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Claimed Bug Bounty Hunter Likely Used LLM to Build PhantomRaven npm Stealer

Claimed Bug Bounty Hunter Likely Used LLM to Build PhantomRaven npm Stealer

Sep 18, 2026 Malware / Cybercrime
A financially motivated threat actor has been linked to the development and distribution of a JavaScript (JS)-based information stealer known as PhantomRaven via the npm package registry. "The developer likely wrote the malware using a large language model (LLM), an assessment made with high confidence based on verbose comments, placeholder code, and statistical token-analysis patterns," CrowdStrike's Counter Adversary Operations said in an analysis published this week. PhantomRaven was first flagged by Koi Security and DCODX in late October 2025, calling attention to a slopsquatting and typosquatted campaign in which more than 100 malicious packages were uploaded to npm to steal authentication tokens, CI/CD secrets, and GitHub credentials from developers' machines. The software supply chain attack used these packages as a cover to retrieve a remote dynamic dependency (RDD) from an external server so that the libraries themselves are not flagged by security ...
PhantomRaven Malware Found in 126 npm Packages Stealing GitHub Tokens From Devs

PhantomRaven Malware Found in 126 npm Packages Stealing GitHub Tokens From Devs

Oct 30, 2025 DevSecOps / Software Security
Cybersecurity researchers have uncovered yet another active software supply chain attack campaign targeting the npm registry with over 100 malicious packages that can steal authentication tokens, CI/CD secrets, and GitHub credentials from developers' machines. The campaign has been codenamed PhantomRaven by Koi Security. The activity is assessed to have begun in August 2025, when the first packages were uploaded to the repository. It has since ballooned to a total of 126 npm libraries, attracting more than 86,000 installs. Some of the packages have also been flagged by the DevSecOps company DCODX -  op-cli-installer (486 Downloads) unused-imports (1,350 Downloads) badgekit-api-client (483 Downloads) polyfill-corejs3 (475 Downloads) eslint-comments (936 Downloads) What makes the attack stand out is the attacker's pattern of hiding the malicious code in dependencies by pointing to a custom HTTP URL, causing npm to fetch them from an untrusted website (in this case,...
GlassWorm Supply-Chain Attack Abuses 72 Open VSX Extensions to Target Developers

GlassWorm Supply-Chain Attack Abuses 72 Open VSX Extensions to Target Developers

Mar 14, 2026 Malware / Threat Intelligence
Cybersecurity researchers have flagged a new iteration of the GlassWorm campaign that they say represents a "significant escalation" in how it propagates through the Open VSX registry. "Instead of requiring every malicious listing to embed the loader directly, the threat actor is now abusing extensionPack and extensionDependencies to turn initially standalone-looking extensions into transitive delivery vehicles in later updates, allowing a benign-appearing package to begin pulling a separate GlassWorm-linked extension only after trust has already been established," Socket said in a report published Friday. The software supply chain security company said it discovered at least 72 additional malicious Open VSX extensions since January 31, 2026, targeting developers. These extensions mimic widely used developer utilities, including linters and formatters, code runners, and tools for artificial intelligence (AI)-powered coding assistants like Clade Code and Google...
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Phantom Squatting Uses AI-Hallucinated Domains for Phishing and Malware

Phantom Squatting Uses AI-Hallucinated Domains for Phishing and Malware

Jul 01, 2026 Artificial Intelligence / Threat Intelligence
Large language models keep inventing web addresses that do not exist. Attackers have started buying those made-up domains before anyone else can, then hosting phishing pages on them to catch traffic that AI tools point their way. Palo Alto Networks' Unit 42 calls the trick phantom squatting , and its new research shows it is already happening in the wild. The reason it matters is trust. Developers and AI assistants increasingly treat the links a model hands back as real. When a model invents a domain that does not exist yet, whoever registers it first inherits all of that misplaced trust, with no phishing email and no malicious ad required. To measure the problem, Unit 42 asked two AI models 685,339 questions about 913 well-known brands across technology, finance, healthcare, government, gambling, and other sectors. The models produced 2.1 million links. Threat intelligence already flagged 13,229 of them as outright malicious, meaning the AI was handing out known-ba...
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