Comparison Overview
Hypertronics
Hypertronics
16 Brent Drive, Hudson, MA, 01749, US
Last Update: 02/02/2026
Hypertac is a world-leading provider of high performance interconnect solutions and electrical connectors for demanding medical, military, aerospace, industrial, mass transit, test & measurement electronics markets. Hypertac’s extensive product portfolio is built upon t...
Legrand
128 avenue du Marechal de Lattre de Tassigny, Limoges, 87045, FR
Last Update: 12/09/2026
Legrand is a global specialist in electrical and digital building infrastructures, dedicated to supporting technological, societal and environmental change around the globe. Our purpose is to improve lives by transforming the spaces where people live, work and meet by...
Compliance Ranges Comparison
Hypertronics
Legrand
Benchmark & Cyber Underwriting Signals
Incidents vs Appliances, Electrical, and Electronics Manufacturing Industry Avg (This Year)
No incidents recorded for Hypertronics in 2026.
Incidents vs Appliances, Electrical, and Electronics Manufacturing Industry Avg (This Year)
No incidents recorded for Legrand in 2026.
Incident History - Hypertronics (X = Date, Y = Severity)
Hypertronics cyber incidents detection timeline including parent company and subsidiaries.
Incident History - Legrand (X = Date, Y = Severity)
Legrand cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents
Hypertronics
Legrand
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.