## https://sploitus.com/exploit?id=6F391413-8683-5F0E-97B0-BE868550D164
# CVE-2025-14847: MongoBleed Laboratory
## Table of Contents
1. [Introduction](#introduction)
2. [Vulnerability Details](#vulnerability-details)
- [How it Works](#how-it-works)
3. [Impact](#impact)
4. [Lab Architecture](#lab-architecture)
5. [Prerequisites](#prerequisites)
6. [Installation and Usage](#installation-and-usage)
- [1. Start the Environment](#1-start-the-environment)
- [2. Install Dependencies](#2-install-dependencies)
- [3. Verify Lab Setup (Optional)](#3-verify-lab-setup-optional)
- [4. Run the Exploit](#4-run-the-exploit)
7. [Exploitation Walkthrough](#exploitation-walkthrough)
8. [Remediation](#remediation)
9. [License](#license)
10. [Disclaimer](#disclaimer)
11. [Author](#author)
## Introduction
This laboratory is designed to reproduce and analyze **MongoBleed** (CVE-2025-14847), a critical vulnerability in MongoDB. This flaw allows unauthenticated attackers to read sensitive data from the server's memory due to improper handling of compressed messages.
The environment includes a vulnerable MongoDB instance populated with dummy sensitive data (PII, API keys, financial records) to demonstrate the severity of the leak.
## Vulnerability Details
**CVE ID**: CVE-2025-14847
**Name**: MongoBleed
**Component**: Wire Protocol (OP_COMPRESSED)
**Vulnerable Versions**: MongoDB 6.0.x [**NVD CVE-2025-14847**](https://nvd.nist.gov/vuln/detail/CVE-2025-14847)
### How it Works
The vulnerability resides in the way MongoDB handles `OP_COMPRESSED` messages using the `zlib` compression algorithm.
1. **Size Mismatch**: An attacker sends a compressed message where the `uncompressed_size` field in the header is intentionally set to a value much larger than the actual decompressed data size.
2. **Memory Allocation**: The server allocates a memory buffer based on this inflated `uncompressed_size`.
3. **Partial Write**: The `zlib` decompressor writes the actual (small) payload to the beginning of this buffer. The rest of the buffer remains **uninitialized**, containing residual data from previous operations (RAM artifacts).
4. **The Leak**: When the server attempts to parse this buffer as a BSON document, it reads past the valid data into the uninitialized memory. If the parser encounters an error (which is likely), it may return the "bad" data in the error message to the client.
## Impact
- **Unauthenticated Access**: The attack does not require valid credentials.
- **Information Disclosure**: Attackers can extract anything currently in the MongoDB process memory, including:
- Authentication credentials (cleartext passwords or hashes).
- Data from other databases/collections.
- Server configuration and environment variables.
- Active session tokens.
## Lab Architecture
The lab consists of:
- **Vulnerable Service**: MongoDB 6.0.10 (Docker container).
- **Authentication**: Enabled (`admin` / `secretpassword`).
- **Data Seeding**: An initialization script (`init-mongo.js`) that populates 4 distinct databases to simulate a real environment:
- **sensitive_db**: Core application data (Users, API Keys, Financial Transactions).
- **legacy_crm**: Old customer data and classified archives (e.g., "Top Secret" docs).
- **internal_logs**: System events, error logs, and admin activity.
- **session_store**: Active user sessions and tokens.
- **Exploit**: A Python script (`exploit.py`) implementing the reverse-engineered protocol attack.
## Prerequisites
- Docker
- Docker Compose
- Python 3
## Installation and Usage
### 1. Start the Environment
Launch the vulnerable container. This will automatically create the `sensitive_db` and populate it with data.
```bash
docker-compose up -d
```
*Wait about 10-15 seconds for the database to initialize and load the data.*
**Note:** If you have run this lab before, ensure you reset the volume to load the latest data structure:
```bash
docker-compose down -v
docker-compose up -d
```
### 2. Install Dependencies
You can install the required dependencies using `pip` with the legacy `requirements.txt` or the modern `pyproject.toml`.
**Option A: Using requirements.txt (Standard)**
```bash
pip install -r requirements.txt
```
**Option B: Using pyproject.toml (Modern)**
This will install the project and its dependencies in the current environment.
```bash
pip install .
```
### 3. Verify Lab Setup (Optional)
We have provided a verification script to ensure the database is reachable and the data has been seeded correctly.
```bash
python verify_lab.py
```
*This script uses the admin credentials to check the existence of databases like `sensitive_db`, `legacy_crm`, etc.*
### 4. Run the Exploit
Execute the Python script to attack the server. **No credentials are required** for this step, demonstrating the unauthenticated nature of the vulnerability.
```bash
python exploit.py --host localhost --port 27017 --min 100 --max 5000
```
## Exploitation Walkthrough
The script performs the following steps:
1. Constructs a malicious BSON payload.
2. Compresses it and wraps it in an `OP_COMPRESSED` header with a faked, inflated size.
3. Sends it to the target server.
4. Listens for error responses.
5. Prints any readable text found in the server's response (which comes from the memory leak).
**Expected Output:**
You should see output indicating "Potential leak". Look for strings like:
- `sensitive_db`
- `Juan Perez`
- `AKIAIOSFODNN7EXAMPLE` (Leaked AWS Key)
- `sk_live_...`
- `legacy_crm`
```text
[*] Target: localhost:27017
[*] Scanning offsets 100-5000
[+] Offset 117: Found potential leak in error message
Raw: ... sensitive_db ... users ... Juan Perez ...
```
## Remediation
To fix this vulnerability in production environments:
1. **Upgrade**: Update MongoDB to a patched version (e.g., 6.0.27+, 7.0.28+, 8.0.17+).
2. **Network Restrictions**: Ensure MongoDB ports (27017) are not exposed to the public internet.
## License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
## Disclaimer
This material is for **educational and research purposes only**. Do not use this exploit on systems you do not own or have explicit permission to test. **The author is not responsible for any misuse of this information or tool.**
## Author
Joseph Meneses (ElJoamy)
Backend and AI Developer · Cybersecurity Engineer · DBA · Penetration Tester