────┴───────┐
      │ patterns.yaml│
      └──────────────┘
```

---

## 🧪 **Test Harness Script**

This script simulates log scanning, quarantining, and revocation.

```python
import yaml, json, re
from datetime import datetime

# --- Load patterns.yaml ---
with open("patterns.yaml", "r") as f:
    patterns_config = yaml.safe_load(f)

PATTERNS = patterns_config["patterns"]

QUARANTINE = []
SANITIZED_LOGS = []

def redact(secret):
    return secret[:4] + "*" * (len(secret) - 7) + secret[-3:]

def scan_log(log_line, log_id, source_agent):
    alerts = []
    for secret_type, props in PATTERNS.items():
        if not props.get("active", True):
            continue
        match = re.search(props["regex"], log_line)
        if match:
            secret = match.group(0)
            severity = props["severity"]
            alert = {
                "timestamp": datetime.utcnow().isoformat() + "Z",
                "source_agent": source_agent,
                "log_line_id": log_id,
                "secret_type": secret_type,
                "redacted_sample": redact(secret),
                "confidence_score": props["confidence"],
                "severity": severity,
                "recommended_action": "Revoke key/rotate credentials" if severity == "HIGH" else "Review"
            }
            alerts.append(alert)

            # Quarantine if severity is HIGH
            if severity == "HIGH":
                quarantine_log(log_line, f"High severity secret detected: {secret_type}")
                trigger_revocation(secret_type, redact(secret))
    return alerts

def quarantine_log(log_line, reason):
    entry = {"timestamp": datetime.utcnow().isoformat() + "Z", "reason": reason, "log_line": log_line}
    QUARANTINE.append(entry)
    print(f"[QUARANTINE] {reason}")

def trigger_revocation(secret_type, redacted_sample):
    # Simulated webhook call
    print(f"[REVOCATION] Simulated revocation triggered for {secret_type} ({redacted_sample})")

def process_logs(logs):
    for i, log_line in enumerate(logs):
        alerts = scan_log(log_line, f"log_{i}", "agent_demo")
        if alerts:
            print(json.dumps(alerts, indent=2))
        else:
            SANITIZED_LOGS.append(log_line)

# --- Test Run ---
sample_logs = [
    "INFO User logged in successfully",
    "WARNING Found AWS key AKIA1234567890ABCD in commit",
    "DEBUG JWT detected eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.fake.fake"
]

process_logs(sample_logs)

print("\n--- Quarantine Store ---")
print(json.dumps(QUARANTINE, indent=2))
```

✅ **What this does:**

- Reads `patterns.yaml`
    
- Scans logs, prints alerts, quarantines high-severity entries
    
- Simulates revocation calls for AWS/GitHub/Slack
    
- Keeps sanitized logs separate from quarantined logs
    

---

## ✅ Next Expansions (Optional)

- 📦 **Redis/DB backend** for QUARANTINE instead of memory.
    
- 📡 **Real webhook integrations** (AWS STS, GitHub API, Slack API).
    
- 🧠 **Feedback ingestion module** (e.g., curator submits: `"false_positive": "AWS_ACCESS_KEY"` → adjusts regex in `patterns.yaml`).
    
- 🔄 **Auto-replay from Hyperlog** so Sentinel can retroactively scan old logs with new regex rules.
    

---
🔥 **production-grade spec**.

---

## 📂 **1️⃣ Feedback Ingestion Spec**

This defines how curators/humans give feedback to the Sentinel so it can **update its detection rules (patterns.yaml)** safely.

---

### 🔄 **Feedback Flow**

1. **Curator/Reviewer sees alert** → marks it as:
    
    - `false_positive` (regex over-triggered)
        
    - `missed_secret` (regex failed to detect)
        
    - `uncertain` (needs better regex refinement)
        
2. **Feedback API** ingests the report:
    

```json
{
  "alert_id": "log_345",
  "secret_type": "AWS_ACCESS_KEY",
  "feedback_type": "false_positive",
  "evidence": "Key was dummy data: TESTKEY123",
  "suggested_regex_fix": null
}
```

3. **Meta-Learner** updates rules:
    

- `false_positive` → adds **exceptions** (e.g., allowlist prefixes like `TESTKEY`).
    
- `missed_secret` → drafts **new regex** from evidence (using regex generator or LLM).
    
- Writes changes to **patterns.yaml** under `pending_review`.
    

4. **Security admin approves** before the new regex is marked `active: true`.
    

---

### 🧠 **Feedback Schema in YAML**

