Comparison Overview
Allianz Consulting

Allianz Consulting
Fritz-Schäffer-Straße 9, Munich, 81737, DE
Last Update: 23/12/2025
Allianz Consulting, part of Allianz Services, is the global in-house consultancy of the Allianz Group, established in 2004 with formal headquarters in Munich. Being the trusted advisor for one of the world's leading insurers and asset managers, we provide best-in-class...

Alvarez & Marsal
600 Madison Avenue, New York, 10022, US
Last Update: 13/09/2026
Alvarez & Marsal is a leading global professional services firm dedicated to helping organizations tackle their most complex business issues, maximize stakeholder value, and deliver sustainable change. Privately held since its founding in 1983, clients select us for o...
Compliance Ranges Comparison

Allianz Consulting







Alvarez & Marsal






Benchmark & Cyber Underwriting Signals
Incidents vs Business Consulting and Services Industry Avg (This Year)
No incidents recorded for Allianz Consulting in 2026.
Incidents vs Business Consulting and Services Industry Avg (This Year)
No incidents recorded for Alvarez & Marsal in 2026.
Incident History - Allianz Consulting (X = Date, Y = Severity)
Allianz Consulting cyber incidents detection timeline including parent company and subsidiaries.
Incident History - Alvarez & Marsal (X = Date, Y = Severity)
Alvarez & Marsal cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents

Allianz Consulting

Alvarez & Marsal
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