Security Bulletin: Maximo AI Service uses multiple third party dependencies which is vulnerable to multiple CVEs.

Summary Maximo AI Service uses transformers-4.48.3-py3-none-any.whl, transformers-4.50.0-py3-none-any.whl, transformers-4.52.1-py3-none-any.whl, transformers-4.53.0-py3-none-any.whl, transformers-4.57.3-py3-none-any.whl, urllib3-1.26.19-py2.py3-none-any.whl, urllib3-2.1.0-py3-none-any.whl,...

Security Bulletin: IBM Maximo Application Suite - Visual Inspection component uses transformers-4.57.3-py3-none-any.whl which is vulnerable to CVE-2025-14920, CVE-2025-14921, CVE-2025-14924, CVE-2025-14926, CVE-2025-14927, CVE-2025-14928, CVE-2025-14929.

Summary IBM Maximo Application Suite - Visual Inspection component uses transformers-4.57.3-py3-none-any.whl which is vulnerable to CVE-2025-14920, CVE-2025-14921, CVE-2025-14924, CVE-2025-14926, CVE-2025-14927, CVE-2025-14928, CVE-2025-14929.This bulletin contains information regarding the...

Security Bulletin: IBM Maximo Application Suite - Monitor Component uses transformers-4.53.0-py3-none-any.whl which is vulnerable to multiple CVEs.

Summary IBM Maximo Application Suite - Monitor Component uses transformers-4.53.0-py3-none-any.whl which is vulnerable to CVE-2025-14920, CVE-2025-14921, CVE-2025-14926, CVE-2025-14927, CVE-2025-14924, CVE-2025-14928, CVE-2025-14929, CVE-2025-14930. This bulletin contains information addressing t...

Arbitrary Remote Code Execution via `_attn_implementation_internal` Config Injection in transformers (No `trust_remote_code` Required)

Description A critical remote code execution vulnerability exists in the HuggingFace transformers library. An attacker can craft a malicious config.json containing the field attnimplementationinternal set to an attacker-controlled HuggingFace Hub repository ID. When a victim loads this model usin...

LoRA-Based Parameter-Efficient LLMs for Continuous Learning in Edge-Based Malware Detection

The proliferation of edge devices has created an urgent need for security solutions capable of detecting malware in real time while operating under strict computational and memory constraints. Recently, Large Language Models LLMs have demonstrated remarkable capabilities in recognizing complex...

Deserialization of Untrusted Data

Overview transformers is a State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow Affected versions of this package are vulnerable to Deserialization of Untrusted Data via the loadrngstate that uses unsafe torch.load function. An attacker can achieve an arbitrary code execution by...

Few-Shot Learning for Security Bug Report Identification

Security bug reports require prompt identification to minimize the window of vulnerability in software systems. Traditional machine learning ML techniques for classifying bug reports to identify security bug reports rely heavily on large amounts of labeled data. However, datasets for security bug...

Security Bulletin: IBM Maximo Application Suite - Monitor Component uses transformers-4.51.3-py3-none-any.whl which is vulnerable to CVE-2025-6638 and CVE-2025-3777.

Summary IBM Maximo Application Suite - Monitor Component uses transformers-4.51.3-py3-none-any.whl which is vulnerable to CVE-2025-6638 and CVE-2025-3777. This bulletin contains information addressing the vulnerability. Vulnerability Details CVEID:CVE-2025-6638 DESCRIPTION: A Regular Expression...

CVE-2025-14930

A flaw was found in the Hugging Face Transformers library. The parsing of weights fails to validate user-supplied data, causing a deserialization of untrusted data. An attacker can exploit this issue by providing a malicious GLM4 model, resulting in arbitrary code execution in the context of the...

CVE-2025-14929

A flaw was found in the Hugging Face Transformers library. The parsing of checkpoints fails to validate user-supplied data, causing a deserialization of untrusted data. An attacker can exploit this issue by providing a malicious X-CLIP model, resulting in arbitrary code execution in the context o...

CVE-2025-14928

A flaw was found in the Hugging Face Transformers library. The convertconfig function fails to validate a user-supplied string before using it to execute Python code. An attacker can exploit this flaw by providing a malicious HuBERT model checkpoint, causing arbitrary code execution in the contex...

CVE-2025-14927

A flaw was found in the Hugging Face Transformers library. The convertconfig function fails to validate a user-supplied string before using it to execute Python code. An attacker can exploit this flaw by providing a malicious SEW-D model checkpoint, causing arbitrary code execution in the context...

CVE-2025-14926

A flaw was found in the Hugging Face Transformers library. The convertconfig function fails to validate a user-supplied string before using it to execute Python code. An attacker can exploit this flaw by providing a malicious SEW model checkpoint, causing arbitrary code execution in the context o...

CVE-2025-14924

A flaw was found in the Hugging Face Transformers library. The parsing of checkpoints fails to validate user-supplied data, causing a deserialization of untrusted data. An attacker can exploit this issue by providing a malicious megatrongpt2 model, resulting in arbitrary code execution in the...

CVE-2025-14920

A flaw was found in the Hugging Face Transformers library. The parsing of model files fails to validate user-supplied data, causing a deserialization of untrusted data. An attacker can exploit this issue by providing a malicious Perceiver model or convincing a user to visit a malicious page,...

CVE-2025-14921

A flaw was found in the Hugging Face Transformers library. The parsing of model files fails to validate user-supplied data, causing a deserialization of untrusted data. An attacker can exploit this issue by providing a malicious Transformer-XL model, resulting in arbitrary code execution in the...

Arbitrary Code Injection

Overview transformers is a State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow Affected versions of this package are vulnerable to Arbitrary Code Injection via the convertconfig function. An attacker can execute arbitrary code by supplying a malicious checkpoint file that is process...

Arbitrary Code Injection

Overview transformers is a State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow Affected versions of this package are vulnerable to Arbitrary Code Injection via the convertconfig function. An attacker can execute arbitrary code by supplying a malicious checkpoint file that is process...

Deserialization of Untrusted Data

Overview transformers is a State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow Affected versions of this package are vulnerable to Deserialization of Untrusted Data via the parsing process of model files. An attacker can execute arbitrary code in the context of the current user by...

Deserialization of Untrusted Data

Overview transformers is a State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow Affected versions of this package are vulnerable to Deserialization of Untrusted Data via the megatrongpt2 process. An attacker can achieve arbitrary code execution by tricking a user into opening a...