Comparison Overview
Gainsight

Gainsight
350 Bay St, San Francisco, California, US, 94133
Last Update: 14/07/2026
Gainsight is the retention engine behind the world’s most customer-centric companies. The Gainsight platform orchestrates the customer journey from onboarding to outcomes. More than 2,000 companies trust Gainsight’s applications and AI agents to drive learning, adoption...

PedidosYa
La Cumparsita 1475, 11200 Montevideo, Departamento de Montevideo, Montevideo, Montevideo, UY, 11200
Last Update: 13/09/2026
We’re the delivery market leader in Latin America. Our platform connects over 77.000 restaurants, supermarkets, pharmacies and stores with millions of users. Nowadays we operate in more than 500 cities in Latinamerica. And we are now over 3.400 employees. PedidosYa is ...
Compliance Ranges Comparison

Gainsight







PedidosYa






Benchmark & Cyber Underwriting Signals
Incidents vs Software Development Industry Avg (This Year)
Gainsight has 5.66% fewer incidents than the average of same-industry companies with at least one recorded incident.
Incidents vs Software Development Industry Avg (This Year)
No incidents recorded for PedidosYa in 2026.
Incident History - Gainsight (X = Date, Y = Severity)
Gainsight cyber incidents detection timeline including parent company and subsidiaries.
Incident History - PedidosYa (X = Date, Y = Severity)
PedidosYa cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents

Gainsight

PedidosYa
FAQ
Latest Global CVEs
A vulnerability was determined in xuxueli xxl-job up to 3.5.0. The impacted element is an unknown function of the file /jobgroup/insert. This manipulation of the argument Name causes cross site scripting. The attack can be initiated remotely. The exploit has been publicly disclosed and may be utilized. The vendor was contacted early about this disclosure but did not respond in any way.
A vulnerability was found in Moore Threads MTT S80 Driver Package 340.150. The affected element is the function sub_140006F0C in the library mtdispkm64.sys of the component IOCTL Handler. The manipulation results in improper privilege management. Attacking locally is a requirement. The vendor was contacted early about this disclosure but did not respond in any way.
vLLM Mooncake connector through 0.29.0 fails to properly manage GPU KV cache block ownership when concurrent child requests share a single transfer ID in prefill/decode disaggregated deployments. Attackers can trigger GPU memory exhaustion by submitting completion requests with multiple prompts, causing orphaned KV cache blocks to accumulate until process restart and eventually preventing legitimate requests from executing.
- https://github.com/vllm-project/vllm
- https://github.com/vllm-project/vllm/blob/v0.29.0/vllm/distributed/kv_transfer/kv_connector/v1/mooncake/mooncake_connector.py#L1978-L1989
- https://github.com/vllm-project/vllm/pull/49796
- https://www.vulncheck.com/advisories/vllm-through-0.29.0-gpu-kv-cache-leak-via-mooncake-transfer-id-collision
vLLM through 0.29.0 fails to validate the tp_size parameter in kv_transfer_params on OpenAI-compatible completion endpoints, allowing attackers to allocate unbounded memory. Attackers can supply arbitrary tp_size values in prefill/decode disaggregated deployments to exhaust memory and trigger kernel OOM-kill of the decode worker process.
- https://github.com/vllm-project/vllm
- https://github.com/vllm-project/vllm/blob/v0.29.0/vllm/distributed/kv_transfer/kv_connector/utils.py#L569-L573
- https://github.com/vllm-project/vllm/blob/v0.29.0/vllm/distributed/kv_transfer/kv_connector/v1/nixl/metadata.py#L277
- https://github.com/vllm-project/vllm/pull/51137
- https://www.vulncheck.com/advisories/vllm-through-0.29.0-memory-exhaustion-via-unvalidated-nixl-tp-size
vLLM through 0.29.0 contains a resource exhaustion vulnerability in MooncakeConnector where rejected prefill requests create ownerless transfer placeholders that are never reclaimed. Attackers can send rejected requests to exhaust sender task pools, causing valid requests to be delayed by up to 480 seconds while health checks continue returning success.
- https://github.com/vllm-project/vllm
- https://github.com/vllm-project/vllm/blob/v0.29.0/vllm/distributed/kv_transfer/kv_connector/v1/mooncake/mooncake_connector.py#L1234-L1242
- https://github.com/vllm-project/vllm/pull/51236
- https://www.vulncheck.com/advisories/vllm-through-0.29.0-resource-exhaustion-via-ownerless-mooncake-transfer-placeholders