This article explains how the vulnerability works, how to set up a safe lab environment, and how to exploit it using a proof-of-concept script.
Recently, MongoDB disclosed a critical security vulnerability that security researchers quickly dubbed “MongoBleed” in reference to its similarity to the infamous Heartbleed vulnerability that affected OpenSSL years earlier. Just as Heartbleed allowed attackers to extract memory from vulnerable web servers, MongoBleed enables unauthenticated attackers to leak sensitive data from MongoDB server memory without any credentials or authentication.
In this article, we will briefly discuss NoSQL databases, explore the origins of MongoBleed, and finally walk through the exploitation process in a lab environment. Let’s get rolling!
What is NoSQL Databases?
Before diving into the vulnerability itself, it is essential to have some understanding of databases in general and what MongoDB is.
Relational databases (RDBMS), such as MySQL, are very common, and at Hackers-Arise, you can find a set of articles covering how they might be hacked. However, when an application needs to handle large amounts of data with high speed and reliability, developers may need a different solution. This is where NoSQL databases come in.
NoSQL systems like MongoDB offer an alternative to traditional SQL databases. They are popular today because they are easy to use, scale well both horizontally and vertically, and provide flexible data storage. Unlike relational databases, NoSQL does not force data into fixed tables and rows. Instead, developers can store data in the format that best suits their needs.
NoSQL databases come in four main types, as shown on the image below.
Among them, document databases are the most widely used. They store data in document format, making it easy to search and structure. In document databases, a “document” replaces a table row, and a “collection” replaces a table. MongoDB also a document database that stores data as flexible BSON (Binary JSON) documents.
Understanding the Vulnerability
MongoBleed takes advantage of a flaw in how MongoDB’s network layer processes compressed messages. To understand it fully, we need to look at how the MongoDB wire protocol works, how zlib compression fits into it, and where the vulnerability appears in that process.
MongoDB Wire Protocol Basics
MongoDB clients and servers communicate using a binary protocol that exchanges messages over TCP connections. Each message consists of a header containing metadata like message length and operation type, followed by the actual message body containing the command or response data. When compression is enabled, this body section gets compressed before transmission and must be decompressed by the receiver before processing.
The wire protocol header includes a field indicating the total message length, which the receiver uses to know how much data to read from the network socket. For compressed messages, there’s an additional header containing information about the compression algorithm used and the claimed uncompressed size of the data. This uncompressed size field is important to understanding the vulnerability, as it tells MongoDB how much memory to allocate for holding the decompressed data.
How Zlib Compression Works
Zlib is a widely-used compression library that implements the DEFLATE algorithm. Simplified DEFLATE algorithm is shown below.
When MongoDB enables zlib compression, outgoing messages get compressed before transmission and incoming compressed messages get decompressed upon receipt. The compression process reduces the network bandwidth required for communication, which can significantly improve performance when clients and servers communicate over limited or high-latency networks.
The decompression process requires allocating a buffer large enough to hold the uncompressed data. The compressed data includes information about how much space the uncompressed form will require, and MongoDB reads this value to allocate an appropriately sized buffer. The zlib decompression function then writes the decompressed data into this buffer, returning a value indicating how many bytes were actually written.
If you struggle to understand how compression works, consider checking our Cryptography Basics for Hackers training.
The Vulnerability Mechanism
An attacker crafts a malicious MongoDB wire protocol message that claims an unrealistically large uncompressed size. For example, they might send a message whose compressed payload is only 100 bytes but claims it will decompress to 50,000 bytes. MongoDB, trusting this claim, allocates a 50,000-byte buffer to hold the decompressed data.
The zlib library then decompresses the actual 100 bytes of compressed data, which expands to perhaps 500 bytes of uncompressed data. Zlib writes these 500 bytes to the beginning of the 50,000-byte buffer and returns a value indicating that it wrote 500 bytes. However, due to the bug in MongoDB’s implementation, the server doesn’t properly verify this return value against the claimed uncompressed size. Instead, it treats the entire 50,000-byte buffer as if it contains valid decompressed data.
