Overview

In late 2025, a high-severity memory information disclosure vulnerability that had been lurking in MongoDB for years was finally revealed. Dubbed MongoBleed, this flaw allows unauthenticated attackers to read uninitialized heap memory, potentially exposing sensitive information. The U.S. Cybersecurity and Infrastructure Security Agency (CISA) has added this vulnerability to its Known Exploited Vulnerabilities (KEV) catalog, signaling evidence of active exploitation and urging immediate remediation. 

This article breaks down the root cause of MongoBleed (CVE-2025-14847), explains the attack flow, explores why it remained undiscovered for eight years, and provides guidance on mitigation strategies.

 

Technical Background

1. MongoDB Wire Protocol and Message Compression

MongoDB uses its proprietary binary protocol, the MongoDB Wire Protocol, for client-server communication instead of HTTP. Historically, it relied on various opcodes such as OP_QUERY and OP_INSERT, but starting with MongoDB 5.1, most operations were consolidated under OP_MSG. This opcode (OP_MSG) provides an extensible message format that transmits payloads in BSON format.

In 2017, with MongoDB 3.6, zlib-based message compression was introduced to reduce network traffic. MongoDB supports three compression algorithms: snappy, zlib, and zstd. During the handshake process, the client and server negotiate which algorithm to use. When compression is enabled, the original message is wrapped and transmitted as an OP_COMPRESSED message.

An OP_COMPRESSED message contains a MsgHeader (16 bytes), originalOpcode (4 bytes), uncompressedSize (4 bytes), compressorId (1 byte), and the compressed payload. Because the uncompressedSize field is trusted without validation, directly using this value can lead to allocating a memory buffer larger than the actual data.

 

2. BSON Format and Parsing Mechanism

BSON (Binary JSON) is MongoDB’s native data format, which serializes JSON-like documents into a binary representation. Field names (element names) are expressed as null-terminated strings (cstring).

The MongoDB server parses BSON data sequentially in memory. The parser first reads the document’s total size, then iterates through each field. For every field, it checks the type byte and then reads the field name until it encounters a null terminator. If the parser encounters an unexpected data structure during this process, MongoDB halts parsing and returns an error. The error message may include the name of the problematic field.

 

Cause of CVE-2025-14847

The MongoBleed vulnerability arises from a length-handling flaw in the ZlibMessageCompressor::decompressData() function within src/mongo/transport/message_compressor_zlib.cpp, combined with how BSON parsing behaves. Let’s examine each contributing issue.

 

1. decompressData

This function is responsible for inflating compressed data when an OP_COMPRESSED message is received. 

It takes two parameters: 

• input: a ConstDataRange object holding the compressed data.
• output: a DataRange object serving as the buffer for the decompressed data.

The function first declares a length variable and initializes it with output.length(). Here, output.length() returns the total allocated size of the output buffer. It then calls zlib’s uncompress() function to perform the actual decompression.

The uncompress() function has the signature: int uncompress(Bytef *dest, uLongf *destLen, const Bytef *source, uLong sourceLen). The destLen parameter is an in-out parameter: before the call, it represents the allocated size of the dest buffer; after the call, it is updated to the actual size of the decompressed data.

The core flaw lies in the handling of the function’s return value. The decompressData() function returns the value output.length(), which is the originally allocated buffer size, instead of the length value updated by uncompress().

 

2. BSON Parsing and Memory Leak

If decompressData() returns an incorrect size, the server treats the contents of an oversized buffer—which may include uninitialized memory—as valid data. An attacker can manipulate the uncompressedSize field of an OP_COMPRESSED message to trick the server into allocating a buffer larger than the actual decompressed data.

Under normal conditions, a field name ends with a null terminator within the valid data. However, if the returned buffer size is wrong, the parser may read past the legitimate data boundary into uninitialized memory. This uninitialized region can contain residual strings/fragments previously present on the heap, which the parser will attempt to interpret as a field name.

If the parser happens to encounter a null byte in the uninitialized memory, it interprets all bytes up to that point as the field name. Since the BSON structure is invalid, parsing fails, and MongoDB generates an error message containing the leaked memory content. By repeatedly triggering such errors and collecting the responses, an attacker can harvest sensitive information from server memory.