```yaml
pending_updates:
  - regex_name: AWS_ACCESS_KEY
    action: modify
    new_regex: "AKIA[0-9A-Z]{16}(?!TESTKEY)"
    confidence: 0.82
    status: "pending human review"
    submitted_by: curator_2
    timestamp: 2025-08-02T12:40:00Z
```

✅ This keeps **audit trails** & allows **safe hot updates**.

---

## ⚙️ **2️⃣ Real AWS/GitHub Webhook Payload Templates**

These are **example POST payloads** your Sentinel would send when it detects a leaked secret.

---

### 🔐 **AWS Access Key Revocation**

**Endpoint:**  
`POST https://security.example.com/hooks/aws-revoke`

**Payload:**

```json
{
  "event": "secret_leak_detected",
  "secret_type": "AWS_ACCESS_KEY",
  "redacted_key": "AKIA****XYZ",
  "log_reference": "hyperlog:58321",
  "recommended_action": "Revoke IAM access key immediately",
  "severity": "HIGH",
  "timestamp": "2025-08-02T12:45:00Z"
}
```

➡ Your security automation would call AWS CLI or IAM API:

```bash
aws iam update-access-key --access-key-id <redacted> --status Inactive
aws iam delete-access-key --access-key-id <redacted>
```

---

### 🐙 **GitHub Token Revocation**

**Endpoint:**  
`POST https://security.example.com/hooks/github-revoke`

**Payload:**

```json
{
  "event": "secret_leak_detected",
  "secret_type": "GITHUB_TOKEN",
  "redacted_key": "ghp_****abcd",
  "repository": "repo-name",
  "log_reference": "hyperlog:58322",
  "severity": "HIGH",
  "recommended_action": "Invalidate GitHub token via API",
  "timestamp": "2025-08-02T12:46:00Z"
}
```

➡ This would tie into GitHub’s [token-scanning API](https://docs.github.com/en/developers/overview/secret-scanning) or use PAT revocation.

---

### 💬 **Slack Token Revocation**

**Endpoint:**  
`POST https://security.example.com/hooks/slack-revoke`

**Payload:**

```json
{
  "event": "secret_leak_detected",
  "secret_type": "SLACK_TOKEN",
  "redacted_key": "xoxb****hjk",
  "workspace": "company-slack",
  "log_reference": "hyperlog:58323",
  "severity": "HIGH",
  "recommended_action": "Revoke Slack bot/user token",
  "timestamp": "2025-08-02T12:47:00Z"
}
```

➡ Slack Admin API can be used to **revoke** or **rotate**.

---

## 📡 **3️⃣ Redis or PostgreSQL Quarantine Store**

Switching from memory to **persistent storage** means quarantined logs survive restarts.

---

### ✅ **Redis Option (Fast, Volatile)**

```python
import redis, json
r = redis.Redis(host='localhost', port=6379, decode_responses=True)

def quarantine_log(log_line, reason):
    entry = {"timestamp": datetime.utcnow().isoformat() + "Z", "reason": reason, "log_line": log_line}
    r.lpush("quarantine", json.dumps(entry))
    print(f"[QUARANTINE] Stored in Redis: {reason}")
```

- 🏎 **Pros:** Fast, easy to scale.
    
- ⚠️ **Cons:** Volatile unless persisted (RDB/AOF).
    

---

### ✅ **PostgreSQL Option (Auditable, Durable)**

**Schema:**

```sql
CREATE TABLE quarantine (
    id SERIAL PRIMARY KEY,
    timestamp TIMESTAMPTZ NOT NULL,
    reason TEXT NOT NULL,
    log_line TEXT NOT NULL,
    reviewed BOOLEAN DEFAULT FALSE
);
```

**Python Insert:**

```python
import psycopg2

conn = psycopg2.connect("dbname=sentinel user=postgres password=secret")
cursor = conn.cursor()

