Comparison Overview
Panasonic India
Panasonic India
Gurgaon, 122002, IN
Last Update: 04/01/2026
Panasonic is a diversified technology company, and offers complete solutions for consumers in living spaces and in their community and business. We provide a wide range of integrated solutions in consumer electronics and appliances such as televisions, cameras, home a...
Keysight Technologies
1400 Fountaingrove Pkwy, Santa Rosa, California, US, 95403
Last Update: 09/09/2026
Keysight empowers innovators to explore, design, and bring world-changing technologies to life. As the industry’s premier global innovation partner, Keysight’s software-centric solutions serve engineers across the design and development environment, enabling them to del...
Compliance Ranges Comparison
Panasonic India
Keysight Technologies
Benchmark & Cyber Underwriting Signals
Incidents vs Appliances, Electrical, and Electronics Manufacturing Industry Avg (This Year)
No incidents recorded for Panasonic India in 2026.
Incidents vs Appliances, Electrical, and Electronics Manufacturing Industry Avg (This Year)
No incidents recorded for Keysight Technologies in 2026.
Incident History - Panasonic India (X = Date, Y = Severity)
Panasonic India cyber incidents detection timeline including parent company and subsidiaries.
Incident History - Keysight Technologies (X = Date, Y = Severity)
Keysight Technologies cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents
Panasonic India
Keysight Technologies
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.