| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| 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. |
| NLTK (Natural Language Toolkit) is a suite of open source Python modules, data sets, and tutorials supporting research and development in Natural Language Processing. Prior to 3.10.0-rc1, nltk.data.load() in NLTK is vulnerable to path traversal via URL-encoded path separators and traversal segments when using the nltk: URL scheme. The unsafe-path regex check is performed before url2pathname() decodes the %xx sequences (a classic decode-after-check / TOCTOU-style flaw), allowing an attacker to bypass the protection documented in NLTK's SECURITY.md and read arbitrary files from the filesystem. While literal traversal strings such as ../../../etc/passwd are correctly blocked, encoded variants such as %2fetc%2fpasswd, %2e%2e%2f..., and ..%2f..%2f slip past the regex and are subsequently decoded into a real filesystem path. This vulnerability is fixed in 3.10.0-rc1. |
| NLTK versions before 3.10.3 contain a filesystem containment bypass vulnerability in the Downloader.download and Downloader.incr_download methods that allows attackers to overwrite files outside the install root through pre-existing hardlinks. Attackers with write access to a shared downloader directory can create hardlinks pointing to outside-root files that are then overwritten during normal package extraction, mutating files outside the intended install tree. |
| nltk versions before 3.10.2 contain a symlink-based arbitrary file read vulnerability in IPIPANCorpusReader methods that bypass nltk.pathsec validation entirely. Attackers can place a symlink in the corpus root directory and read arbitrary files accessible to the process by calling channels(), domains(), categories(), or fileids() methods with the symlink filename. |
| NLTK before 3.10.3 contains a regular expression denial of service vulnerability in Pl196xCorpusReader that allows attackers to cause quadratic CPU consumption by supplying malformed TEI blocks with many unmatched opening tags. Attackers can exploit lazy regex patterns in the read_block method through public APIs like words() and tagged_words() to force repeated rescans and achieve near-quadratic runtime growth. |
| NLTK before 3.10.3 contains an uncontrolled recursion vulnerability in nltk.featstruct.FeatStructReader that allows unauthenticated attackers to cause a denial of service by supplying deeply nested feature-structure input. Attackers can craft trivial payloads with nested brackets that exceed Python's recursion limit and raise an unhandled RecursionError, crashing applications that parse user-supplied feature structures or feature grammars. |
| nltk PorterStemmer in versions <= 3.10.2 (fixed in 3.10.3) contains an inefficient-algorithmic-complexity denial of service in PorterStemmer.stem(). The _is_consonant() helper walks backward over the entire run of trailing 'y' characters on every call, and _measure() invokes it for each stem position, causing O(n^2) behavior. A single ~20-50 KB untrusted token consisting of a long run of the letter 'y' followed by a matching suffix (e.g., 'ness') can pin a CPU core for seconds to minutes, causing availability impact. |
| 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). |
| NLTK before 3.10.3 fails to validate JVM options passed through the per-call options parameter in the java() function, allowing attackers to inject dangerous JVM flags. Attackers can supply malicious options like -agentpath, -javaagent, or @argfile to Stanford wrapper classes to achieve arbitrary code execution. |
| NLTK before 3.10.3 contains a remote code execution vulnerability in AllowlistUnpickler that validates only the pickle module string and not the global name, allowing attackers to resolve dotted names by attribute traversal to callables outside the allowlisted namespace. Attackers can craft untrusted transition-parser models that execute arbitrary commands when TransitionParser.parse loads the model through allowlisted_pickle_load. |
| NLTK through 3.10.3 contains a path traversal vulnerability in model-artifact APIs that bypass pathsec enforcement by using raw file operations on caller-controlled paths. Attackers can read or write files outside allowed sandbox roots through TransitionParser, AveragedPerceptron, PerceptronTagger, and maxent parameter APIs when pathsec is enabled. |
| NLTK versions before 3.10.3 contain a quadratic CPU exhaustion vulnerability in XMLCorpusView._read_xml_fragment() that rescans accumulated XML fragments on every 1 KiB block read. Attackers can provide malformed XML corpus files to cause severe CPU consumption and denial of service through affected readers like BNCCorpusReader. |
| 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. |
| NLTK versions before 3.10.0 contain a regular expression denial of service vulnerability in Text.findall() and TokenSearcher.findall() methods that accept user-supplied regular expressions without validation or timeout. Attackers can supply crafted regex patterns that cause catastrophic backtracking, resulting in indefinite CPU saturation and denial of service to all users of the Python process. |
| 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. |
| NLTK before 3.10.3 contains a regular expression denial of service (ReDoS) vulnerability in the tgrep module. The _tgrep_node_action function compiles user-supplied regular expressions embedded in /regex/ pattern nodes and executes them via re.search against tree node labels without any validation or timeout. An attacker who controls the tgrep pattern (e.g., via tgrep_positions() or tgrep_compile() exposed to external input) can supply a pattern that triggers catastrophic backtracking, causing indefinite CPU saturation that blocks the Python process. |
| NLTK versions before 3.10.3 contain a path sandbox bypass vulnerability in corpus-reader constructors that allows attackers to read files outside the intended data root. Attackers can supply arbitrary corpus root paths to LinThesaurusCorpusReader and PanLexLiteCorpusReader constructors to access filesystem content and SQLite databases outside the pathsec sandbox boundary. |
| NLTK versions before 3.10.3 contain a path traversal vulnerability in corpus readers that reopen root-derived paths using built-in open() instead of nltk.pathsec.open(), allowing symlinks to escape trusted roots. Attackers who stage symlinked corpus files under a trusted data root can disclose outside-root content through normal corpus reader methods like channels(), domains(), and synonyms(). |
| 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. |
| NLTK before 3.10.0 (affected versions <=3.9.4) contains an unsafe pickle deserialization vulnerability in the TransitionParser.parse() method (nltk/parse/transitionparser.py). The method calls pickle_load() with the default restricted=False, routing deserialization through WarningUnpickler, which does not override find_class() and therefore permits arbitrary class resolution. When an application loads an attacker-crafted model file, embedded pickle gadget chains execute arbitrary Python code with the privileges of the user running the application. NLTK provides a RestrictedUnpickler for safe deserialization, but it is not used by production code paths. Fixed in 3.10.0. |
