Comparison Overview
Advantest
Advantest
Shin Marunouchi Center Bldg.,, Tokyo, 100-0005, JP
Last Update: 03/07/2026
Advantest (TSE: 6857) is the leading manufacturer of automatic test and measurement equipment used in the design and production of semiconductors for applications including 5G communications, the Internet of Things (IoT), autonomous vehicles, high performance computing ...
AMD
2485 Augustine Drive, Santa Clara, 95054, US
Last Update: 10/09/2026
We care deeply about transforming lives with AMD technology to enrich our industry, our communities, and the world. Our mission is to build great products that accelerate next-generation computing experiences – the building blocks for the data center, artificial intelli...
Compliance Ranges Comparison
Advantest
AMD
Benchmark & Cyber Underwriting Signals
Incidents vs Semiconductor Manufacturing Industry Avg (This Year)
Advantest has 58.33% fewer incidents than the average of same-industry companies with at least one recorded incident.
Incidents vs Semiconductor Manufacturing Industry Avg (This Year)
AMD has 191.26% more incidents than the average of all companies with at least one recorded incident.
Incident History - Advantest (X = Date, Y = Severity)
Advantest cyber incidents detection timeline including parent company and subsidiaries.
Incident History - AMD (X = Date, Y = Severity)
AMD cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents
Advantest
AMD
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.