Comparison Overview
Florence Bank

Florence Bank
85 Main Street, Florence, 01062, US
Last Update: 16/07/2026
Our commitment to sound banking, combined with our promise to provide the best service available, has made us one of the fastest growing banks in our area. Florence Bank remains committed to serving the community as a local bank. The bank is depositor owned and its D...

Access Bank Plc
Corporate Head Office, Victoria Island, 234-1, NG
Last Update: 04/04/2026
Access Bank Plc is a full service commercial Bank operating through a network of over 600 branches and service outlets located in major centres across Nigeria, Sub Saharan Africa and the United Kingdom. Listed on the Nigerian Stock Exchange in 1998, the Bank serves its ...
Compliance Ranges Comparison

Florence Bank







Access Bank Plc






Benchmark & Cyber Underwriting Signals
Incidents vs Banking Industry Avg (This Year)
Florence Bank has 42.2% fewer incidents than the average of same-industry companies with at least one recorded incident.
Incidents vs Banking Industry Avg (This Year)
No incidents recorded for Access Bank Plc in 2026.
Incident History - Florence Bank (X = Date, Y = Severity)
Florence Bank cyber incidents detection timeline including parent company and subsidiaries.
Incident History - Access Bank Plc (X = Date, Y = Severity)
Access Bank Plc cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents

Florence Bank

Access Bank Plc
FAQ
Latest Global CVEs
Uncontrolled Resource Consumption (CWE-400) in Kibana can lead to denial of service via Excessive Allocation (CAPEC-130). A low-privileged authenticated user can send a specially crafted request to a Kibana machine learning feature, causing the server to exhaust available memory and become unavailable to all users.
Uncontrolled Resource Consumption (CWE-400) in Kibana can lead to denial of service via Excessive Allocation (CAPEC-130). An authenticated attacker with low-privilege access can trigger a denial of service condition in Kibana by sending a specially crafted, oversized request payload. Processing this user-supplied input requires resource-intensive memory allocation that can exhaust the available heap memory in the Kibana process, causing it to crash and become unavailable to all users.
Authorization Bypass Through User-Controlled Key (CWE-639) in Kibana can lead to information disclosure via user-supplied identifiers that reference scheduled query result data from Kibana Spaces the requester is not authorized to access.
Incorrect Authorization (CWE-863) in Kibana can lead to integrity compromise of Machine Learning audit and notification records via Accessing Functionality Not Properly Constrained by ACLs (CAPEC-1). A vulnerability exists in Kibana's Machine Learning functionality where a Machine Learning management endpoint performs an insufficient authorization check. The endpoint validates only a coarse privilege level but does not verify that the requesting user has access to the specific Machine Learning job or notification resources provided in the request. As a result, a low-privileged user with Machine Learning access in any Kibana space can manipulate Machine Learning audit and notification records for arbitrary jobs—including jobs in other spaces or belonging to other users—by leveraging Kibana's internally elevated credentials to write to restricted Machine Learning system indices that the user cannot access directly.
Uncontrolled Recursion (CWE-674) in Elasticsearch can lead to denial of service via a specially crafted search request submitted by a low-privileged authenticated user. A user with read-level index access can submit a request that triggers unbounded recursive processing within the Elasticsearch query evaluation component, causing a fatal error that terminates the affected node. In single-node deployments, this results in complete service outage; in multi-node clusters, it causes repeated node restarts and sustained availability degradation.