Affected Technology

GitHub incidents

GitHub AI tooling and Copilot security

Matching incidents

10

Technology type

Vendor

News NEW

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

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,"

CircleCIGitHubGitLabGoogleJenkinsMicrosoft
Low severity NEW

LiteLLM Security Incident

### Summary A server-side request forgery in LiteLLM Proxy lets an authenticated caller redirect the proxy's outbound request to a host of their choosing by smuggling an `api_base` inside the `user_config` request body, bypassing the existing parameter guard. ### Details LiteLLM Proxy validates request bodies with `is_request_body_safe`, which blocks the `api_base` and `base_url` parameters but does not cover `user_config`. The `user_config` object is used to build the outbound router for a request, so a caller can place an `api_base` inside it and reach an arbitrary host. The guard only inspected the two top-level keys, so the same `api_base` nested inside `user_config` was never checked. Exploitation requires a valid virtual key. ### Impact An authenticated caller can make the proxy issue server-side requests to internal or external hosts of their choosing, reaching endpoints the caller cannot otherwise access. ### Affected / Patched Affected: `

litellmvulnerabilityLiteLLM ProxyBerriAI/litellmreleased
Low severity STABLE

Claude Security Vulnerability

Anthropic's Claude Opus 4.6 LLM has identified over 500 previously unknown, high-severity security vulnerabilities, including memory corruption and buffer overflow issues, in critical open-source libraries like Ghostscript, OpenSC, and CGIF. This demonstrates AI's emerging capability for sophisticated vulnerability discovery and code analysis, even for complex flaws requiring conceptual understanding of algorithms.

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