CVE-2026-8476

IBM Langflow OSS 1.0.0 through 1.10.0 contain a critical remote code execution vulnerability in the disk-based caching mechanism. The AsyncDiskCache class uses Python's unsafe pickle.loads function to deserialize cached objects from disk without validation, integrity verification, or...

CVE-2026-8476 Disk Cache Deserialization Remote Code Execution Vulnerability

IBM Langflow OSS 1.0.0 through 1.10.0 contain a critical remote code execution vulnerability in the disk-based caching mechanism. The AsyncDiskCache class uses Python's unsafe pickle.loads function to deserialize cached objects from disk without validation, integrity verification, or...

EUVD-2026-45276

IBM Langflow OSS 1.0.0 through 1.10.0 contain a critical remote code execution vulnerability in the disk-based caching mechanism. The AsyncDiskCache class uses Python's unsafe pickle.loads function to deserialize cached objects from disk without validation, integrity verification, or...

CVE-2026-8476

Langflow OSS versions 1.0.0–1.10.0 are impacted by a remote code execution vulnerability in the disk-based cache. The AsyncDiskCache deserializes cached items with unsafe pickle.loads() without validation, allowing arbitrary code execution when an attacker can influence cached data (e.g., through...

PT-2026-60864

Name of the Vulnerable Software and Affected Versions IBM Langflow OSS versions 1.0.0 through 1.10.0 Description A remote code execution issue exists in the disk-based caching mechanism. The AsyncDiskCache class uses the unsafe pickle.loads function to deserialize cached objects from disk without...

CVE-2026-54499 Stanza: Remote Code Execution via Unsafe Pickle Deserialization in Model Loaders

Stanza is a Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages. Prior to 1.12.2, Stanza model loaders such as stanza.models.common.pretrain.Pretrain.load attempt torch.load..., weightsonly=True but fall back to torch.load...,...

CVE-2026-54499

CVE-2026-54499 affects Stanza prior to 1.12.2, where model loading uses torch.load(..., weights_only=True) and on an attacker-controllable pickle.UnpicklingError falls back to weights_only=False, enabling arbitrary pickle code execution when loading a malicious .pt pretrain/file. The vulnerabilit...

CVE-2025-71369

picklescan before 0.0.28 fails to detect malicious pickle files that use torch.utils.data.datapipes.utils.decoder.basichandlers in reduce methods, allowing attackers to bypass safety checks. Remote attackers can embed undetected malicious code in pickle files that executes during deserialization,...

PYSEC-2026-545 OpenStack Object Storage (swift) Code Injection vulnerability

OpenStack Object Storage swift before 1.7.0 uses the loads function in the pickle Python module unsafely when storing and loading metadata in memcached, which allows remote attackers to execute arbitrary code via a crafted pickle object...

CVE-2026-56304

picklescan before 1.0.1 contains an unsafe pickle deserialization vulnerability allowing unauthenticated attackers to create arbitrary zero-byte files via logging.FileHandler class instantiation. Attackers can exploit this by crafting malicious pickle payloads to bypass RCE blocklists and create...

CVE-2026-56304

CVE-2026-56304 affects picklescan versions before 1.0.1. The flaw is an unsafe pickle deserialization through the logging.FileHandler class, allowing unauthenticated attackers to craft malicious pickle payloads to create arbitrary zero-byte files. This can bypass RCE blocklists and lead to filesy...

EUVD-2026-38123

picklescan before 1.0.1 contains an unsafe pickle deserialization vulnerability allowing unauthenticated attackers to create arbitrary zero-byte files via logging.FileHandler class instantiation. Attackers can exploit this by crafting malicious pickle payloads to bypass RCE blocklists and create...

CVE-2026-53872 picklescan - Arbitrary File Read via Unsafe Pickle Deserialization

picklescan before 0.0.35 contains an unsafe pickle deserialization vulnerability allowing unauthenticated attackers to read arbitrary server files by chaining io.FileIO and urllib.request.urlopen. Attackers can bypass RCE-focused blocklists to exfiltrate sensitive data like /etc/passwd to externa...

CVE-2026-53872 picklescan - Arbitrary File Read via Unsafe Pickle Deserialization

picklescan before 0.0.35 contains an unsafe pickle deserialization vulnerability allowing unauthenticated attackers to read arbitrary server files by chaining io.FileIO and urllib.request.urlopen. Attackers can bypass RCE-focused blocklists to exfiltrate sensitive data like /etc/passwd to externa...

EUVD-2026-37738

picklescan before 0.0.35 contains an unsafe pickle deserialization vulnerability allowing unauthenticated attackers to read arbitrary server files by chaining io.FileIO and urllib.request.urlopen. Attackers can bypass RCE-focused blocklists to exfiltrate sensitive data like /etc/passwd to externa...

CVE-2026-10042

The CVE-2026-10042 issue affects manga-image-translator, specifically the share.py module of the shared API server. It enables remote code execution through unsafe deserialization of attacker-controlled pickle data in the /execute/{method_name} and /simple_execute/{method_name} endpoints, which c...

CVE-2026-10042 manga-image-translator RCE via Unsafe Pickle Deserialization in Share Model

manga-image-translator contains a remote code execution vulnerability in the shared API server mode due to unsafe deserialization of untrusted pickle data in the share.py module, where the /execute/methodname and /simpleexecute/methodname endpoints deserialize attacker-controlled HTTP request...

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...

EUVD-2026-29507

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...

Deserialization of Untrusted Data

Overview lightning is a Deep Learning framework to train, deploy, and ship AI products Lightning fast. Affected versions of this package are vulnerable to Deserialization of Untrusted Data in the LightningModule.loadfromcheckpoint function. Any workflow that calls this function on an untrusted...