ai.new-wave:spring-agent-app (>=0.1.0 <=0.3.0), ai.new-wave:spring-agent-core (>=0.1.0 <=0.3.0) +372 more potentially affected by CVE-2026-41712 via org.springframework.ai:spring-ai-model (>=2.0.0-M1 <=2.0.0-M5)

org.springframework.ai:spring-ai-model MAVEN version =2.0.0-M1, =0.1.0, =0.1.0, =1.21.9, =0.0.1, =0.0.1, =0.0.1, =0.0.1, =0.0.1, =0.0.1, =0.0.1, =0.0.1, =0.0.1, =0.0.2 and more Source cves: CVE-2026-41712 Source advisory: OSV:GHSA-Q62F-H9X2-GCQC...

CVE-2026-41713

A malicious user could craft input that is stored in conversation memory and later interpreted by the model in an unintended way. Applications using the affected advisor with user-controlled input may be susceptible to manipulation of model behavior across conversation turns...

CVE-2026-41713

A malicious user could craft input that is stored in conversation memory and later interpreted by the model in an unintended way. Applications using the affected advisor with user-controlled input may be susceptible to manipulation of model behavior across conversation turns...

CVE-2026-41713 Prompt Injection via Memory Poisoning in PromptChatMemoryAdvisor

A malicious user could craft input that is stored in conversation memory and later interpreted by the model in an unintended way. Applications using the affected advisor with user-controlled input may be susceptible to manipulation of model behavior across conversation turns...

CVE-2024-54017

CVE-2024-54017 affects SIPROTEC 5 devices (multiple models listed) and is caused by insufficient randomness in session identifiers. This enables an unauthenticated remote attacker to brute-force a session ID and read limited information from the web server without authorization. No exploitation d...

CVE-2026-7482

A flaw was found in Ollama. A remote attacker can exploit a heap out-of-bounds read vulnerability in the GGUF model loader by providing a specially crafted GGUF GGML Unified Format file to the /api/create endpoint. This allows the attacker to read beyond the allocated memory buffer, potentially...

MINI-2326-PCVF-V44Q

Bulletin has no description...

MINI-V863-CM32-G69R

Bulletin has no description...

MINI-R824-5GRJ-GH98

Bulletin has no description...

MINI-PC27-73F6-6P4G

Bulletin has no description...

MINI-M63V-766W-MJG9

Bulletin has no description...

MINI-M4VF-67MH-RXH8

Bulletin has no description...

MINI-JMCP-MHGC-944G

Bulletin has no description...

MINI-HG23-3G85-262V

Bulletin has no description...

MINI-38MP-539P-23QJ

Bulletin has no description...

MINI-F45C-MFH5-R5W2

Bulletin has no description...

MINI-927X-FH9W-PPFM

Bulletin has no description...

CVE-2026-31218

The CVE concerns the optimate project’s neural_magic_training.py, where _load_model() deserializes a state_dict.pt with torch.load() without enabling weights_only=True. This enables deserialization of arbitrary Python objects via Pickle, allowing a remote attacker to provide a crafted state_dict....

CVE-2026-31219

The loadmodel function in the neuralmagictraining.py script of the optimate project in commit a6d302f912b481c94370811af6b11402f51d377f 2024-07-21 is vulnerable to insecure deserialization CWE-502. When a user provides a single model file path e.g., .pt or .pth via the --model command-line argumen...

CVE-2026-31229

The Adversarial Robustness Toolbox ART thru 1.20.1 contains an insecure deserialization vulnerability CWE-502 in its Kubeflow component's model loading functionality. When loading model weights from a file e.g., model.pt during robustness evaluation, the code uses torch.load without the...