Stanfordnlp vulnerabilities

Stanza is a Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages. Prior to 1.14.0, stanza.resources.common.unzip in stanza/resources/common.py passes downloaded model and resource archives to zipfile.ZipFile.extractall without validating member paths, and the vulnerable extraction path is reachable through stanza.download and stanza.install_corenlp. A malicious archive containing parent-directory traversal entries can write outside the intended model directory, allowing files writable by the Stanza process to be overwritten and potentially enabling code execution through modified shell configuration, SSH authorization data, Python packages, or executable scripts. This issue is fixed in version 1.14.0.

DSPy 3.3.0b1 contains a file exfiltration vulnerability in the Image and Audio output field adapters that allows attackers with influence over language model outputs to read arbitrary local files by injecting a filesystem path into the url field of a parsed Image or Audio typed output. The JSONAdapter and ChatAdapter parse untrusted language model completions through parse_value into TypeAdapter validation, which triggers encode_image or encode_audio to read and base64-encode any local file path via the os.path.isfile branch in image.py and audio.py, subsequently embedding the file contents into outgoing prompt messages sent to the attacker-controlled model endpoint.

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(..., weights_only=True) but fall back to torch.load(..., weights_only=False) on attacker-controllable pickle.UnpicklingError, allowing a malicious .pt pretrain or model file to execute arbitrary pickle code when a Stanza NLP pipeline loads it. This issue is fixed in version 1.12.2.