def quarantine_log(log_line, reason):
    entry_time = datetime.utcnow().isoformat() + "Z"
    cursor.execute(
        "INSERT INTO quarantine (timestamp, reason, log_line) VALUES (%s, %s, %s)",
        (entry_time, reason, log_line)
    )
    conn.commit()
    print(f"[QUARANTINE] Stored in PostgreSQL: {reason}")
```

✅ **Postgres is better for long-term auditing** — you can run reports like:

- “How many AWS keys leaked this month?”
    
- “Which agents generated the most HIGH-severity quarantines?”
    

---

## 🚀 **What’s Next?**

We now have:  
✅ **Detection → Redaction → Quarantine → Revocation → Feedback → Pattern Evolution**  
✅ **patterns.yaml** for versioned regex  
✅ **Webhooks** for real-time secret revocation  
✅ **Persistent quarantine store** (Redis or Postgres)

---





## 🛡️ **Expanded System Prompt for Secrets Sentinel**

> **Role & Mission**:  
> You are the **Secrets Sentinel**, a security-focused agent monitoring all log streams for potential leaks of sensitive information (API keys, passwords, tokens, etc.). Your mission: **detect**, **sanitize**, and **prevent** secret exposure while keeping operations secure and auditable.
> 
> **Core Responsibilities**:  
> ✅ Scan **all log entries** for API keys, passwords, JWTs, database strings, and private keys.  
> ✅ **Redact** any detected secrets in-flight before writing them to storage or forwarding.  
> ✅ **Generate structured alerts** for each detection with relevant metadata.  
> ✅ **Quarantine** log lines that contain **high-severity** secrets (so they aren’t distributed further).  
> ✅ Support **continuous learning** by flagging uncertain cases for human/curator review.
> 
> **Secret Detection Targets**:
> 
> - **Cloud Keys** (AWS, GCP, Azure, etc.)
>     
> - **OAuth Tokens** (Bearer, Slack, Discord, GitHub, etc.)
>     
> - **JWTs** (header.payload.signature format)
>     
> - **SSH Private Keys** (`-----BEGIN PRIVATE KEY-----`)
>     
> - **Database Connection Strings** (Postgres, MySQL, MongoDB, etc.)
>     
> - **Generic Passwords** (detected from common prefixes, e.g. `pwd=`, `password:`).
>     
> 
> **Detection Rules**:
> 
> - Use **regex patterns** for known key formats.
>     
> - Score detections with a **confidence metric** (0–1).
>     
> - If a string doesn’t fully match, classify as **LOW confidence** for review.
>     
> 
> **Redaction Policy**:
> 
> - Always redact most of the secret (`AKIA************XYZ`).
>     
> - Never store or transmit the **full secret**.
>     
> 
> **Alert Format (JSON)**:
> 
> ```json
> {
>   "timestamp": "2025-08-02T10:12:34Z",
>   "source_agent": "agent_42",
>   "log_line_id": "hyperlog:134593",
>   "secret_type": "AWS_ACCESS_KEY",
>   "redacted_sample": "AKIA********XYZ",
>   "confidence_score": 0.95,
>   "severity": "HIGH",
>   "recommended_action": "Revoke AWS key immediately and rotate credentials"
> }
> ```
> 
> **Behavior Under Edge Cases**:
> 
> - If unsure: flag as LOW severity with `"recommended_action": "Manual review"`.
>     
> - If a secret is clearly fake (like `TESTKEY123`), still alert but tag as `test_credential: true`.
>     
> 
> **Tone & Style**:
> 
> - Precise, security-minded, and concise in reporting.
>     

---

## 📚 **Regex Patterns Library (Starter Set)**

```python
REGEX_PATTERNS = {
    "AWS_ACCESS_KEY": r"AKIA[0-9A-Z]{16}",
    "AWS_SECRET_KEY": r"(?i)aws(.{0,20})?(?-i)['\"][0-9a-zA-Z\/+]{40}['\"]",
    "GCP_API_KEY": r"AIza[0-9A-Za-z\\-_]{35}",
    "GITHUB_TOKEN": r"gh[pousr]_[0-9A-Za-z]{36}",
    "SLACK_TOKEN": r"xox[baprs]-[0-9A-Za-z-]{10,48}",
    "JWT": r"eyJ[A-Za-z0-9_-]+?\.[A-Za-z0-9._-]+?\.[A-Za-z0-9._-]+",
    "SSH_PRIVATE_KEY": r"-----BEGIN (RSA|DSA|EC|OPENSSH) PRIVATE KEY-----",
    "GENERIC_PASSWORD": r"(?:password|pwd|pass|secret)\s*[:=]\s*['\"]?[^\s'\";]+['\"]?",
    "DB_CONN_STRING": r"(postgres|mysql|mongodb|mssql|redis):\/\/[^\s]+"
}
```

---

## 🛠 **Python Skeleton Implementation**

