Comparison Overview
Kraken Technologies Japan
Kraken Technologies Japan
六本木1−6−１, 港区, 106-6028, JP
Last Update: 02/09/2026
Krakenは、エネルギー業界向けの最も信頼され、実績あるオペレーティングシステムです。Utility-Grade AI™と深い業界知見を活かし、ユーティリティ事業者の業務変革とエネルギー移行を支援しています。家庭・法人から大規模産業顧客まで、世界9,000万以上のアカウントをサポートし、最大40％の業務効率化、顧客満足度を3倍に改善といった成果を実現。東京ガス、EDF Energy、E.ON Next、Octopus Energy、Origin、Plenitude、National Gridなど、世界の主要ユーティリティに採用されて...
DoorDash
San Francisco, US
Last Update: 12/09/2026
At DoorDash, our mission to empower local economies shapes how our team members move quickly and always learn and reiterate to support merchants, Dashers and the communities we serve. We are a technology and logistics company that started with door-to-door delivery, and...
Compliance Ranges Comparison
Kraken Technologies Japan
DoorDash
Benchmark & Cyber Underwriting Signals
Incidents vs Software Development Industry Avg (This Year)
No incidents recorded for Kraken Technologies Japan in 2026.
Incidents vs Software Development Industry Avg (This Year)
DoorDash has 2.91% fewer incidents than the average of all companies with at least one recorded incident.
Incident History - Kraken Technologies Japan (X = Date, Y = Severity)
Kraken Technologies Japan cyber incidents detection timeline including parent company and subsidiaries.
Incident History - DoorDash (X = Date, Y = Severity)
DoorDash cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents
Kraken Technologies Japan
DoorDash
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.