Comparison Overview
Alabama Department of Public Health

Alabama Department of Public Health
201 Monroe Street, Montgomery, 36104, US
Last Update: 23/06/2026
The Alabama Department of Public Health (ADPH) is the state's primary health agency. With approximately 2,700 employees, ADPH is one of the largest state agencies. ADPH aims to provide public health "services for the improvement and protection of the public’s health thr...

National Institute of Statistics and Geography of Mexico (INEGI)
Av. Héroe de Nacozari Sur 2301, Aguascalientes, 20276, MX
Last Update: 02/04/2026
The National Institute of Statistics and Geography of Mexico (INEGI) is an autonomous institution of the Federal Public Sector. INEGI is the coordinator of the National System of Statistical and Geographical Information of Mexico. The main objective of INEGI is to pr...
Compliance Ranges Comparison

Alabama Department of Public Health







National Institute of Statistics and Geography of Mexico (INEGI)






Benchmark & Cyber Underwriting Signals
Incidents vs Government Administration Industry Avg (This Year)
Alabama Department of Public Health has 33.77% fewer incidents than the average of same-industry companies with at least one recorded incident.
Incidents vs Government Administration Industry Avg (This Year)
No incidents recorded for National Institute of Statistics and Geography of Mexico (INEGI) in 2026.
Incident History - Alabama Department of Public Health (X = Date, Y = Severity)
Alabama Department of Public Health cyber incidents detection timeline including parent company and subsidiaries.
Incident History - National Institute of Statistics and Geography of Mexico (INEGI) (X = Date, Y = Severity)
National Institute of Statistics and Geography of Mexico (INEGI) cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents

Alabama Department of Public Health

National Institute of Statistics and Geography of Mexico (INEGI)
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