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
- Now navigate to Files section and download the link.
- It was observed that we are able to Read the Digital Ocean Metadata
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
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
- Cloud Metadata Theft: Complete exfiltration of instance metadata
- Lateral Movement: Discovery and enumeration of internal network services
- Credential Exposure: Theft of cloud IAM credentials, SSH keys, API tokens
- Infrastructure Mapping: Network topology, IP addressing, service discovery
Impact
Vulnerability Type: Server-Side Request Forgery (SSRF)
CVSS Score: 7.7 - 9.1 (High to Critical, depending on cloud deployment)
Untrusted input controls the target URL of a server-initiated request, which may reach internal services not otherwise accessible from outside. Typical impact: access to internal metadata services, internal APIs, or cloud credentials.
Affected versions
Security releases
Kodem intelligence
Severity tells you how bad this could be in the worst case. It does not tell you whether you are exposed. Exploitability and impact are functions of runtime truth: whether the vulnerable code is present, reachable, and actually executes in your application. A vulnerable package can sit in your dependency tree and never run.
Kodem, an Intelligent Application Security platform, uses runtime intelligence to reveal which vulnerabilities actually execute in production, so teams prioritize the ones that genuinely matter. Kodem's runtime-powered SCA identifies whether this CVE is reachable in your applications.
Remediation advice
Implement URL validation in the download engine:
- Whitelist allowed URL schemes (http/https only)
- Block requests to private IP ranges (RFC 1918, link-local addresses)
- Block cloud metadata endpoints (169.254.169.254, metadata.google.internal, etc.)
- Implement request destination validation before initiating downloads
Frequently Asked Questions
- What is CVE-2026-33992? CVE-2026-33992 is a critical-severity server-side request forgery (SSRF) vulnerability in pyload-ng (pip), affecting versions <= 0.5.0b3.dev96. No fixed version is listed yet. Untrusted input controls the target URL of a server-initiated request, which may reach internal services not otherwise accessible from outside.
- Which versions of pyload-ng are affected by CVE-2026-33992? pyload-ng (pip) versions <= 0.5.0b3.dev96 is affected.
- Is there a fix for CVE-2026-33992? No fixed version is listed for CVE-2026-33992 yet. Monitor the advisory for updates and apply mitigations in the interim.
- Is CVE-2026-33992 exploitable, and should I be worried? Whether CVE-2026-33992 is exploitable in your environment depends on whether the vulnerable code is present and reachable. A CVSS score is a worst-case rating; it does not account for your specific deployment, configuration, or usage patterns. Kodem, an Intelligent Application Security platform, uses runtime intelligence to show which vulnerabilities actually execute in production, so you can focus on the ones that represent real risk. Get a demo
- What actually determines whether CVE-2026-33992 is exploitable, and how bad it is? Exploitability and impact are not fixed properties of a CVE. They depend on runtime truth: whether the vulnerable code is present, reachable, and actually executes in your application. A high CVSS score on a dependency that never runs is not the same as real risk. Kodem, an Intelligent Application Security platform, uses runtime intelligence to reveal which vulnerabilities actually execute in production, so teams prioritize the ones that genuinely matter.
- How do I fix CVE-2026-33992? No fixed version is listed yet. In the interim: Validate and restrict destination URLs against an allowlist. Block requests to private IP ranges and cloud metadata endpoints.