```python
import re
import json
from datetime import datetime

REGEX_PATTERNS = {
    "AWS_ACCESS_KEY": r"AKIA[0-9A-Z]{16}",
    "AWS_SECRET_KEY": r"(?i)aws(.{0,20})?(?-i)['\"][0-9a-zA-Z\/+]{40}['\"]",
    "GCP_API_KEY": r"AIza[0-9A-Za-z\\-_]{35}",
    "GITHUB_TOKEN": r"gh[pousr]_[0-9A-Za-z]{36}",
    "SLACK_TOKEN": r"xox[baprs]-[0-9A-Za-z-]{10,48}",
    "JWT": r"eyJ[A-Za-z0-9_-]+?\.[A-Za-z0-9._-]+?\.[A-Za-z0-9._-]+",
    "SSH_PRIVATE_KEY": r"-----BEGIN (RSA|DSA|EC|OPENSSH) PRIVATE KEY-----",
    "GENERIC_PASSWORD": r"(?:password|pwd|pass|secret)\s*[:=]\s*['\"]?[^\s'\";]+['\"]?",
    "DB_CONN_STRING": r"(postgres|mysql|mongodb|mssql|redis):\/\/[^\s]+"
}

def redact(secret: str) -> str:
    """Redact a secret leaving only first and last 3 chars."""
    return secret[:4] + "*" * (len(secret) - 7) + secret[-3:]

def scan_log_line(log_line: str, log_id: str, source_agent: str):
    alerts = []
    for secret_type, pattern in REGEX_PATTERNS.items():
        match = re.search(pattern, log_line)
        if match:
            secret = match.group(0)
            alert = {
                "timestamp": datetime.utcnow().isoformat() + "Z",
                "source_agent": source_agent,
                "log_line_id": log_id,
                "secret_type": secret_type,
                "redacted_sample": redact(secret),
                "confidence_score": 0.95,
                "severity": "HIGH" if "PRIVATE_KEY" in secret_type or "AWS" in secret_type else "MEDIUM",
                "recommended_action": "Revoke key/rotate credentials"
            }
            alerts.append(alert)
    return alerts

# Example usage:
log = "User pushed code with AWS key: AKIA1234567890ABCD"
alerts = scan_log_line(log, "hyperlog:42", "agent_7")
print(json.dumps(alerts, indent=2))
```

---

## 🚨 **Optional Extensions**

- ✅ **Automatic Quarantine** → If severity=HIGH, forward to a “quarantine pipeline” (prevent further log distribution).
    
- ✅ **Secret Revocation Hooks** → Webhooks/scripts to auto-disable compromised keys (AWS IAM revoke, GitHub token reset, etc.).
    
- ✅ **Curator Feedback Loop** → If many false positives occur, agents/curators can “vote” on regex quality → improves future detection.
    

---

👉 Do you want me to:

- **📡 Add “quarantine mode” logic** (e.g. isolate log lines and mark them unsafe)?
    
- **🔗 Draft a webhook design** for automatic secret revocation (AWS/GitHub/Slack)?
    
- **🧠 Write a “meta-prompt” for this agent** so it can _learn new secret formats_ over time from curator feedback?














Here’s the **full build-out** with all three requested additions:





## 🛡 **Secrets Sentinel: Extended Prompt**

> **Role & Mission**:
> You are the **Secrets Sentinel**, a security agent tasked with scanning all logs for leaked secrets. You **detect**, **redact**, **quarantine**, and optionally **revoke** compromised credentials. You also **evolve your detection rules** over time by learning from curator and human feedback.
>
> **Extended Responsibilities**:
> ✅ **Quarantine:** When you find a **HIGH severity** secret, isolate the entire log entry from normal processing so it doesn’t spread.
> ✅ **Revocation Hooks:** Trigger a webhook or automation script to disable the compromised key (e.g., AWS IAM revoke).
> ✅ **Adaptive Learning:** If you get “false positive” or “missed secret” feedback, update or request updates to your regex rules and detection logic.

---

### 1️⃣ **Quarantine Mode Logic**

Add this to the **Python skeleton**:

```python
QUARANTINE_STORE = []  # This could be a Redis list, DB table, etc.

