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CVE-2026-33992

CRITICAL

pyLoad: Server-Side Request Forgery via Download Link Submission Enables Cloud Metadata Exfiltration

Published March 27, 2026Updated June 29, 2026Source: osv

Summary

## Summary PyLoad's download engine accepts arbitrary URLs without validation, enabling Server-Side Request Forgery (SSRF) attacks. An authenticated attacker can exploit this to access internal network services and exfiltrate cloud provider metadata. On DigitalOcean droplets, this exposes sensitive infrastructure data including droplet ID, network configuration, region, authentication keys, and SSH keys configured in user-data/cloud-init. ## Details The vulnerability exists in PyLoad's download package functionality (`/api/addPackage` endpoint), which directly passes user-supplied URLs to the download engine without validating the destination. The affected code in `src/pyload/webui/app/blueprints/api_blueprint.py`: ```python @bp.route("/addPackage", methods=["POST"], endpoint="add_package") @login_required def add_package(): name = flask.request.form["add_name"] links = flask.request.form["add_links"].split("\n") # ... validation omitted ... api.add_package(name, links, dest) # No URL validation ``` The download engine in `src/pyload/core/managers/download.py` accepts any URL scheme and initiates HTTP requests to arbitrary destinations, including internal network addresses and cloud metadata endpoints. ## Proof of Concept **Live Demo Instance:** http://143.244.141.81:8000 **Credentials:** `pyload` / `pyload` - Login into the pyload application - Navigate to package tab and enter the package name and fill the Link section with the following URL ``` http://169.254.169.254/metadata/v1.json ``` <img width="1851" height="786" alt="image" src="https://github.com/user-attachments/assets/18e7aedf-7663-4a57-8f3e-5200be2c958e" /> - Now navigate to Files section and download the link. <img width="1429" height="870" alt="image" src="https://github.com/user-attachments/assets/9b8b9cd6-afb7-461c-b058-a3cc4f26e2e6" /> - It was observed that we are able to Read the Digital Ocean Metadata <img width="1872" height="837" alt="image" src="https://github.com/user-attachments/assets/d30d2d74-53e9-46f8-8206-894a275ac831" /> The downloaded `v1.json` file contains sensitive cloud infrastructure data: - **Droplet ID**: Unique identifier for the instance - **Network Configuration**: Public/private IP addresses, VPC topology - **Authentication Keys**: Cloud provider auth tokens - **SSH Keys**: Public keys configured in droplet metadata - **Region and Datacenter**: Infrastructure location ## Impact **Vulnerability Type:** Server-Side Request Forgery (SSRF) **CVSS Score:** 7.7 - 9.1 (High to Critical, depending on cloud deployment) ### Affected Systems - All PyLoad installations (version 0.5.0 and potentially earlier) - **Critical Impact** on cloud deployments (AWS EC2, DigitalOcean, Google Cloud, Azure) where metadata contains: - IAM credentials (AWS) - SSH private keys (configured in user-data) - API tokens and secrets - Database credentials stored in cloud-init ### Attack Requirements - Valid PyLoad user account (any role - ADMIN or USER) - Network connectivity to PyLoad instance ### Security Impact 1. **Cloud Metadata Theft**: Complete exfiltration of instance metadata 2. **Lateral Movement**: Discovery and enumeration of internal network services 3. **Credential Exposure**: Theft of cloud IAM credentials, SSH keys, API tokens 4. **Infrastructure Mapping**: Network topology, IP addressing, service discovery ## Remediation Implement URL validation in the download engine: 1. Whitelist allowed URL schemes (http/https only) 2. Block requests to private IP ranges (RFC 1918, link-local addresses) 3. Block cloud metadata endpoints (169.254.169.254, metadata.google.internal, etc.) 4. Implement request destination validation before initiating downloads

Affected Packages (1)

PackageEcosystemAffectedFixed In
pyload-ng
pypi
0.5.0a5.dev528, 0.5.0a5.dev532, 0.5.0a5.dev535, 0.5.0a5.dev536 (+97 more)Range-based data available

Vulnerability Classification

Common Weakness Enumeration (CWE) identifiers for this vulnerability type.

  • CWE-918
    Server-Side Request Forgery (SSRF)MITRE

CVSS Score Breakdown

What the CVSS (Common Vulnerability Scoring System) 9.6 score means for each attack dimension.

Attack Vector
Network
Attack Complexity
Low
Privileges Required
Low
User Interaction
None
Scope
Confidentiality
Integrity
Availability

CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:N/SC:H/SI:H/SA:N

Frequently Asked Questions

What is CVE-2026-33992?
pyLoad: Server-Side Request Forgery via Download Link Submission Enables Cloud Metadata Exfiltration This vulnerability has been assigned a severity rating of CRITICAL (CVSS score: 9.6/10).
How do I check if my project is affected by CVE-2026-33992?
CVE-2026-33992 affects pyload-ng. Use GeekWala's free vulnerability scanner to check your dependencies against CVE-2026-33992 and 200,000+ other known vulnerabilities.

Severity & Exploitability

CVSS Score
9.6

Exploitation is straightforward and causes maximum impact. Patch immediately.

Also Known As

GHSA-m74m-f7cr-432x
PYSEC-2026-497

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