Comparison Overview
Applied Materials Korea
Applied Materials Korea
N/A
Last Update: 19/03/2026
미국 실리콘밸리에 본사를 둔 어플라이드 머티어리얼즈(Applied Materials)의 한국법인 어플라이드 머티어리얼즈 코리아(Applied Materials Korea)는 최첨단 기술과 글로벌 선진 사례를 국내 공유하고, 국내 기업으로부터 부품을 조달 받으며 지난 한국 IT 산업 발전에 기여해 왔습니다. 1989년 설립되어 반도체를 시작으로 1994년 평판 디스플레이, 2008년 태양전지 등 다양한 분야로 사업을 확장하고 있습니다. 어플라이드 코리아 블로그: https://b...
Renesas Electronics
TOYOSU FORESIA, 3-2-24, Koto-ku, Toyosu, 135-0061, JP
Last Update: 13/09/2026
Renesas is an embedded semiconductor solution provider driven by its Purpose ‘To Make Our Lives Easier.’ As the industry’s leading expert in embedded processing with unmatched quality and system-level know-how, we have evolved to provide scalable and comprehensive semic...
Compliance Ranges Comparison
Applied Materials Korea
Renesas Electronics
Benchmark & Cyber Underwriting Signals
Incidents vs Semiconductor Manufacturing Industry Avg (This Year)
No incidents recorded for Applied Materials Korea in 2026.
Incidents vs Semiconductor Manufacturing Industry Avg (This Year)
No incidents recorded for Renesas Electronics in 2026.
Incident History - Applied Materials Korea (X = Date, Y = Severity)
Applied Materials Korea cyber incidents detection timeline including parent company and subsidiaries.
Incident History - Renesas Electronics (X = Date, Y = Severity)
Renesas Electronics cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents
Applied Materials Korea
Renesas Electronics
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.