def quarantine_log(log_line: str, reason: str):
    """Move a sensitive log line to quarantine for review."""
    quarantine_entry = {
        "timestamp": datetime.utcnow().isoformat() + "Z",
        "reason": reason,
        "log_line": log_line
    }
    QUARANTINE_STORE.append(quarantine_entry)
    print(f"[QUARANTINE] Log quarantined: {reason}")
    return quarantine_entry

def scan_log_line(log_line: str, log_id: str, source_agent: str):
    alerts = []
    for secret_type, pattern in REGEX_PATTERNS.items():
        match = re.search(pattern, log_line)
        if match:
            secret = match.group(0)
            severity = "HIGH" if "PRIVATE_KEY" in secret_type or "AWS" in secret_type else "MEDIUM"
            alert = {
                "timestamp": datetime.utcnow().isoformat() + "Z",
                "source_agent": source_agent,
                "log_line_id": log_id,
                "secret_type": secret_type,
                "redacted_sample": redact(secret),
                "confidence_score": 0.95,
                "severity": severity,
                "recommended_action": "Revoke key/rotate credentials"
            }
            alerts.append(alert)
            if severity == "HIGH":
                quarantine_log(log_line, f"High severity secret detected: {secret_type}")
    return alerts
```

➡ **Now, any HIGH-severity find triggers quarantine.**

---

### 2️⃣ **Webhook Design for Secret Revocation**

We’ll use a **simple webhook dispatcher** that calls different revocation endpoints depending on the secret type.

```python
import requests

REVOCATION_HOOKS = {
    "AWS_ACCESS_KEY": "https://security.example.com/hooks/aws-revoke",
    "GITHUB_TOKEN": "https://security.example.com/hooks/github-revoke",
    "SLACK_TOKEN": "https://security.example.com/hooks/slack-revoke"
}

def trigger_revocation(secret_type: str, redacted_sample: str):
    """Send webhook request to revoke compromised credentials."""
    if secret_type in REVOCATION_HOOKS:
        payload = {
            "secret_type": secret_type,
            "sample": redacted_sample,
            "reason": "Detected secret leak"
        }
        try:
            r = requests.post(REVOCATION_HOOKS[secret_type], json=payload, timeout=5)
            if r.status_code == 200:
                print(f"[REVOCATION] Successfully triggered revocation for {secret_type}")
            else:
                print(f"[REVOCATION] Failed revocation for {secret_type}: {r.status_code}")
        except Exception as e:
            print(f"[REVOCATION ERROR] {e}")
```

Then, in the alert loop:

```python
if severity == "HIGH":
    quarantine_log(log_line, f"High severity secret detected: {secret_type}")
    trigger_revocation(secret_type, redact(secret))
```

➡ **Now, if the sentinel finds an AWS key or GitHub token, it can hit the right webhook to revoke it immediately.**

---

### 3️⃣ **Meta-Prompt for Learning New Secret Formats**

This allows the Sentinel to **expand its detection library** dynamically.

---

**🧠 Adaptive Learning Meta-Prompt**

> **Role**: You are the “Meta-Learner” function of Secrets Sentinel.
>
> **Mission**: Continuously expand the Sentinel’s knowledge of new secret formats and detection rules.
>
> **Responsibilities**:
>
> * Accept **feedback reports** from curators or human reviewers (false positives, missed secrets).
> * If multiple missed secrets share a pattern, propose a **new regex** (or modify an existing one).
> * Version-control detection rules (e.g., store regex patterns in a JSON or YAML file with version numbers).
> * Generate a **confidence score** for new rules before promoting them to active use.
> * Flag uncertain cases for human approval.
>
> **Behavior**:
>
> * If false positives keep happening for a regex → weaken or add exception clauses.
> * If missed secrets are reported → extract examples, infer format, draft new regex, test on past logs.
>
> **Output**:
>
> ```json
> {
>   "action": "add|update|remove",
>   "regex_name": "NEW_PROVIDER_KEY",
>   "regex_pattern": "XXX",
>   "confidence": 0.87,
>   "status": "pending human review"
> }
> ```
>
> **Goal**: Turn curator/human feedback into a **self-evolving secret-detection engine**.

---

### 🧩 How It All Fits

✅ **Secrets Sentinel core** = Detect + Redact + Quarantine
✅ **Revocation Hooks** = Automated security response
✅ **Meta-Learning** = Regex patterns evolve over time


---

## 📜 **1️⃣ Migration Script: Redis → PostgreSQL**

This script will migrate existing quarantined log entries from **Redis** to **Postgres**.

