Vulnary
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Critical· 9.3

CVE-2026-35459

pyLoad, a free download manager, has a server‑side request forgery flaw that lets an authenticated user trick the system into fetching internal network resources. The problem occurs when a user submits a URL that redirects to an internal address, bypassing the IP check added in a previous patch.

publishedApr 6, 2026
last modifiedJul 24, 2026
sourcesNVD
severity · cvss
9.3
critical · how bad it is
exploitation · epss
<1%
20th percentile · chance of exploitation in 30 days
(ai-assisted) A model wrote this summary from the official data, so double-check it against the source before you act on it. Read the official advisory →
auto-deletes from the system
counting…on Sep 7, 2026

No official fix yet. If none appears within 45 days of first tracking, this entry is removed automatically.

01

Who is affected

pyLoad (pyload‑ng_project pyload‑ng) versions 0.5.0b3.dev96 and earlier. Users who run these versions and grant ADD permission to authenticated users are at risk.

02

Real-world impact

An attacker could cause the pyLoad server to access internal services or files, potentially exposing sensitive data or enabling further attacks inside the network.

03

Why this severity

The CVSS score of 9.3 reflects the high impact on confidentiality and integrity, the low attack complexity, and the fact that no user interaction is required. The flaw allows an attacker to read or modify internal resources through the server.

04

What to do about it

no official fix yet

No official fix or mitigation is documented in the sources yet. Monitor the vendor advisory and apply the patch as soon as it is released.

No fix documented in sources

05

Timeline

  1. Apr 6, 2026 · Apr 6, 2026
    Published
    Disclosed and added to the National Vulnerability Database.
  2. Jul 24, 2026 · 11d ago
    Advisory updated
    The NVD record was last revised.
06

How it’s attacked

Attack vectorNetwork (remote)
Attack complexityLow
Attack requirementsNone
Privileges requiredLow
User interactionNone needed
Confidentiality impactHigh
Integrity impactHigh
Availability impactNone
07

References & advisories

(ai-assisted) A model wrote this summary from the official data, so double-check it against the source before you act on it. Read the official advisory →