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The HTMLSectionSplitter class in langchain-text-splitters is vulnerable to XML External Entity (XXE) attacks due to unsafe XSLT parsing. This vulnerability arises because the class allows the use of arbitrary XSLT stylesheets, which are parsed using lxml.etree.parse() and lxml.etree.XSLT() without any hardening measures. In lxml versions up to 4.9.x, external entities are resolved by default, allowing attackers to read arbitrary local files or perform outbound HTTP(S) fetches. In lxml versions 5.0 and above, while entity expansion is disabled, the XSLT document() function can still read any URI unless XSLTAccessControl is applied. This vulnerability allows remote attackers to gain read-only access to any file the LangChain process can reach, including sensitive files such as SSH keys, environment files, source code, or cloud metadata. No authentication, special privileges, or user interaction are required, and the issue is exploitable in default deployments that enable custom XSLT.

ESET warns of fake Signal and ToTok apps spreading Android spyware in the UAE, stealing contacts, messages, and chat backups from users.

### Impact Anyone with VIEW access to a user profile can create a token for that user. If that XWiki instance is configured to allow token authentication, it allows authentication with any user (since users are very commonly viewable, at least to other registered users). ### Patches Version 2.18.2. ### Workarounds The only workaround is to disable token access. ### References * https://jira.xwiki.org/browse/OIDC-240 * https://github.com/xwiki-contrib/oidc/commit/d90d717172283aaa96bb5bb44e357f910ae64adb ### For more information If you have any questions or comments about this advisory: * Open an issue in [Jira XWiki.org](https://jira.xwiki.org/) * Email us at [Security Mailing List](mailto:security@xwiki.org)

Attackers are using realistic-looking 1Password emails to trick users into handing over their vault logins.

A misconfigured database belonging to a pet insurance company, "Rainwalk Pet Insurance," exposed sensitive PII and veterinary claim data. The data exposure reveals new fraud tactics, including microchip and reimbursement scams.

### Summary User-controlled input flows to an unsafe implementaion of a dynamic Function constructor , allowing a malicious actor to run JS code in the context of the host (not sandboxed) leading to RCE. ### Details When creating a new `Custom MCP` Chatflow in the platform, the MCP Server Config displays a placeholder hinting at an example of the expected input structure: ```json { "command": "npx", "args": ["-y", "@modelcontextprotocol/server-filesystem", "/path/to/allowed/files"] } ``` Behind the scene, a `POST` request to `/api/v1/node-load-method/customMCP` is sent with the provided MCP Server Config, with additional parameters (excluded for brevity): ```json { ...SNIP... "inputs":{ "mcpServerConfig":{ "command":"npx", "args":[ "-y", "@modelcontextprotocol/server-filesystem", "/path/to/allowed/files" ] } }, "loadMethod":"listActions" ...SNIP... } ``` Sending the same request with the para...

The cyber world never hits pause, and staying alert matters more than ever. Every week brings new tricks, smarter attacks, and fresh lessons from the field. This recap cuts through the noise to share what really matters—key trends, warning signs, and stories shaping today’s security landscape. Whether you’re defending systems or just keeping up, these highlights help you spot what’s coming

In the era of rapidly advancing artificial intelligence (AI) and cloud technologies, organizations are increasingly implementing security measures to protect sensitive data and ensure regulatory compliance. Among these measures, AI-SPM (AI Security Posture Management) solutions have gained traction to secure AI pipelines, sensitive data assets, and the overall AI ecosystem. These solutions help

As developers increasingly lean on AI-generated code to build out their software—as they have with open source in the past—they risk introducing critical security failures along the way.

Discord confirms a data breach via a third-party vendor, exposing government-issued photo IDs, names, emails, and limited billing data of users who contacted customer support. Learn the full risk.