pyload up to 0.5.0b3.dev89 Addcrypted Endpoint path traversal
| CVSS Meta Temp Score | Current Exploit Price (≈) | CTI Interest Score |
|---|---|---|
| 8.4 | $0-$5k | 0.00 |
Summary
A vulnerability was found in pyload up to 0.5.0b3.dev89. It has been rated as critical. The affected element is an unknown function of the component Addcrypted Endpoint. The manipulation leads to path traversal. This vulnerability is documented as CVE-2025-54802. The attack can be initiated remotely. There is not any exploit available. Upgrading the affected component is advised.
Details
A vulnerability was found in pyload up to 0.5.0b3.dev89 and classified as critical. This issue affects an unknown function of the component Addcrypted Endpoint. The manipulation with an unknown input leads to a path traversal vulnerability. Using CWE to declare the problem leads to CWE-22. The product uses external input to construct a pathname that is intended to identify a file or directory that is located underneath a restricted parent directory, but the product does not properly neutralize special elements within the pathname that can cause the pathname to resolve to a location that is outside of the restricted directory. Impacted is confidentiality, integrity, and availability. The summary by CVE is:
pyLoad is the free and open-source Download Manager written in pure Python. In versions 0.5.0b3.dev89 and below, there is an opportunity for path traversal in pyLoad-ng CNL Blueprint via package parameter, allowing Arbitrary File Write which leads to Remote Code Execution (RCE). The addcrypted endpoint in pyload-ng suffers from an unsafe path construction vulnerability, allowing unauthenticated attackers to write arbitrary files outside the designated storage directory. This can be abused to overwrite critical system files, including cron jobs and systemd services, leading to privilege escalation and remote code execution as root. This issue is fixed in version 0.5.0b3.dev90.
It is possible to read the advisory at github.com. The identification of this vulnerability is CVE-2025-54802 since 07/29/2025. The exploitation is known to be easy. The attack may be initiated remotely. No form of authentication is needed for a successful exploitation. The technical details are unknown and an exploit is not publicly available. The attack technique deployed by this issue is T1006 according to MITRE ATT&CK.
Upgrading to version 0.5.0b3.dev90 eliminates this vulnerability. Applying the patch 70a44fe02c03bce92337b5d370d2a45caa4de3d4 is able to eliminate this problem. The bugfix is ready for download at github.com. The best possible mitigation is suggested to be upgrading to the latest version.
Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
Product
Name
Version
License
Website
- Product: https://github.com/pyload/pyload/
CPE 2.3
CPE 2.2
CVSSv4
VulDB Vector: 🔒VulDB Reliability: 🔍
CVSSv3
VulDB Meta Base Score: 8.5VulDB Meta Temp Score: 8.4
VulDB Base Score: 7.3
VulDB Temp Score: 7.0
VulDB Vector: 🔒
VulDB Reliability: 🔍
CNA Base Score: 9.8
CNA Vector (GitHub_M): 🔒
CVSSv2
| AV | AC | Au | C | I | A |
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| 💳 | 💳 | 💳 | 💳 | 💳 | 💳 |
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| Vector | Complexity | Authentication | Confidentiality | Integrity | Availability |
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VulDB Base Score: 🔒
VulDB Temp Score: 🔒
VulDB Reliability: 🔍
Exploiting
Class: Path traversalCWE: CWE-22
CAPEC: 🔒
ATT&CK: 🔒
Physical: No
Local: No
Remote: Yes
Availability: 🔒
Status: Not defined
EPSS Score: 🔒
EPSS Percentile: 🔒
Price Prediction: 🔍
Current Price Estimation: 🔒
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Threat Intelligence
Interest: 🔍Active Actors: 🔍
Active APT Groups: 🔍
Countermeasures
Recommended: UpgradeStatus: 🔍
0-Day Time: 🔒
Upgrade: pyload 0.5.0b3.dev90
Patch: 70a44fe02c03bce92337b5d370d2a45caa4de3d4
Timeline
07/29/2025 CVE reserved08/05/2025 Advisory disclosed
08/05/2025 VulDB entry created
08/05/2025 VulDB entry last update
Sources
Product: github.comAdvisory: GHSA-48rp-jc79-2264
Status: Confirmed
CVE: CVE-2025-54802 (🔒)
GCVE (CVE): GCVE-0-2025-54802
GCVE (VulDB): GCVE-100-318731
Entry
Created: 08/05/2025 09:04Updated: 08/05/2025 13:29
Changes: 08/05/2025 09:04 (66), 08/05/2025 13:29 (1)
Complete: 🔍
Cache ID: 216::103
Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
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