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CVE-2026-33992 — pyload-ng

Fix: pyload/pyload@b76b6d4

CVE-2026-33992 is a Server-Side Request Forgery (SSRF) vulnerability in pyload-ng. The records list no fixed version yet; check the vendor advisory below and apply the mitigations in the meantime.

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

Also known asGHSA-m74m-f7cr-432xPYSEC-2026-497
Published
Updated
Affected
1 pkg
Patched
See advisory
Exploits
None indexed
Exploitation data as of Oct 29, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Exploitation Status

Proof-of-concept exploit code exists

  • CISA’s SSVC triage found public proof-of-concept exploit code for this CVE, though no confirmed active exploitation.
  • CISA assesses this as automatable — exploitation doesn’t require manual, per-target effort, which raises the odds of mass scanning and opportunistic attacks.
  • A successful exploit gives an attacker total control of the affected component, not partial access.

Exploitation and automatability from CISA’s SSVC triage for CVE-2026-33992.

EPSS Exploitation Probability

via FIRST.org ↗
0.4%probability of exploitation in next 30 days
Lower Risk-0.05%
Lower risk than most CVEs35th percentile — riskier than 35% of all scored CVEsHighest risk
0.00%0.32%0.63%0.95%0.1%0.4%Apr 26Aug 26Oct 26

Probability of exploitation in the next 30 days, from FIRST.org EPSS.

Real-World Exposure

1 pkg affected
🐍pyload-ng

Real-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.

Description

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:

@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 total
EcosystemPackageVulnerable rangeFix
🐍PyPIpyload-ngall versionsNo fix

Affected Products

1 product · 1 configurations
Application
pyloadpyload
1 version
0.5.0

Detection & mitigation playbook

Open-source dependency

  1. Detect

    Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for pyload-ng, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.

  2. Remediation status

    The records we use list no patched version of pyload-ng for CVE-2026-33992. Check the maintainer's advisory, and where your build allows, override or pin the dependency away from the vulnerable range.

  3. Mitigate without a patch

    Restrict outbound requests from the affected component to an allowlist of hosts, block access to link-local and internal address ranges at the network layer, and require authentication on internal services so a forged request cannot reach them unauthenticated.

Frequently Asked Questions

## 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 t
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CVE-2026-33992: pyload-ng SSRF