feat: nsfw detection for images attached

events/anti-nsfw.ts

@@ -0,0 +1,63 @@
+import { EventType, eventModule } from '@sern/handler';
+import { ActionRowBuilder, ButtonBuilder, ButtonStyle, EmbedBuilder, Message, TextChannel } from 'discord.js';
+import * as tf from '@tensorflow/tfjs-node'
+import axios from 'axios';
+import { nsfwModel } from '../index.js';
+
+export default eventModule({
+	type: EventType.Discord,
+	name: 'messageCreate',
+	execute(message: Message) {
+        message.attachments.forEach(async (attachment) => {
+			switch (attachment.contentType) {
+				case 'image/png':
+					break;
+				case 'image/jpeg':
+					break;
+				default:
+					return;
+			}
+			const pic = await axios.get(attachment.url,
+				{ responseType: 'arraybuffer' }
+			)
+			const image = tf.node.decodeImage(pic.data, 3) as tf.Tensor3D
+			// @ts-ignore
+			const predictions = await nsfwModel.classify(image)
+			
+			switch (predictions[0].className) {
+				case 'Hentai':
+				case 'Porn':
+					if (predictions[0].probability > 0.75) {
+						const embed = new EmbedBuilder()
+							.setTitle(`Se ha detectado una imagen NSFW en tus adjuntos.`)
+							.setDescription('Por eso, se ha eliminado tu mensaje.\nPor si es un falso positivo, te vamos a dejar abajo el contenido del mensaje para recuperarlo.')
+							.setFields(
+								{ name: 'Contenido del mensaje', value: message.content || '(nada)' },
+								{ name: 'Tipo', value: predictions[0].className.toString() },
+							)
+							.setFooter({ text: 'Esta detección ha sido automatizada.' })
+						const modLogsEmbed = new EmbedBuilder()
+							.setAuthor({ name: message.author.username, iconURL: message.author.displayAvatarURL() })
+							.setTitle(`Se ha detectado una imagen NSFW en los adjuntos de un mensaje.`)
+							.setDescription('Aquí está toda la información:')
+							.setFields(
+								{ name: 'Contenido del mensaje', value: message.content || '(nada)' },
+								{ name: 'Tipo', value: predictions[0].className.toString() },
+							)
+							.setFooter({ text: 'Esta detección ha sido automatizada.' })
+						const button = new ActionRowBuilder<ButtonBuilder>()
+							.addComponents(
+								new ButtonBuilder()
+									.setLabel('Imagen adjuntada que saltó las alarmas')
+									.setURL(attachment.url)
+									.setStyle(ButtonStyle.Link)
+							)
+						await message.delete()
+						await message.author.send({ embeds: [embed], components: [button] })
+						await (await message.client.channels.fetch(process.env.MODLOGS_CHANNEL!) as TextChannel).send({ embeds: [modLogsEmbed], components: [button] })
+					}
+					break;
+			}
+        })
+    },
+});

index.ts

@@ -10,6 +10,8 @@ import birthdays from './util/birthdays.js';
 import twitternotifications from './util/twitternotifications.js';
 import webserver from './util/web/webserver.js'
 import minecraftstatus from './util/minecraftstatus.js';
+import * as tf from '@tensorflow/tfjs-node'
+import * as nsfw from 'nsfwjs'
 // import giveawaychecker from './util/giveawaychecker.js';
 
 let devMode: boolean
@@ -33,6 +35,9 @@ const client = new Client({
 	],
 });
 
+tf.enableProdMode()
+export const nsfwModel = await nsfw.load()
+
 mongoose.connect(process.env.MONGODB!).then(() => {
 	console.log('Connected to MongoDB');
 });

package.json

@@ -37,6 +37,7 @@
     "@discordjs/voice": "^0.14.0",
     "@napi-rs/canvas": "^0.1.30",
     "@sern/handler": "^2.5.1",
+    "@tensorflow/tfjs-node": "^3.20.0",
     "axios": "^1.1.3",
     "dayjs": "^1.11.6",
     "discord-tictactoe": "^4.0.0",
@@ -50,6 +51,7 @@
     "got": "^12.5.3",
     "libsodium-wrappers": "^0.7.10",
     "mongoose": "^6.5.1",
+    "nsfwjs": "^2.4.2",
     "pretty-seconds-spanish": "^2.1.1",
     "rockpaperscissors-checker": "^1.2.0",
     "set-interval-async": "^3.0.2",