Comparison Overview
GF Piping Systems Canada
GF Piping Systems Canada
75 Dupont Blvd., Coteau-du-Lac, J0P 1B0, CA
Last Update: 19/03/2026
GF is the leading flow solutions provider for industry and infrastructure, enabling the safe and sustainable transport of fluids. The division ensures process quality with industry-leading, leakage-free, easy-to-install, and maintain flow solutions and engineering servi...
Metso
Rauhalanpuisto 9, Espoo, 02230, FI
Last Update: 07/09/2026
Metso is a frontrunner in sustainable technologies, end-to-end solutions and services for the aggregates, minerals processing and metals refining industries globally. By improving our customers’ energy and water efficiency, increasing their productivity, and reducing ...
Compliance Ranges Comparison
GF Piping Systems Canada
Metso
Benchmark & Cyber Underwriting Signals
Incidents vs Industrial Machinery Manufacturing Industry Avg (This Year)
No incidents recorded for GF Piping Systems Canada in 2026.
Incidents vs Industrial Machinery Manufacturing Industry Avg (This Year)
No incidents recorded for Metso in 2026.
Incident History - GF Piping Systems Canada (X = Date, Y = Severity)
GF Piping Systems Canada cyber incidents detection timeline including parent company and subsidiaries.
Incident History - Metso (X = Date, Y = Severity)
Metso cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents
GF Piping Systems Canada
Metso
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.