Comparison Overview
Capgemini Invent
Capgemini Invent
Place de l'Etoile, 11 rue de Tilsitt, Paris, FR, 75017
Last Update: 14/09/2026
Capgemini Invent is the digital innovation, consulting and transformation brand of the Capgemini Group, a global business line that combines market leading expertise in strategy, technology, data science and creative design, to help CxOs envision and build what’s next f...
Genpact
1155, Avenue of the Americas, 4th Floor,, New York, NY, US, 10036
Last Update: 02/04/2026
Genpact is an agentic and advanced technology solutions company. We leverage process intelligence and artificial intelligence to deliver measurable outcomes. With a strong partner ecosystem and decades of client trust, we provide innovative solutions that transform how ...
Compliance Ranges Comparison
Capgemini Invent
Genpact
Benchmark & Cyber Underwriting Signals
Incidents vs Business Consulting and Services Industry Avg (This Year)
No incidents recorded for Capgemini Invent in 2026.
Incidents vs Business Consulting and Services Industry Avg (This Year)
No incidents recorded for Genpact in 2026.
Incident History - Capgemini Invent (X = Date, Y = Severity)
Capgemini Invent cyber incidents detection timeline including parent company and subsidiaries.
Incident History - Genpact (X = Date, Y = Severity)
Genpact cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents
Capgemini Invent
Genpact
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.