Comparison Overview
Tata Electronics
Tata Electronics
Bengaluru , IN
Last Update: 13/09/2026
Tata Electronics is a prominent global player in the electronics manufacturing industry, with fast-emerging capabilities in Electronics Manufacturing Services, Semiconductor Assembly and Test, Semiconductor Foundry, and Design Services. Established in 2020 as a greenf...
Grendene S/A
Av. Pedro Grendene, 131. Bairro Volta Grande, Farroupilha, 95180-000, BR
Last Update: 12/09/2026
Se você deseja construir uma carreira em uma das maiores empresas do Brasil, a Grendene é o seu lugar. Se você quer estar em uma empresa diferente, com criatividade brasileira, tecnologia global e inovação constante, faça parte da nossa equipe. Se você busca desen...
Compliance Ranges Comparison
Tata Electronics
Grendene S/A
Benchmark & Cyber Underwriting Signals
Incidents vs Manufacturing Industry Avg (This Year)
Tata Electronics has 20.0% fewer incidents than the average of same-industry companies with at least one recorded incident.
Incidents vs Manufacturing Industry Avg (This Year)
No incidents recorded for Grendene S/A in 2026.
Incident History - Tata Electronics (X = Date, Y = Severity)
Tata Electronics cyber incidents detection timeline including parent company and subsidiaries.
Incident History - Grendene S/A (X = Date, Y = Severity)
Grendene S/A cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents
Tata Electronics
Grendene S/A
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.