```python
import redis, json, psycopg2
from datetime import datetime

# Redis config
r = redis.Redis(host='localhost', port=6379, decode_responses=True)

# Postgres config
conn = psycopg2.connect("dbname=sentinel user=postgres password=secret")
cursor = conn.cursor()

def migrate_quarantine():
    count = 0
    while True:
        entry_json = r.rpop("quarantine")  # pop oldest entry from Redis
        if not entry_json:
            break
        entry = json.loads(entry_json)
        cursor.execute(
            "INSERT INTO quarantine (timestamp, reason, log_line) VALUES (%s, %s, %s)",
            (entry["timestamp"], entry["reason"], entry["log_line"])
        )
        count += 1
    conn.commit()
    print(f"[MIGRATION] Moved {count} quarantined entries from Redis → PostgreSQL")

if __name__ == "__main__":
    migrate_quarantine()
```

✅ **Run once** after Postgres is set up — empties Redis queue into the durable DB.

---

## 🖥 **2️⃣ Admin Dashboard Spec**

**Purpose:** A web UI to manage the Sentinel’s security pipeline.

---

### 🎯 **Core Features**

✅ **Quarantine Browser**

- Paginated view of all quarantined logs
    
- Search/filter by `secret_type`, `source_agent`, `date`, `status`
    
- Mark quarantined logs as **reviewed** or **false alarm**
    

✅ **Regex Rules Manager**

- Lists all regexes from `patterns.yaml`
    
- Add / update / deactivate rules via UI
    
- Shows `pending_updates` flagged by the Meta-Learner for human approval
    

✅ **Revocation Status Board**

- See which secrets triggered revocations
    
- Status of revocation hooks (success/fail)
    

✅ **Metrics Dashboard**

- Charts: “Secrets Detected Over Time”, “Top Sources of Leaks”
    
- KPIs: # HIGH severity secrets this month, # rules updated, # false positives
    

---

### 🏗 **Tech Stack Suggestion**

- **Backend:** FastAPI (Python)
    
- **Frontend:** React + Tailwind
    
- **DB:** PostgreSQL for quarantine + rules history
    
- **Auth:** OAuth (GitHub/Google) + RBAC (only security admins can approve regex changes)
    

---

### 🔌 **Endpoints**

```
GET  /api/quarantine         → list quarantined entries
POST /api/quarantine/review  → mark entry as reviewed
GET  /api/rules              → list regex patterns
POST /api/rules/update       → update or add a regex
GET  /api/revocations        → list revocation events
```

---

### 🖥 **Mock Dashboard Layout**

- **Left Nav:** Quarantine | Rules | Revocations | Metrics
    
- **Main Panel:**
    
    - Data tables with sorting/filtering
        
    - Inline editors for regex rules
        
    - Approve/Reject buttons for pending regex updates
        

✅ Basically a **security control room** for Sentinel.

---

## 🤖 **3️⃣ Meta-Curator AI Prompt**

This agent reviews Sentinel’s work and **tunes it automatically**.

---

### **Meta-Curator: System Prompt**

> **Role & Mission:**  
> You are the **Meta-Curator**, a supervisory AI responsible for reviewing the **Secrets Sentinel’s** detections, regex updates, and feedback reports.
> 
> **Core Responsibilities:**  
> ✅ **Audit alerts** – Look for false positives, duplicates, or missed leaks by cross-checking Sentinel outputs.  
> ✅ **Review regex proposals** – When Sentinel drafts new regex rules, decide if they’re:
> 
> - ✅ Approved (safe to activate)
>     
> - ❌ Rejected (too broad or incorrect)
>     
> - 🕒 Deferred (needs human review)  
>     ✅ **Tune detection thresholds** – Adjust `confidence` or `severity` on patterns based on outcomes.  
>     ✅ **Generate new rules** – If multiple missed secrets share a format, draft a regex and submit to humans for approval.  
>     ✅ **Report upstream** – Summarize changes to security admins weekly.
>     

---

### **Behavior Guidelines**

- **Conservative by default:** Don’t auto-approve regexes unless confidence > 0.95.
    
- **Keep auditability:** Every decision (approve/reject) is logged in the hyperlog.
    
- **Respect human overrides:** Never overwrite a regex that a human explicitly locked.
    

---

### **Example Meta-Curator Output**

```json
{
  "action": "approve_regex",
  "regex_name": "GITLAB_TOKEN",
  "regex_pattern": "glpat-[0-9A-Za-z\\-_]{20}",
  "confidence": 0.97,
  "decision_reason": "Validated against 12 quarantined examples, no false positives found.",
  "timestamp": "2025-08-02T13:45:00Z"
}
```

✅ This meta-agent is the **brains of the rules layer** — keeps Sentinel evolving, but under control.

---

## 🚀 **Now You Have:**

✅ **Migration Path** → Redis → PostgreSQL  
✅ **Admin Dashboard Spec** → complete with endpoints & layout  
✅ **Meta-Curator Prompt** → the agent that “manages the manager”

---