
Financial Crimes Enforcement Network, US Treasury
Official LinkedIn account of the Financial Crimes Enforcement Network, a U.S. Treasury bureau. Learn more at www.fincen.gov



Official LinkedIn account of the Financial Crimes Enforcement Network, a U.S. Treasury bureau. Learn more at www.fincen.gov

Work with the Alberta government to build a stronger province for current and future generations. We offer diverse and rewarding employment opportunities in an environment that encourages continuous learning and career growth. We are one of the largest employers in Alberta with over 27,000 employees throughout the province. We are an award winning organization that values respect, accountability, integrity, and excellence. Our employees share a common vision of proudly working together to build a stronger province and make a positive and lasting difference in the lives of Albertans. The people of Alberta enjoy a very high quality of life, including the lowest overall taxes in Canada. www.jobs.alberta.ca Please see our comment policy: https://www.alberta.ca/social-media-comment-policy.aspx
Security & Compliance Standards Overview












Financial Crimes Enforcement Network, US Treasury has 53.85% more incidents than the average of same-industry companies with at least one recorded incident.
No incidents recorded for Government of Alberta in 2025.
Financial Crimes Enforcement Network, US Treasury cyber incidents detection timeline including parent company and subsidiaries
Government of Alberta cyber incidents detection timeline including parent company and subsidiaries
Last 3 Security & Risk Events by Company
vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.11.1, vllm has a critical remote code execution vector in a config class named Nemotron_Nano_VL_Config. When vllm loads a model config that contains an auto_map entry, the config class resolves that mapping with get_class_from_dynamic_module(...) and immediately instantiates the returned class. This fetches and executes Python from the remote repository referenced in the auto_map string. Crucially, this happens even when the caller explicitly sets trust_remote_code=False in vllm.transformers_utils.config.get_config. In practice, an attacker can publish a benign-looking frontend repo whose config.json points via auto_map to a separate malicious backend repo; loading the frontend will silently run the backend’s code on the victim host. This vulnerability is fixed in 0.11.1.
fastify-reply-from is a Fastify plugin to forward the current HTTP request to another server. Prior to 12.5.0, by crafting a malicious URL, an attacker could access routes that are not allowed, even though the reply.from is defined for specific routes in @fastify/reply-from. This vulnerability is fixed in 12.5.0.
Angular is a development platform for building mobile and desktop web applications using TypeScript/JavaScript and other languages. Prior to 21.0.2, 20.3.15, and 19.2.17, A Stored Cross-Site Scripting (XSS) vulnerability has been identified in the Angular Template Compiler. It occurs because the compiler's internal security schema is incomplete, allowing attackers to bypass Angular's built-in security sanitization. Specifically, the schema fails to classify certain URL-holding attributes (e.g., those that could contain javascript: URLs) as requiring strict URL security, enabling the injection of malicious scripts. This vulnerability is fixed in 21.0.2, 20.3.15, and 19.2.17.
Gin-vue-admin is a backstage management system based on vue and gin. In 2.8.6 and earlier, attackers can delete any file on the server at will, causing damage or unavailability of server resources. Attackers can control the 'FileMd5' parameter to delete any file and folder.
Portkey.ai Gateway is a blazing fast AI Gateway with integrated guardrails. Prior to 1.14.0, the gateway determined the destination baseURL by prioritizing the value in the x-portkey-custom-host request header. The proxy route then appends the client-specified path to perform an external fetch. This can be maliciously used by users for SSRF attacks. This vulnerability is fixed in 1.14.0.