AUTOMATIC1111 stable-diffusion-webui up to 1.10.1 Metadata Extraction modules/sd_models.py read_metadata_from_safetensors header length field allocation of resources
| CVSS Meta Temp Score | Current Exploit Price (≈) | CTI Interest Score |
|---|---|---|
| 4.1 | $0-$5k | 1.94 |
Summary
A vulnerability classified as problematic has been found in AUTOMATIC1111 stable-diffusion-webui up to 1.10.1. Affected is the function read_metadata_from_safetensors of the file modules/sd_models.py of the component Metadata Extraction. This manipulation of the argument header length field causes allocation of resources.
This vulnerability is handled as CVE-2026-111985. The attack can be initiated remotely. Additionally, an exploit exists.
The project was informed of the problem early through an issue report but has not responded yet.
Details
A vulnerability classified as problematic was found in AUTOMATIC1111 stable-diffusion-webui up to 1.10.1. Affected by this vulnerability is the function read_metadata_from_safetensors of the file modules/sd_models.py of the component Metadata Extraction. The manipulation of the argument header length field with an unknown input leads to a allocation of resources vulnerability. The CWE definition for the vulnerability is CWE-770. The product allocates a reusable resource or group of resources on behalf of an actor without imposing any restrictions on the size or number of resources that can be allocated, in violation of the intended security policy for that actor. As an impact it is known to affect availability.
It is possible to read the advisory at github.com. This vulnerability is known as CVE-2026-111985. The exploitation appears to be easy. The attack can be launched remotely. The exploitation doesn't need any form of authentication. It demands that the victim is doing some kind of user interaction. Technical details and also a public exploit are known. The attack technique deployed by this issue is T1499 according to MITRE ATT&CK.
It is possible to download the exploit at github.com. It is declared as proof-of-concept. 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.
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: 4.3VulDB Meta Temp Score: 4.1
VulDB Base Score: 4.3
VulDB Temp Score: 4.1
VulDB Vector: 🔒
VulDB Reliability: 🔍
CVSSv2
| AV | AC | Au | C | I | A |
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| 💳 | 💳 | 💳 | 💳 | 💳 | 💳 |
| 💳 | 💳 | 💳 | 💳 | 💳 | 💳 |
| 💳 | 💳 | 💳 | 💳 | 💳 | 💳 |
| Vector | Complexity | Authentication | Confidentiality | Integrity | Availability |
|---|---|---|---|---|---|
| Unlock | Unlock | Unlock | Unlock | Unlock | Unlock |
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VulDB Base Score: 🔒
VulDB Temp Score: 🔒
VulDB Reliability: 🔍
Exploiting
Class: Allocation of resourcesCWE: CWE-770 / CWE-400 / CWE-404
CAPEC: 🔒
ATT&CK: 🔒
Physical: No
Local: No
Remote: Yes
Availability: 🔒
Access: Public
Status: Proof-of-Concept
Download: 🔒
Price Prediction: 🔍
Current Price Estimation: 🔒
| 0-Day | Unlock | Unlock | Unlock | Unlock |
|---|---|---|---|---|
| Today | Unlock | Unlock | Unlock | Unlock |
Threat Intelligence
Interest: 🔍Active Actors: 🔍
Active APT Groups: 🔍
Countermeasures
Recommended: no mitigation knownStatus: 🔍
0-Day Time: 🔒
Timeline
10/17/2026 Advisory disclosed10/17/2026 VulDB entry created
10/17/2026 VulDB entry last update
Sources
Product: github.comAdvisory: 17498
Status: Confirmed
CVE: CVE-2026-111985 (🔒)
GCVE (CVE): GCVE-0-2026-111985
GCVE (VulDB): GCVE-100-421651
scip Labs: https://www.scip.ch/en/?labs.20161013
Entry
Created: 10/17/2026 23:54Changes: 10/17/2026 23:54 (59)
Complete: 🔍
Submitter: r1ck99
Cache ID: 216::103
Submit
Accepted
- Submit #1005484: AUTOMATIC1111 stable-diffusion-webui v1.10.1 Allocation of Resources Without Limits or Throttling (by r1ck99)
Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
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