immich-app Immich up to 3.2.x Predict Endpoint base.py clear_cache cache_dir input validation
| CVSS Meta Temp Score | Current Exploit Price (≈) | CTI Interest Score |
|---|---|---|
| 6.3 | $0-$5k | 1.30 |
Summary
A vulnerability has been found in immich-app Immich up to 3.2.x and classified as critical. This vulnerability affects the function clear_cache of the file machine-learning/immich_ml/models/base.py of the component Predict Endpoint. This manipulation of the argument cache_dir causes input validation.
This vulnerability is registered as CVE-2026-119328. Remote exploitation of the attack is possible. No exploit is available.
The affected component should be upgraded.
Details
A vulnerability classified as critical was found in immich-app Immich up to 3.2.x. Affected by this vulnerability is the function clear_cache of the file machine-learning/immich_ml/models/base.py of the component Predict Endpoint. The manipulation of the argument cache_dir with an unknown input leads to a input validation vulnerability. The CWE definition for the vulnerability is CWE-20. The product receives input or data, but it does
not validate or incorrectly validates that the input has the
properties that are required to process the data safely and
correctly. As an impact it is known to affect integrity, and availability. The summary by CVE is:
Immich is a high-performance self-hosted photo and video management solution. Prior to 3.3.0, the unauthenticated machine-learning /predict endpoint in machine-learning/immich_ml/main.py accepted an options object and passed its values into model construction in machine-learning/immich_ml/models/base.py without restricting security-sensitive parameters. An attacker with network access to the service could set cache_dir to an arbitrary writable path, causing model downloads to write there and causing clear_cache() to pass that path to shutil.rmtree() after selected model-loading failures. Depending on filesystem permissions and the selected path, this could modify files in mounted data locations or recursively delete an attacker-selected directory. The model-name allowlist prevents this issue from becoming arbitrary-model deserialization or code execution. This issue is fixed in version 3.3.0.
It is possible to read the advisory at github.com. This vulnerability is known as CVE-2026-119328 since 10/29/2026. The exploitation appears to be easy. The attack can be launched remotely. The exploitation doesn't need any form of authentication. Technical details of the vulnerability are known, but there is no available exploit.
Upgrading to version 3.3.0 eliminates this vulnerability.
Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
Product
Vendor
Name
Version
Website
CPE 2.3
CPE 2.2
CVSSv4
VulDB Vector: 🔒VulDB Reliability: 🔍
CVSSv3
VulDB Meta Base Score: 6.5VulDB Meta Temp Score: 6.3
VulDB Base Score: 6.5
VulDB Temp Score: 6.2
VulDB Vector: 🔒
VulDB Reliability: 🔍
CNA Base Score: 6.5
CNA Vector (GitHub_M): 🔒
CVSSv2
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| Vector | Complexity | Authentication | Confidentiality | Integrity | Availability |
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VulDB Base Score: 🔒
VulDB Temp Score: 🔒
VulDB Reliability: 🔍
Exploiting
Class: Input validationCWE: CWE-20
CAPEC: 🔒
ATT&CK: 🔒
Physical: No
Local: No
Remote: Yes
Availability: 🔒
Status: Not defined
EPSS Score: 🔒
EPSS Percentile: 🔒
Price Prediction: 🔍
Current Price Estimation: 🔒
| 0-Day | Unlock | Unlock | Unlock | Unlock |
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Threat Intelligence
Interest: 🔍Active Actors: 🔍
Active APT Groups: 🔍
Countermeasures
Recommended: UpgradeStatus: 🔍
0-Day Time: 🔒
Upgrade: Immich 3.3.0
Timeline
10/29/2026 CVE reserved10/30/2026 Advisory disclosed
10/30/2026 VulDB entry created
10/30/2026 VulDB entry last update
Sources
Product: github.comAdvisory: github.com
Status: Confirmed
CNA: GitHub_M
CVE: CVE-2026-119328 (🔒)
GCVE (CVE): GCVE-0-2026-119328
GCVE (VulDB): GCVE-100-429355
Entry
Created: 10/30/2026 21:10Changes: 10/30/2026 21:10 (67)
Complete: 🔍
Cache ID: 216::103
Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
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