Comparison Overview
TA Instruments
TA Instruments
159 Lukens Drive, New Castle, 19720, US
Last Update: 30/03/2026
TA Instruments provides innovative material characterization instruments that are widely used for research, analysis, and quality control in the evaluation of physical properties. We are the world’s leading supplier of thermal analysis, rheology, and microcalorimetry in...
Havells India Ltd
QRG Towers, 2D, Sector 126, Noida, UP, IN, 201304
Last Update: 12/09/2026
Havells India Limited is a leading FMEG company with a strong global presence, manufacturing a wide range of electrical products for residential, commercial, and industrial use. Key brands include Havells, Havells Studio, Lloyd, Havells Crabtree, Standard Electricals an...
Compliance Ranges Comparison
TA Instruments
Havells India Ltd
Benchmark & Cyber Underwriting Signals
Incidents vs Appliances, Electrical, and Electronics Manufacturing Industry Avg (This Year)
No incidents recorded for TA Instruments in 2026.
Incidents vs Appliances, Electrical, and Electronics Manufacturing Industry Avg (This Year)
No incidents recorded for Havells India Ltd in 2026.
Incident History - TA Instruments (X = Date, Y = Severity)
TA Instruments cyber incidents detection timeline including parent company and subsidiaries.
Incident History - Havells India Ltd (X = Date, Y = Severity)
Havells India Ltd cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents
TA Instruments
Havells India Ltd
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.