Nltk
Monthly
Unsafe path handling in NLTK's filestring() function enables attackers to read arbitrary files on affected iOS and AI/ML systems through improper input validation. An unauthenticated attacker can exploit this over the network by supplying directory traversal or absolute paths to access sensitive data, with particular risk in deployments exposing the function through web APIs. No patch is currently available for this high-severity vulnerability (CVSS 8.6).
Path traversal in NLTK (Natural Language Toolkit) versions ≤3.9.2 allows remote unauthenticated attackers to read arbitrary files from the server hosting NLP applications. Multiple CorpusReader classes (WordListCorpusReader, TaggedCorpusReader, BracketParseCorpusReader) fail to sanitize file paths, enabling directory traversal to access sensitive files including SSH keys, API tokens, and system configurations. This poses critical risk in machine learning APIs, chatbots, and NLP pipelines that process user-controlled file inputs. EPSS score of 0.25% (48th percentile) suggests low widespread exploitation probability despite public disclosure via huntr.com bounty, though the unauthenticated network vector (AV:N/PR:N) and zero attack complexity make this readily exploitable once targets are identified.
Arbitrary code execution in the NLTK (Natural Language Toolkit) Python library affects all versions through its data downloader: the _unzip_iter function in nltk/downloader.py calls zipfile.extractall() with no path validation, so a malicious data package can drop attacker-controlled Python files (e.g. __init__.py) that execute automatically on import. Any application that downloads NLTK data from an attacker-influenced source is exposed to full remote code execution. Publicly available exploit code exists (huntr.com bounty), EPSS is modest at 0.57% (68th percentile), and there is no public exploit identified as actively exploited in CISA KEV.
NLTK (Natural Language Toolkit) is a suite of open source Python modules, data sets, and tutorials supporting research and development in Natural Language Processing. Rated high severity (CVSS 7.5), this vulnerability is remotely exploitable, no authentication required, low attack complexity. Public exploit code available.
nltk is vulnerable to Inefficient Regular Expression Complexity. Rated high severity (CVSS 7.5), this vulnerability is remotely exploitable, no authentication required, low attack complexity. Public exploit code available.
NLTK Downloader before 3.4.5 is vulnerable to a directory traversal, allowing attackers to write arbitrary files via a ../ (dot dot slash) in an NLTK package (ZIP archive) that is mishandled during. Rated high severity (CVSS 7.5), this vulnerability is remotely exploitable, no authentication required, low attack complexity. Public exploit code available.
Unsafe path handling in NLTK's filestring() function enables attackers to read arbitrary files on affected iOS and AI/ML systems through improper input validation. An unauthenticated attacker can exploit this over the network by supplying directory traversal or absolute paths to access sensitive data, with particular risk in deployments exposing the function through web APIs. No patch is currently available for this high-severity vulnerability (CVSS 8.6).
Path traversal in NLTK (Natural Language Toolkit) versions ≤3.9.2 allows remote unauthenticated attackers to read arbitrary files from the server hosting NLP applications. Multiple CorpusReader classes (WordListCorpusReader, TaggedCorpusReader, BracketParseCorpusReader) fail to sanitize file paths, enabling directory traversal to access sensitive files including SSH keys, API tokens, and system configurations. This poses critical risk in machine learning APIs, chatbots, and NLP pipelines that process user-controlled file inputs. EPSS score of 0.25% (48th percentile) suggests low widespread exploitation probability despite public disclosure via huntr.com bounty, though the unauthenticated network vector (AV:N/PR:N) and zero attack complexity make this readily exploitable once targets are identified.
Arbitrary code execution in the NLTK (Natural Language Toolkit) Python library affects all versions through its data downloader: the _unzip_iter function in nltk/downloader.py calls zipfile.extractall() with no path validation, so a malicious data package can drop attacker-controlled Python files (e.g. __init__.py) that execute automatically on import. Any application that downloads NLTK data from an attacker-influenced source is exposed to full remote code execution. Publicly available exploit code exists (huntr.com bounty), EPSS is modest at 0.57% (68th percentile), and there is no public exploit identified as actively exploited in CISA KEV.
NLTK (Natural Language Toolkit) is a suite of open source Python modules, data sets, and tutorials supporting research and development in Natural Language Processing. Rated high severity (CVSS 7.5), this vulnerability is remotely exploitable, no authentication required, low attack complexity. Public exploit code available.
nltk is vulnerable to Inefficient Regular Expression Complexity. Rated high severity (CVSS 7.5), this vulnerability is remotely exploitable, no authentication required, low attack complexity. Public exploit code available.
NLTK Downloader before 3.4.5 is vulnerable to a directory traversal, allowing attackers to write arbitrary files via a ../ (dot dot slash) in an NLTK package (ZIP archive) that is mishandled during. Rated high severity (CVSS 7.5), this vulnerability is remotely exploitable, no authentication required, low attack complexity. Public exploit code available.