When MongoDB then parses this buffer as BSON, the parser reads field names and values sequentially through the buffer. It successfully parses the first 500 bytes of legitimate decompressed data, but then continues reading into the remaining 49,500 bytes of uninitialized memory. In C and C++ programming, uninitialized memory contains whatever data happened to be there from previous operations rather than being zeroed out. This memory space might contain fragments of previous MongoDB operations, other clients’ queries, configuration data, or any other information that recently resided in that memory region.
The BSON parser continues reading through this uninitialized memory region, interpreting random bytes as field names until it encounters null bytes (0x00) which mark the end of field names in the BSON format. By carefully choosing different claimed uncompressed sizes in successive exploitation attempts, an attacker can probe different regions of memory, extracting varying chunks of data and slowly reconstructing complete sensitive information.
Affected Versions
The MongoBleed vulnerability affects a very broad range of MongoDB Server releases, covering almost a decade of versions. It impacts MongoDB 8.2.0 through 8.2.2, 8.0.0 through 8.0.16, 7.0.0 through 7.0.27, 6.0.0 through 6.0.26, 5.0.0 through 5.0.31, 4.4.0 through 4.4.29, as well as all releases in the 4.2.x, 4.0.x, and 3.6.x series. In simple terms, any deployment running a version released since mid-2017 may be at risk if it has not been updated.
The issue affects both Community and Enterprise editions and applies to environments running on-premises, in virtual machines, containers, or in the cloud. As long as the server has zlib compression enabled and is reachable over the network, it remains vulnerable.
MongoDB has issued fixes for all currently supported branches. Older versions such as 4.2, 4.0, and 3.6 no longer receive patches.
The Exploitation
To exploit the MongoBleed vulnerability, there are several proof-of-concept implementations available in different programming languages. One useful example is Joe Desimone’s PoC, which also includes a Docker Compose file that lets you quickly spin up a vulnerable MongoDB environment for testing.
To begin, clone the repository using the following command:
kali> git clone https://github.com/joe-desimone/mongobleed.git
By reviewing the mongobleed script, we can see how it generates malformed compressed BSON messages and attempts to capture memory bytes that the server unintentionally leaks.
To test the PoC, we’ll first set up a vulnerable MongoDB instance:
kali> docker-compose up -d
By checking the running Docker containers, we can see that mongobleed-target is active and listening on the default MongoDB port.
kali> sudo docker ps | grep mongo
Let’s run the exploit on it:
kali> python3 mongobleed.py –host localhost
This initial scan probed memory offsets from 20 to 8192. The exploit works by creating BSON documents with artificially large length fields. When MongoDB processes these documents, it reads field names from uninitialized memory until it encounters a null byte. Using different offsets gives access to different memory regions.
The leaked data can include internal MongoDB logs and state information, WiredTiger configuration details, system /proc data such as memory and network stats, file paths from inside the Docker container, and even connection UUIDs and client IP addresses.
To gather more information, we can run a deeper scan:
kali> python3 mongobleed.py –host localhost –max-offset 50000
According to Shodan, there are nearly 214,000 hosts running MongoDB.
However, it’s important to remember that many of these systems are already patched, and some do not use zlib compression at all, which makes MongoBleed ineffective against them.
Summary
MongoBleed is one of the most serious MongoDB vulnerabilities discovered in recent years, affecting almost ten years of server releases. Tracked as CVE-2025-14847, it carries a CVSS score between 7.5 and 8.7, depending on the scoring system. Its impact is severe because it requires no login, is easy to exploit over the network, and affects MongoDB versions from 3.6 up through 8.2.
In this article, we walked through the vulnerability, demonstrated how it can be exploited in a lab setup, and highlighted the potential attack surface it exposes.
Source: HackersArise
Source Link: https://hackers-arise.com/database-hacking-get-started-with-mongobleed-vulnerability/