NLTK versions before 3.10.3 contain a remote code execution vulnerability in allowlisted pickle loaders that trust entire module namespaces instead of specific safe callables. Attackers can craft malicious pickle payloads invoking dangerous in-namespace functions like ReppTokenizer._execute and numpy.f2py.crackfortran.myeval through pickle REDUCE to execute arbitrary commands during model or tokenizer artifact loading.
CVSS Score
9.3
EPSS Score
0.012
Published
2026-08-25
NLTK before 3.10.3 contains a server-side request forgery vulnerability in nltk.pathsec.urlopen (and callers nltk.data.load, nltk.downloader.Downloader.index/download) when an HTTP proxy is configured. pathsec.urlopen validates the requested hostname locally, but proxy-handler inheritance disables the safe HTTP/HTTPS handlers so the actual fetch is performed by the proxy against a destination that is never re-validated. An attacker can supply a validated public URL that the proxy forwards to an internal loopback-only service, allowing disclosure of internal HTTP resources, loading of forged downloader indexes, and installation of attacker-chosen package content.
CVSS Score
8.7
EPSS Score
0.002
Published
2026-08-25
NLTK versions before 3.10.3 use xml.etree.ElementTree to parse XML in multiple modules, which honors entity declarations in document DTDs. Attackers can craft XML payloads with nested entity declarations that expand from hundreds of bytes to megabytes in memory, causing denial of service.
CVSS Score
8.7
EPSS Score
0.003
Published
2026-08-25
NLTK versions before 3.9.4 contain a symlink escape vulnerability in CorpusReader.open() that allows local attackers to read arbitrary files outside the corpus root. The vulnerability exists because path validation is lexical and does not account for symlink resolution, enabling attackers to place symlinks inside the corpus root to access files outside the intended boundary.
CVSS Score
8.6
EPSS Score
0.001
Published
2026-08-22
NLTK before 3.10.0 (affected versions <= 3.9.4) contains a server-side request forgery (SSRF) vulnerability in the validate_network_url() function in nltk/pathsec.py. The _resolve_hostname() helper catches OSError and ValueError during socket.getaddrinfo() and returns an empty list; when DNS resolution fails, the validation loop executes no IP checks and the function fails open, allowing urlopen() to proceed without validation. An attacker who can trigger DNS resolution failures or use DNS rebinding can bypass SSRF protections and reach restricted network resources, including cloud metadata endpoints (e.g., 169.254.169.254).
CVSS Score
6.9
EPSS Score
0.002
Published
2026-08-22
NLTK versions before 3.9.4 contain an unbounded recursion vulnerability in JSONTaggedDecoder.decode_obj() that allows attackers to cause denial of service by supplying deeply nested JSON structures. Attackers can craft JSON payloads exceeding the recursion limit to trigger an unhandled RecursionError that crashes the Python process.
CVSS Score
8.7
EPSS Score
0.004
Published
2026-08-22
NLTK before 3.9.3 fails to verify file integrity after downloading packages and before extraction in the downloader module. Attackers can perform man-in-the-middle attacks or DNS poisoning to inject malicious package contents that are extracted without validation.
CVSS Score
9.3
EPSS Score
0.001
Published
2026-08-22
NLTK versions before 3.10.0 default to ENFORCE=False in pathsec.py, causing all security validation functions to emit warnings instead of raising exceptions. Attackers can bypass path traversal and pickle deserialization protections by exploiting the disabled security controls that are only active when manually enabled.
CVSS Score
8.7
EPSS Score
0.005
Published
2026-08-22
NLTK (Natural Language Toolkit) before version 3.9.3 contains an eval injection vulnerability in the nltk.collocations module that allows an attacker who controls command-line arguments to execute arbitrary Python code. When collocations.py is invoked directly, the __main__ block passes command-line arguments directly to eval() as suffixes of BigramAssocMeasures without allowlist validation or sanitization, enabling an attacker to supply a Python expression that escapes the intended attribute lookup and executes arbitrary code including OS commands via the os module.
CVSS Score
8.5
EPSS Score
0.002
Published
2026-07-24
In nltk/nltk versions 3.9.3 and earlier, five Stanford interface classes (StanfordPOSTagger, StanfordNERTagger, StanfordParser, StanfordDependencyParser, and StanfordNeuralDependencyParser) are vulnerable to untrusted JAR code execution. These classes accept user-controllable JAR paths and execute them via the `java()` function, which invokes `subprocess.Popen()` without integrity verification. This vulnerability is identical to CVE-2026-0848, which was fixed for StanfordSegmenter by adding SHA256 verification. However, the fix was not applied to these additional classes, leaving them susceptible to arbitrary code execution when loading untrusted JAR files.
CVSS Score
7.8
EPSS Score
0.002
Published
2026-07-04