Is glin-profanity safe?
What glin-profanity does
glin-profanity is a JavaScript and TypeScript library that detects and filters profanity in text. It is published on npm by GLINCKER, checks words in 24 languages, can catch leetspeak spellings and Unicode lookalike characters, and can replace matches with a string such as ***. It offers checkProfanity, isProfane, a configurable Filter class with an optional result cache, and a useProfanityChecker hook for React. Machine-learning toxicity detection, OCR and integrations for OpenAI, LangChain and the Vercel AI SDK rely on optional peer dependencies. The latest npm release declares no runtime dependencies and no install scripts. Before installing, add only the optional peer packages for the features you use, such as @tensorflow/tfjs for toxicity detection.
- Node.js dynamic code execution
- Node.js network egress
What to do: Nothing here argues against installing it. Grant the capabilities it lists only if you expect the tool to need them.
glin-profanity is an npm package analyzed by SkillTotal's deterministic static scanner. The scan found no malicious indicators. It can: dynamic code execution and network egress — capabilities are what the code can do, not a verdict on intent. Risk score 0/100 (low).
glin-profanity 4.0.1
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Automated static-analysis result. It can contain false positives and false negatives, and is not a claim about the intent of glin-profanity's authors. Report a false positive.
Behavioral traits
How this component maps to the CSA agentic threat model. Descriptive — it never affects the risk score.
Findings (2)
The code turns strings into live code at runtime (eval / new Function / exec).
return new Function("m", "return import(m)")(moduleName);return new Function("m", "return import(m)")(moduleName);Why it matters: If those strings aren't fixed and trusted, they become a way to run arbitrary code.
Fix: Avoid evaluating dynamically constructed code; if unavoidable, ensure the input is a trusted constant and never derived from external data.
The component makes outbound network requests.
const response = await fetch(`${baseUrl}${endpoint}`, {const response = await fetch(`${baseUrl}${endpoint}`, {const response = await fetch(`${baseUrl}${endpoint}`, {const response = await fetch(`${baseUrl}${endpoint}`, {const response = await fetch(`${baseUrl}/audio/transcriptions`, {const response = await fetch(
const response = await fetch(`${baseUrl}/audio/transcriptions`, {const response = await fetch(
const response = await fetch(`${baseUrl}/audio/transcriptions`, {const response = await fetch(
const response = await fetch(`${baseUrl}/audio/transcriptions`, {const response = await fetch(
pattern: /(?:mailgun)[_\-. ]?(?:webhook[_\-. ]?)?(?:signing[_\-. ]?)?key['":\s=]+([A-Za-z0-9_\-]{32,512})/i,pattern: /(?:mailgun)[_\-. ]?(?:webhook[_\-. ]?)?(?:signing[_\-. ]?)?key['":\s=]+([A-Za-z0-9_\-]{32,512})/i,Why it matters: Usually legitimate, but confirm the destinations are expected and no sensitive data leaves.
Fix: Confirm the destination hosts are expected and that no sensitive data is sent off-host.
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