CVE-2026-33992
pyLoad: Server-Side Request Forgery via Download Link Submission Enables Cloud Metadata Exfiltration
pyLoad is a free and open-source download manager written in Python. Prior to version 0.5.0b3.dev97, 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. Version 0.5.0b3.dev97 contains a patch.
Attack profile
How easy it is to exploit
- Attack vector
- Network
- Complexity
- Low
- Privileges needed
- Low
- User interaction
- None
What an attacker can affect
- Confidentiality
- High
- Integrity
- High
- Availability
- None
Exploit likelihood
What each source reports
CVE List Score used
pyLoad: Server-Side Request Forgery via Download Link Submission Enables Cloud Metadata Exfiltration
pyLoad is a free and open-source download manager written in Python. Prior to version 0.5.0b3.dev97, 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. Version 0.5.0b3.dev97 contains a patch.
- Record
CVE-2026-33992- CVSS 4.0
- 9.3 Critical
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 - Weakness
- CWE-918
- Updated
- 2026-11-02
EUVDEUVD-2026-16886
pyLoad is a free and open-source download manager written in Python. Prior to version 0.5.0b3.dev97, 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. Version 0.5.0b3.dev97 contains a patch.
- Record
EUVD-2026-16886- CVSS 4.0
- 9.3 Critical
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 - Updated
- 2026-11-02
GitHub AdvisoriesGHSA-m74m-f7cr-432x
pyLoad: Server-Side Request Forgery via Download Link Submission Enables Cloud Metadata Exfiltration
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
- 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
Remediation
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
- Record
GHSA-m74m-f7cr-432x- CVSS 4.0
- 9.3 Critical
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 - Weakness
- CWE-918
- Updated
- 2026-11-02
NVD
pyLoad is a free and open-source download manager written in Python. Prior to version 0.5.0b3.dev97, 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. Version 0.5.0b3.dev97 contains a patch.
- Record
CVE-2026-33992- CVSS 4.0
- 9.3 Critical
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/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X - CVSS 3.1
- 6.5 Medium
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N - Weakness
- CWE-918
- Updated
- 2026-11-02
OSV
pyLoad: Server-Side Request Forgery via Download Link Submission Enables Cloud Metadata Exfiltration
pyLoad is a free and open-source download manager written in Python. Prior to version 0.5.0b3.dev97, 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. Version 0.5.0b3.dev97 contains a patch.
- Record
CVE-2026-33992- CVSS 4.0
- 9.3 Critical
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 - Weakness
- CWE-918
- Updated
- 2026-11-02
OSVGHSA-m74m-f7cr-432x
pyLoad: Server-Side Request Forgery via Download Link Submission Enables Cloud Metadata Exfiltration
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
- 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
Remediation
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
- Record
GHSA-m74m-f7cr-432x- CVSS 4.0
- 9.3 Critical
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 - Weakness
- CWE-918
- Updated
- 2026-11-02
OSVPYSEC-2026-497
pyLoad: Server-Side Request Forgery via Download Link Submission Enables Cloud Metadata Exfiltration
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
- 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
Remediation
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
- Record
PYSEC-2026-497- CVSS 4.0
- 9.3 Critical
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 - Updated
- 2026-11-02
Affected products
Affected packages
| Package | Affected | Fixed |
|---|---|---|
pyload-ngPyPI |
through 0.5.0b3.dev96 | None known |
pyload-ngPyPI |
through 0.5.0b3.dev96, plus listed versions 0.5.0a5.dev5280.5.0a5.dev5320.5.0a5.dev5350.5.0a5.dev5360.5.0a5.dev537 Show 45 moreShow less0.5.0a5.dev5390.5.0a5.dev5400.5.0a5.dev5450.5.0a5.dev5620.5.0a5.dev5640.5.0a5.dev5650.5.0a6.dev5700.5.0a6.dev5780.5.0a6.dev5870.5.0a7.dev5960.5.0a8.dev6020.5.0a9.dev6150.5.0a9.dev6290.5.0a9.dev6320.5.0a9.dev6410.5.0a9.dev6430.5.0a9.dev6550.5.0a9.dev8060.5.0b1.dev10.5.0b1.dev20.5.0b1.dev30.5.0b1.dev40.5.0b1.dev50.5.0b2.dev100.5.0b2.dev110.5.0b2.dev120.5.0b2.dev90.5.0b3.dev130.5.0b3.dev140.5.0b3.dev170.5.0b3.dev180.5.0b3.dev190.5.0b3.dev200.5.0b3.dev210.5.0b3.dev220.5.0b3.dev240.5.0b3.dev260.5.0b3.dev270.5.0b3.dev280.5.0b3.dev290.5.0b3.dev300.5.0b3.dev310.5.0b3.dev320.5.0b3.dev330.5.0b3.dev34 |
None known |
History
| Recorded | Changed | Sources |
|---|---|---|
| first indexed | CVE List, EUVD, GitHub Advisories, NVD, OSV |
Dates are when Every CVE recorded each change. Upstream dates may differ.
In short
CVE-2026-33992 is a critical vulnerability (CVSS 9.3) in Pyload, published March 27, 2026. No source lists public exploit code. EPSS puts the chance of exploitation in the next 30 days at 0.40%, the 34th percentile. No source names a fixed version.
References
github.com/pyload/pyload/security/advisories/GHSA-m74m-f7cr-432x
nvd.nist.gov/vuln/detail/CVE-2026-33992
pypi.org/project/pyload-ng
Left out here: 50 versions. The JSON record has them.