Comparison Overview
Unimed-Rio
Unimed-Rio
Av. Ayrton Senna, 2.500 Barra da Tijuca - Rio de Janeiro - RJ, Rio de Janeiro, Rio de Janeiro, undefined, BR
Last Update: 03/03/2026
A Unimed-Rio é o resultado de uma trajetória de empreendedorismo, que teve início em 1972 e hoje conta com 5.650 sócios e mais de 1 milhão de clientes em todo Brasil. Integramos o maior sistema de saúde da América Latina e somos líderes do mercado de planos de saúde do ...
Sharp HealthCare
8695 Spectrum Center Blvd., San Diego, 92123, US
Last Update: 05/09/2026
Sharp HealthCare is a not-for-profit health care system based in San Diego, California, with four acute care hospitals, three specialty hospitals, three medical groups and a health plan. We provide medical services in virtually all fields of medicine, including primary ...
Compliance Ranges Comparison
Unimed-Rio
Sharp HealthCare
Benchmark & Cyber Underwriting Signals
Incidents vs Hospitals and Health Care Industry Avg (This Year)
No incidents recorded for Unimed-Rio in 2026.
Incidents vs Hospitals and Health Care Industry Avg (This Year)
No incidents recorded for Sharp HealthCare in 2026.
Incident History - Unimed-Rio (X = Date, Y = Severity)
Unimed-Rio cyber incidents detection timeline including parent company and subsidiaries.
Incident History - Sharp HealthCare (X = Date, Y = Severity)
Sharp HealthCare cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents
Unimed-Rio
Sharp HealthCare
FAQ
Latest Global CVEs
vLLM through 0.29.0 fails to properly clean up decode-side metadata for rejected inference requests in prefill/decode disaggregated deployments. Remote attackers can submit requests with max_tokens=0 to exhaust decode-worker memory without bound until the worker restarts.
- https://github.com/vllm-project/vllm
- https://github.com/vllm-project/vllm/blob/v0.29.0/vllm/distributed/kv_transfer/kv_connector/v1/nixl/push_worker.py#L162-L181
- https://github.com/vllm-project/vllm/pull/55677
- https://www.vulncheck.com/advisories/vllm-through-0.29.0-memory-exhaustion-via-rejected-requests
redis-parser through 3.0.0 contains a denial of service vulnerability in the RESP protocol parser that allows malicious Redis endpoints to crash the client process through unbounded recursion on nested arrays. Attackers can send crafted RESP byte streams with repeated array headers that exhaust the V8 call stack, causing an uncaught RangeError that terminates the Node.js process without triggering error handling callbacks.
- https://github.com/NodeRedis/node-redis-parser
- https://github.com/NodeRedis/node-redis-parser/blob/701655430f5f7d9ca00892a02f7eefcbc1193a98/lib/parser.js#L204-L213
- https://github.com/NodeRedis/node-redis-parser/blob/701655430f5f7d9ca00892a02f7eefcbc1193a98/lib/parser.js#L291-L306
- https://github.com/redis/ioredis/issues/2108
- https://www.vulncheck.com/advisories/redis-parser-through-3.0.0-denial-of-service-via-unbounded-recursion
Improper neutralization of special elements in output used by a downstream component ('injection') in Azure Cosmos DB allows an authorized attacker to elevate privileges over a network.
Server-side request forgery (ssrf) in Azure AI Foundry allows an unauthorized attacker to elevate privileges over a network.
Missing authentication for critical function in Azure AI Foundry allows an unauthorized attacker to elevate privileges over a network.