Comparison Overview
Criteria Labs
Criteria Labs
706 Brentwood, Austin, TX, 78752, US
Last Update: 24/02/2026
Dedicated to providing the best RF space and semiconductor services possible, Criteria Labs can deliver unique solutions to your complex technical problems, improve your project schedules, and complement you with capabilities not internally available. Our in-house Engi...
Samsung Semiconductor
N/A
Last Update: 13/09/2026
Established in 1974 as a subsidiary of Samsung Electronics, we’re proud to be recognized as one of the leading chip manufacturers in the world. Using our knowledge in semiconductor technology, our ambition is to spark the imagination of device manufacturers with top-of-...
Compliance Ranges Comparison
Criteria Labs
Samsung Semiconductor
Benchmark & Cyber Underwriting Signals
Incidents vs Semiconductor Manufacturing Industry Avg (This Year)
No incidents recorded for Criteria Labs in 2026.
Incidents vs Semiconductor Manufacturing Industry Avg (This Year)
Samsung Semiconductor has 1.96% fewer incidents than the average of all companies with at least one recorded incident.
Incident History - Criteria Labs (X = Date, Y = Severity)
Criteria Labs cyber incidents detection timeline including parent company and subsidiaries.
Incident History - Samsung Semiconductor (X = Date, Y = Severity)
Samsung Semiconductor cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents
Criteria Labs
Samsung Semiconductor
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.