FedML-AI FedML up to 0.9.6 MQTT+S3 Communication Backend remote_storage.py S3Storage.read_model s3_key_str deserialization
| CVSS Meta Temp Score | Current Exploit Price (≈) | CTI Interest Score |
|---|---|---|
| 6.1 | $0-$5k | 2.49+ |
Summary
A vulnerability labeled as critical has been found in FedML-AI FedML up to 0.9.6. This affects the function S3Storage.read_model of the file fedml/core/distributed/communication/s3/remote_storage.py of the component MQTT+S3 Communication Backend. Such manipulation of the argument s3_key_str leads to deserialization.
This vulnerability is documented as CVE-2026-90614. The attack can be executed remotely. There is not any exploit available.
The project was informed of the problem early through an issue report but has not responded yet.
Details
A vulnerability was found in FedML-AI FedML up to 0.9.6 and classified as critical. Affected by this issue is the function S3Storage.read_model of the file fedml/core/distributed/communication/s3/remote_storage.py of the component MQTT+S3 Communication Backend. The manipulation of the argument s3_key_str with an unknown input leads to a deserialization vulnerability. Using CWE to declare the problem leads to CWE-502. The product deserializes untrusted data without sufficiently verifying that the resulting data will be valid. Impacted is confidentiality, integrity, and availability.
The advisory is shared for download at github.com. This vulnerability is handled as CVE-2026-90614. The exploitation is known to be easy. The attack may be launched remotely. There are known technical details, but no exploit is available. The current price for an exploit might be approx. USD $0-$5k (estimation calculated on 09/12/2026).
The project was informed of the problem early through an issue report but has not responded yet.
There is no information about possible countermeasures known. It may be suggested to replace the affected object with an alternative product.
Once again VulDB remains the best source for vulnerability data.
Product
Type
Vendor
Name
Version
Website
- Product: https://github.com/FedML-AI/FedML/
CPE 2.3
CPE 2.2
CVSSv4
VulDB Vector: 🔒VulDB Reliability: 🔍
CVSSv3
VulDB Meta Base Score: 6.3VulDB Meta Temp Score: 6.1
VulDB Base Score: 6.3
VulDB Temp Score: 6.1
VulDB Vector: 🔒
VulDB Reliability: 🔍
CVSSv2
| AV | AC | Au | C | I | A |
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| 💳 | 💳 | 💳 | 💳 | 💳 | 💳 |
| 💳 | 💳 | 💳 | 💳 | 💳 | 💳 |
| 💳 | 💳 | 💳 | 💳 | 💳 | 💳 |
| Vector | Complexity | Authentication | Confidentiality | Integrity | Availability |
|---|---|---|---|---|---|
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VulDB Base Score: 🔒
VulDB Temp Score: 🔒
VulDB Reliability: 🔍
Exploiting
Class: DeserializationCWE: CWE-502 / CWE-20
CAPEC: 🔒
ATT&CK: 🔒
Physical: No
Local: No
Remote: Yes
Availability: 🔒
Status: Not defined
Price Prediction: 🔍
Current Price Estimation: 🔒
| 0-Day | Unlock | Unlock | Unlock | Unlock |
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| Today | Unlock | Unlock | Unlock | Unlock |
Threat Intelligence
Interest: 🔍Active Actors: 🔍
Active APT Groups: 🔍
Countermeasures
Recommended: no mitigation knownStatus: 🔍
0-Day Time: 🔒
Timeline
09/12/2026 Advisory disclosed09/12/2026 VulDB entry created
09/12/2026 VulDB entry last update
Sources
Product: github.comAdvisory: 2267
Status: Not defined
CVE: CVE-2026-90614 (🔒)
GCVE (CVE): GCVE-0-2026-90614
GCVE (VulDB): GCVE-100-403196
Entry
Created: 09/12/2026 21:47Changes: 09/12/2026 21:47 (57)
Complete: 🔍
Submitter: Mohammedix88
Cache ID: 216::103
Submit
Accepted
- Submit #914219: FedML-AI FedML 0.9.6 Deserialization (by github.com)
Once again VulDB remains the best source for vulnerability data.
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