Comparison Overview
metafinanz Informationssysteme GmbH
metafinanz Informationssysteme GmbH
Leopoldstraße 146, Munich, 80804, DE
Last Update: 31/03/2026
For over 35 years, metafinanz Informationssysteme GmbH, a business and IT consulting company, has been at the side of its customers in an increasingly digital and dynamic world. Our promise: We shine a new light on future viability. We enable our customers to find, deve...
Indra
Avda. Bruselas, 35, Madrid, 28108, ES
Last Update: 14/09/2026
Indra Group (https://www.indragroup.com/) is the foremost Spanish multinational and one of the leading European companies that focus on defence and advanced technologies. It stands at the forefront of the defence, space, air traffic management, mobility, and Information...
Compliance Ranges Comparison
metafinanz Informationssysteme GmbH
Indra
Benchmark & Cyber Underwriting Signals
Incidents vs IT Services and IT Consulting Industry Avg (This Year)
No incidents recorded for metafinanz Informationssysteme GmbH in 2026.
Incidents vs IT Services and IT Consulting Industry Avg (This Year)
Indra has 2.91% fewer incidents than the average of all companies with at least one recorded incident.
Incident History - metafinanz Informationssysteme GmbH (X = Date, Y = Severity)
metafinanz Informationssysteme GmbH cyber incidents detection timeline including parent company and subsidiaries.
Incident History - Indra (X = Date, Y = Severity)
Indra cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents
metafinanz Informationssysteme GmbH
Indra
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.