Oklahoma Voice A.I CyberSecurity Scoring
18/03/2026
Access Monitoring Plan
Access Monitoring Plan
No incidents recorded for Oklahoma Voice in 2026.
No incidents recorded for Oklahoma Voice in 2026.
No incidents recorded for Oklahoma Voice in 2026.
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Latest updates, reports, and threat intel affecting the global network.
Laci Henegar, Rogers State University's STEM coordinator, graduated in December with the university's first master's degree in cybersecurity...
Experts warn of more sophisticated 2026 scams, including AI and deepfakes, and offer tips to protect against online fraud and cyberattacks.
Hispanic lawmakers from across the nation convened in Oklahoma City to discuss pressing issues such as affordability, healthcare,...
Returning to his home state of Oklahoma as its chief information security officer, Daniel Langley said he is focusing on agency...
The Oklahoma State Regents for Higher Education approved a request for an additional $426 million from the state Legislature for next budget...
A cybersecurity expert and professor from Oklahoma Christian University joins KOCO to talk about what you need to know ahead of...
Oklahoma has named Daniel Langley, a former Washington state IT official, as Oklahoma's chief information security officer.
The state's next chief information security officer is making the move from his previous position in the Washington state IT shop.
Oklahoma icon Reba is back for her fourth season of "The Voice." The competition will also feature new rules and see the return of some past...
Dify is an open-source LLM app development platform. Prior to 1.16.0, the PUT /console/api/apps/<app_id>/server endpoint in api/controllers/console/app/mcp_server.py used AppMCPServerController.put() to retrieve an AppMCPServer by the client-supplied server ID without verifying that the server belonged to the requested application and tenant. An authenticated workspace member could therefore change another application's MCP server status and parameters, potentially redirecting data or disabling the service. This issue is fixed in version 1.16.0.
vLLM is an inference and serving engine for large language models. Prior to 0.30.0, a caller can use the request-level media_io_kwargs field to select the GLMGA video backend and supply large values for the fps and max_frames options without a strict work ceiling. GLMGA constructs and deduplicates an attacker-sized pre-decode frame-index list, allowing a compact request and tiny valid video to consume disproportionate CPU time and memory in the shared media-loading executor. This issue is fixed in version 0.30.0.
vLLM is an inference and serving engine for large language models. Prior to 0.30.0, the Rust frontend's track_http_metrics middleware records the raw HTTP method token as a Prometheus label for requests reaching registered routes. An unauthenticated attacker can send unique arbitrary method tokens to unguarded routes such as /tokenize, causing Prometheus's Family::get_or_create function to permanently create counter and histogram label sets. Those label sets increase process memory usage and enlarge the /metrics response until the service or monitoring path is exhausted. This issue is fixed in version 0.30.0.
vLLM is an inference and serving engine for large language models. From 0.24.0 until 0.30.0, the Qwen2VLVideoBackend and Qwen3VLVideoBackend classes accept request-level values for the media_io_kwargs.video.max_frames and media_io_kwargs.video.fps fields without enforcing server-side ceilings. An unauthenticated caller can submit these values to the /tokenize endpoint, causing the sampler to decode every frame selected from attacker-controlled video input, consume disproportionate frontend memory, and potentially terminate the API process before scheduling or admission control. The Rust frontend is not affected because it rejects the media_io_kwargs field. This issue is fixed in version 0.30.0.
vLLM is an inference and serving engine for large language models. Prior to 0.30.0, structured-output request failures can escape request-scoped validation and reach the EngineCore fatal-error path. A per-request backend mismatch can re-raise a grammar compilation exception, padding produced by the ngram_gpu speculative-decoding mode can pass a negative token to guidance validation, and the Rust frontend can admit empty structured-output values that the Python frontend rejects, allowing ordinary constrained-generation requests to terminate the shared engine. This issue is fixed in version 0.30.0.
curl -i -X GET 'https://api.rankiteo.com/underwriter-getcompany-history?
linkedin_id=axa' -H 'apikey: YOUR_API_KEY_HERE'
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