/* * This file is part of the Symfony package. * * (c) Fabien Potencier * * For the full copyright and license information, please view the LICENSE * file that was distributed with this source code. */ namespace Symfony\Component\String; if (!\function_exists(u::class)) { function u(?string $string = ''): UnicodeString { return new UnicodeString($string ?? ''); } } if (!\function_exists(b::class)) { function b(?string $string = ''): ByteString { return new ByteString($string ?? ''); } } if (!\function_exists(s::class)) { /** * @return UnicodeString|ByteString */ function s(?string $string = ''): AbstractString { $string = $string ?? ''; return preg_match('//u', $string) ? new UnicodeString($string) : new ByteString($string); } } AI Could Generate 10,000 Malware Variants, Evading Detection in 88% of Case – OWASP Jakarta

AI Could Generate 10,000 Malware Variants, Evading Detection in 88% of Case

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AI Could Generate 10,000 Malware Variants, Evading Detection in 88% of Case


Cybersecurity researchers have found that it’s possible to use large language models (LLMs) to generate new variants of malicious JavaScript code at scale in a manner that can better evade detection.
“Although LLMs struggle to create malware from scratch, criminals can easily use them to rewrite or obfuscate existing malware, making it harder to detect,” Palo Alto Networks Unit 42 researchers

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2024-12-23 13:48:00

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