Comparison Overview
McKesson
McKesson
6555 State Highway 161, Irving, 75039, US
Last Update: 10/09/2026
Welcome to the official LinkedIn page for McKesson Corporation. Our purpose is Advancing Health Outcomes for All®. Guided by a nearly 200-year legacy, we work with biopharma companies, providers, pharmacies, manufacturers, government entities and others to strengthen ...
EsSalud
120 Jirón Domingo Cueto, Jesús María, 15072, PE
Last Update: 10/09/2026
El Seguro Social de Salud, EsSalud, es un organismo público descentralizado, con personería jurídica de derecho público interno, adscrito al Sector Trabajo y Promoción Social. Tiene por finalidad dar cobertura a los asegurados y sus derechohabientes, a través del otorg...
Compliance Ranges Comparison
McKesson
EsSalud
Benchmark & Cyber Underwriting Signals
Incidents vs Hospitals and Health Care Industry Avg (This Year)
McKesson has 43.88% more incidents than the average of same-industry companies with at least one recorded incident.
Incidents vs Hospitals and Health Care Industry Avg (This Year)
No incidents recorded for EsSalud in 2026.
Incident History - McKesson (X = Date, Y = Severity)
McKesson cyber incidents detection timeline including parent company and subsidiaries.
Incident History - EsSalud (X = Date, Y = Severity)
EsSalud cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents
McKesson
EsSalud
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.