 

Attack Scenario

If an attacker targets a vulnerable MongoDB instance, data leakage can occur as illustrated in [Figure 4]. The attacker sends a crafted packet, an OP_COMPRESSED message using zlib compression, with abnormal length and header values without authentication. The server processes this packet during the pre-authentication stage, invoking the decompression logic. Due to the mismatch between the header’s length information and the actual decompressed size, an error condition arises where the server uses the allocated buffer size instead of the actual data length for subsequent operations.

As a result, the server treats memory beyond the valid data length as part of the message. This leftover space may contain uninitialized heap fragments, which then get mixed into the response path and exposed to the client. While each leak may only reveal small fragments, repeated exploitation attempts can yield sensitive information such as tokens, keys, or credentials in partial form.

In fact, in late December 2025, a major online gaming service provider experienced a security incident involving account anomalies and service disruptions. Some reports and security community analyses suggested that MongoBleed (CVE-2025-14847) exploitation was among the possible root causes.

 

Why This Vulnerability Went Undetected for So Long

The primary reason MongoBleed remained undiscovered for years lies in its highly non-deterministic nature. Even when identical input is provided, the leaked output can vary significantly. This type of memory disclosure depends on factors such as heap layout, allocation and deallocation timing, and the memory state influenced by workload. Because of this variability, reproducing the issue consistently is extremely difficult, making it hard to detect through automated testing or routine failure analysis.

Operational visibility was also limited. MongoDB’s default logging configuration (verbosity=0) focuses on informational logs. For assertion or command-related errors to appear in system logs, verbosity must be set to at least 1 (Debug). Without this configuration, attack traffic leaves no detailed trace, and incidents may appear as simple connection drops or transient errors rather than indicators of a deeper problem.

Another factor is that the vulnerability can be triggered before authentication and the resulting error response is returned within a normal protocol flow. This makes it difficult to distinguish using signature-based detection or simple blocking rules, further reducing the likelihood of discovery during standard monitoring or intrusion detection processes.

 

Mitigation Strategies

The most effective way to address the MongoBleed vulnerability is to upgrade immediately to a patched version. However, if an immediate update is not feasible for operational reasons, several temporary mitigation measures can be applied.

First, ensure that MongoDB instances are not directly exposed to the internet. Network access should be minimized using firewalls, ACLs, or VPC configurations. Since this vulnerability exploits the zlib-based OP_COMPRESSED processing path, disabling zlib compression is another critical step. This can be done by removing zlib from the allowed compression algorithms in the configuration file, effectively blocking zlib-compressed messages from being processed.

From a logging perspective, the default configuration (verbosity=0) may not provide sufficient clues about parsing errors. To improve visibility, increase the verbosity level for the COMMAND component to at least 1. This ensures that indicators such as InvalidBSON or Assertion while parsing command are captured in system logs, making it easier to detect abnormal parsing failures.

 

AhnLab Response Status

Detection names for AhnLab products is as follows.

 

AIPS/HIPS Detection Rule

• MongoDB zlib Decompression Information Disclosure Vulnerability (MongoBleed)-1 

 

Conclusion

MongoBleed (CVE-2025-14847) is a striking example of how a single line of faulty length handling logic can accumulate over time and lead to widespread risk. Public reports and scanning results indicated that, at the time of disclosure, approximately 87,000 Internet-exposed instances were mentioned as potentially vulnerable.

MongoDB users should prioritize applying the official patch immediately. If that is not possible, they must block network exposure, disable zlib compression, and strengthen log visibility as interim measures. Security professionals should study cases like this to proactively identify and prevent similar vulnerabilities, while software developers must remember the principle that security takes precedence over functionality.

A detailed technical analysis of this vulnerability is available in the “MongoBleed Vulnerability Analysis Report (CVE-2025-14847) – AhnLab TIP” provided by AhnLab ATIP.

 

Source

• https://nvd.nist.gov/vuln/detail/CVE-2025-14847
• https://github.com/mongodb/mongo/blob/r8.2.2/src/mongo/transport/message_compressor_manager.h
• https://www.abstract.security/blog/critical-mongodb-vulnerability-cve-2025-14847-mongobleed
• https://www.akamai.com/blog/security-research/cve-2025-14847-all-you-need-to-know-about-mongobleed
• https://censys.com/advisory/cve-2025-14847