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The vulnerability resides within the application programming interface blueprint implementation of the pyLoad download manager application.
Specifically, the multipart file upload handling routine located inside the API blueprint source file reads entire uploaded file payloads directly into the system random-access memory.
This operation is executed synchronously via the file read method before any validation, chunking, or streaming mechanisms can process the incoming data stream.
Because the underlying endpoint logic lacks any enforcement of maximum content length or file size boundaries during this initial ingestion phase, an attacker can supply arbitrarily large files.
When a remote authenticated user or client transmits an exceptionally large file via the multipart form upload vector, the server attempts to allocate sufficient memory blocks to hold the entire file payload.
This excessive memory consumption rapidly exhausts the available RAM and swap space of the host operating system running the pyLoad instance.
As a direct consequence of this uncontrolled resource allocation, the operating system kernel intervenes to preserve system stability by terminating the offending pyLoad worker process via its out-of-memory killer mechanism.
Alternatively, severe resource starvation can cause the entire host system to become entirely unresponsive due to aggressive memory swapping and CPU thrashing.
This denial of service condition disrupts all active background tasks, ongoing file downloads, and management sessions handled by the application daemon.
Remediation requires enforcing strict file size thresholds at both the reverse proxy layer and application handlers to prevent unbounded memory allocation during multipart stream processing.
DailyCVE Form:
Platform: pyLoad
Version: v0.5.0b96 and prior
Vulnerability: Memory Exhaustion DoS
Severity: Critical
date: March 2026
Prediction: Patched in v0.5.0b97
What Undercode Say:
To analyze and reproduce the memory exhaustion behavior in a controlled lab environment, use the following bash commands and Python environment setups.
Clone the vulnerable pyLoad repository branch git clone https://github.com/pyload/pyload.git cd pyload git checkout 8e447958b8a66c5899775e725a8b90bce6643004 Create a massive dummy file for testing memory exhaustion truncate -s 10G large_file.bin Check available system memory before testing free -h
Exploit: (Educational Purposes!)
Send a multipart HTTP POST request containing a 10GB file payload to exhaust server memory curl -X POST "http://localhost:8000/api/rpc" \ -H "X-API-Key: YOUR_API_KEY" \ -F "func=check_online_status_container" \ -F "container=@large_file.bin"
Protection:
Implement strict upload size limitations within Nginx reverse proxy configuration
server {
listen 80;
server_name pyload.local;
client_max_body_size 50M;
location / {
proxy_pass http://127.0.0.1:8000;
proxy_set_header Host $host;
proxy_set_header X-Real-IP $remote_addr;
}
}
Impact:
Denial of Service (DoS): The pyLoad service process is forcefully terminated by the operating system kernel out-of-memory killer due to complete RAM exhaustion.
System Instability: Host-wide unresponsiveness can occur from excessive memory swapping and resource starvation.
Operational Interruption: All ongoing file downloads, active user sessions, and background automation tasks managed by the application are abruptly terminated.
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Sources:
Reported By: github.com
Extra Source Hub:
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