CVE-2026-44843 LangChain: Unsafe deserialization of attacker-controlled LangChain objects through overly broad `load()` allowlists

LangChain is a framework for building agents and LLM-powered applications. Prior to 0.3.85 and 1.3.3, LangChain contains older runtime code paths that deserialize run inputs, run outputs, or other application-controlled payloads using overly broad object allowlists. These paths may call load with...

CVE-2026-24163

NVIDIA TRT-LLM for any platform contains a vulnerability in RPC testing, where an attacker could cause an unsafe deserialization. A successful exploit of this vulnerability might lead to code execution, denial of service, data tampering, and information disclosure...

CVE-2025-33255

NVIDIA TRT-LLM for any platform contains a vulnerability in MPI server, where an attacker could cause an unsafe deserialization. A successful exploit of this vulnerability might lead to code execution, denial of service, data tampering, and information disclosure...

EUVD-2026-31057

NVIDIA TRT-LLM for any platform contains a vulnerability in RPC testing, where an attacker could cause an unsafe deserialization. A successful exploit of this vulnerability might lead to code execution, denial of service, data tampering, and information disclosure...

CVE-2026-24163

NVIDIA TRT-LLM for any platform contains a vulnerability in RPC testing, where an attacker could cause an unsafe deserialization. A successful exploit of this vulnerability might lead to code execution, denial of service, data tampering, and information disclosure...

CVE-2026-24163

NVIDIA TensorRT-LLM (any platform) is affected by CVE-2026-24163 due to an unsafe deserialization in RPC testing, enabling attackers to potentially achieve code execution, DoS, data tampering, and information disclosure. Severity: High; CVSS base score 7.5 (NASA bulletin) with local/remote factor...

CVE-2026-24163

NVIDIA TRT-LLM for any platform contains a vulnerability in RPC testing, where an attacker could cause an unsafe deserialization. A successful exploit of this vulnerability might lead to code execution, denial of service, data tampering, and information disclosure...

CVE-2025-33255

NVIDIA TRT-LLM for any platform contains a vulnerability in MPI server, where an attacker could cause an unsafe deserialization. A successful exploit of this vulnerability might lead to code execution, denial of service, data tampering, and information disclosure...

CVE-2025-33255

NVIDIA TRT-LLM for any platform contains a vulnerability in MPI server, where an attacker could cause an unsafe deserialization. A successful exploit of this vulnerability might lead to code execution, denial of service, data tampering, and information disclosure...

CVE-2025-33255

Summary: CVE-2025-33255 affects NVIDIA TensorRT-LLM (any platform) via an MPI server deserialization vulnerability. The impact described across sources includes code execution, denial of service, data tampering, and information disclosure. The NVIDIA security bulletin specifies remediation by upd...

PT-2026-42087

Name of the Vulnerable Software and Affected Versions NVIDIA TRT-LLM affected versions not specified Description A flaw in the MPI server allows an attacker to trigger unsafe deserialization. This process, which involves converting data from a stream back into an object, can be manipulated to...

CVE-2026-33233 AutoGPT Platform: Remote Code Execution via Unsafe Pickle Deserialization of Redis Cache Entries

AutoGPT is a workflow automation platform for creating, deploying, and managing continuous artificial intelligence agents. In versions 0.6.34 through 0.6.51, the backend deserializes Redis cache bytes using pickle.loads without integrity/authenticity checks. The write path serializes values with...

Security Bulletin: NVIDIA TensorRT-LLM - May 2026

NVIDIA has released a software update for NVIDIA® TensorRT-LLM. To protect your system, clone or update this software to TensorRT-LLM v1.2.1 from GitHub. Go to NVIDIA Product Security. Details The following table summarizes the potential vulnerabilities that this security update addresses and the...

camel-infinispan: camel-infinispan: Remote Code Execution via Unsafe Deserialization

A flaw was found in camel-infinispan. This vulnerability involves unsafe deserialization in the ProtoStream remote aggregation repository. A remote attacker with low privileges could exploit this by sending specially crafted data, leading to arbitrary code execution. This allows the attacker to...

EUVD-2026-29560

The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization CWE-502 through its predict method. When a user provides a dataset file path to the predict method, the framework automatically determines the file format. If the file is a pickle .pkl file, it is loaded using...

GHSA-FQ92-QC8F-482V Snorkel BaseLabeler.load uses an unsafe pickle.load

The snorkel library thru v0.10.0 contains a critical insecure deserialization vulnerability CWE-502 in the BaseLabeler.load method of the BaseLabeler class. The method loads serialized labeler models using the unsafe pickle.load function on user-supplied file paths without any validation or...

Snorkel BaseLabeler.load uses an unsafe pickle.load

The snorkel library thru v0.10.0 contains a critical insecure deserialization vulnerability CWE-502 in the BaseLabeler.load method of the BaseLabeler class. The method loads serialized labeler models using the unsafe pickle.load function on user-supplied file paths without any validation or...

GHSA-GPX5-7XM4-229W Snorkel MultitaskClassifier.load uses an unsafe torch.load

The snorkel library thru v0.10.0 contains an insecure deserialization vulnerability CWE-502 in the MultitaskClassifier.load method of the MultitaskClassifier class. The method loads model weight files using torch.load without enabling the security-restrictive weightsonly=True parameter. This...

CVE-2026-31223

The snorkel library thru v0.10.0 contains a critical insecure deserialization vulnerability CWE-502 in the BaseLabeler.load method of the BaseLabeler class. The method loads serialized labeler models using the unsafe pickle.load function on user-supplied file paths without any validation or...

Machine Learning Engineering Open Book 安全漏洞

Machine Learning Engineering Open Book is a collection of methodologies for training and fine-tuning large language models developed by Stas Bekman. There is a security vulnerability in Machine Learning Engineering Open Book. This vulnerability arises from the use of the torch-checkpoint-shrink.p...