| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| 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 3.10.4, nltk.parse.dependencygraph.dot2img resolves the Graphviz dot executable through PATH but invokes the resulting absolute executable without routing through spawn_trusted, so resolve_trusted_executable ownership and writability validation and safe_env loader environment scrubbing do not run. A local low-privileged attacker who can write to a directory on a POSIX victim's PATH can plant or replace dot, and code executes as the victim when dot2img is called directly or DependencyGraph.repr_svg renders a graph. The current-working-directory-only bare-name vector is blocked and is not this vulnerability; this issue is the residual writable absolute PATH element bypass after CVE-2026-78680. This issue is fixed in version 3.10.4. |
| NLTK from 3.10.0 before 3.10.4 contains an arbitrary file read vulnerability in BllipParser that allows attackers to open files outside NLTK data roots by supplying unvalidated model paths. Attackers controlling parser_model, reranker_features, reranker_weights, or from_unified_model_dir() input can make the bllipparser C extension read sensitive files or block on FIFOs and devices. |
| NLTK before 3.10.4 contains a path traversal vulnerability in save_maxent_params() and load_maxent_params() that bypasses the pathsec filesystem restriction mechanism. Attackers who control the tab_dir argument can read or overwrite model parameter files outside permitted data roots, because the functions call Python's built-in open() directly. |
| NLTK before 3.10.4 contains a quadratic-time denial of service vulnerability in ConllCorpusReader._get_srl_instances that allows remote attackers to exhaust CPU through nested span rescans. Attackers can supply a crafted CoNLL SRL corpus with many predicates and span columns, placing the head span last, to pin a core for minutes. |
| NLTK before 3.10.4 contains a denial of service vulnerability in Tree.chomsky_normal_form that allows remote attackers to exhaust CPU through quadratic-time right-factor binarization using list.pop(0). Attackers can supply a wide flat treebank tree parsed by Tree.fromstring to force tens of seconds of single-threaded CPU consumption, blocking the processing thread. |
| NLTK before 3.10.4 contains a denial of service vulnerability in the CCG lexicon parser fromstring that allows remote attackers to exhaust CPU by supplying wide inputs. Attackers can submit lexicon text with long flat bracket bodies or operator chains, triggering quadratic string re-slicing in matchBrackets and augParseCategory that blocks worker threads. |
| NLTK from 3.2.5 before 3.10.4 contains an algorithmic complexity vulnerability in TreebankWordTokenizer.span_tokenize that allows remote attackers to cause quadratic CPU consumption through repeated list.pop(0) calls. Attackers can submit long runs of double-quote characters to services span-tokenizing untrusted text, exhausting a CPU core and degrading availability. |
| NLTK from 3.6 before 3.10.4 contains an algorithmic complexity vulnerability in LegalitySyllableTokenizer.tokenize that allows remote attackers to exhaust CPU by supplying long all-vowel tokens. Attackers can submit a token such as a long run of vowels, causing the unguarded onset reversal loop to perform quadratic work and deny service to syllabification components. |
| NLTK from 3.9.4 before 3.10.4 contains a symlink following vulnerability in nltk.sem.chat80.sql_query() that bypasses the pathsec data-root sandbox containment check. Attackers who can write into a trusted NLTK data root can plant a symbolic link to read SQLite databases outside the sandbox. |
| NLTK before 3.10.4 contains an uncontrolled resource consumption vulnerability in SteppingRecursiveDescentParser.parse() that lacks any max_time deadline or step limit. Attackers influencing the grammar can supply an ambiguous self-embedding grammar and short token input to force unbounded top-down search, pinning CPU cores and exhausting worker pools. |
| NLTK from 3.10.0 before 3.10.4 contains a symlink escape vulnerability in YCOECorpusReader that allows attackers to read files outside the corpus root by planting psd or pos directory symlinks. Attackers controlling a YCOE corpus can make parsed_sents() and tagged_words() return file content from other corpora or temporary files within the NLTK data sandbox. |
| 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 through 3.10.3 contains a path traversal vulnerability in WekaClassifier that allows attackers to bypass nltk.pathsec containment by supplying unvalidated model paths. Attackers controlling the model_filename or model argument can make the weka JVM write files via -d or probe files via -l outside allowed data roots. |
| In nltk version 3.9.4, the `nltk.downloader.Downloader._download_package()` function writes downloaded package bytes to disk and may extract them before enforcing SHA-256 or MD5 checksum validation. This allows an attacker to tamper with the package response body for `info.url` through a compromised mirror, malicious proxy, or other source-substitution condition, leading to the installation of attacker-controlled package bytes. The vulnerability can result in malicious corpus or model content being trusted by downstream users or applications. |
| This CVE ID has been rejected or withdrawn by its CVE Numbering Authority. |
| 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 (Natural Language Toolkit) is a suite of open source Python modules, data sets, and tutorials supporting research and development in Natural Language Processing. In versions 3.9.3 and prior, `nltk.app.wordnet_app` allows unauthenticated remote shutdown of the local WordNet Browser HTTP server when it is started in its default mode. A simple `GET /SHUTDOWN%20THE%20SERVER` request causes the process to terminate immediately via `os._exit(0)`, resulting in a denial of service. Commit bbaae83db86a0f49e00f5b0db44a7254c268de9b patches the issue. |
| A vulnerability in `nltk.downloader` in nltk/nltk versions <= 3.9.4 allows for cross-package resource and model poisoning. The downloader extracts package archives into shared namespaces such as `corpora/` and `taggers/` instead of package-isolated roots, and validates package integrity only after the archive has been written and extracted. This design flaw enables one package to overwrite another package's trusted resources within the same namespace, making the changes immediately active through ordinary NLTK APIs. This issue persists across fresh interpreter restarts and can affect downstream workflows, including machine learning pipelines and reproducibility-sensitive environments. |
| A Server-Side Request Forgery (SSRF) vulnerability exists in nltk/nltk versions 3.9.4 and the current develop branch. The `nltk.pathsec.validate_network_url()` function, intended to prevent SSRF by rejecting internal network addresses, fails to reject IPs in the RFC 6598 shared address space (`100.64.0.0/10`). This occurs because Python's `ipaddress` module does not classify such addresses as `is_private` or `is_global`, and the current guard only checks `is_private` and a few explicit categories. An attacker who can influence a URL passed to NLTK's network-loading helpers can exploit this vulnerability to make a strict-mode application send requests to shared-address-space hosts, potentially exposing non-public infrastructure reachable from the application host. The impact is limited to SSRF-style confidentiality exposure, with no code execution claimed. |
| 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. |
