Comparison Overview
Wpay

Wpay
N/A
Last Update: 14/02/2026
We partner with leading Australian companies to create better payments experiences for them and their customers. Our end to end platform can be customised for your business to deliver: Seamless payments Reduced costs and complexity Deeper customer engagement; and Pred...

J.P. Morgan
270 Park Avenue, New York, NY, US, 10017
Last Update: 05/04/2026
J.P. Morgan is a leader in financial services, offering solutions to clients in more than 100 countries with one of the most comprehensive global product platforms available. We have been helping our clients to do business and manage their wealth for more than 200 years...
Compliance Ranges Comparison

Wpay







J.P. Morgan






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

Wpay

J.P. Morgan
FAQ
Latest Global CVEs
PraisonAI before 1.5.115 contains a path traversal vulnerability in MultiAgentMonitor that fails to sanitize agent IDs when building file paths. Attackers can include traversal sequences like ../ in agent IDs to read, write, or overwrite arbitrary files, enabling sensitive disclosure, denial of service, or code execution.
PraisonAI before 1.5.115 contains an information disclosure vulnerability in the MultiAgentLedger component that allows attackers to access sensitive data by registering agents with duplicate IDs. Attackers can exploit the lack of agent ID uniqueness enforcement to share ledger instances and expose system prompts and conversation history between agents.
PraisonAI before 1.5.128 contains a cross-origin agent execution vulnerability in the AGUI endpoint that allows remote attackers to trigger arbitrary agent execution. The POST /agui endpoint lacks authentication and hardcodes Access-Control-Allow-Origin: * headers, combined with Starlette's Content-Type-agnostic JSON parsing, enabling attackers to bypass CORS preflight checks via simple requests and exfiltrate sensitive agent responses including tool execution results and environment data.
PraisonAI before 4.5.128 contains an arbitrary shell command execution vulnerability where the UI modules hardcode approval_mode to auto, overriding administrator configuration from PRAISON_APPROVAL_MODE environment variable. Authenticated attackers can instruct the LLM agent to execute arbitrary shell commands via subprocess.run with shell=True, bypassing the manual approval gate and insufficient command sanitization blocklists.
PraisonAI before 1.5.128 caches tool approval decisions by tool name only, not by invocation arguments, allowing subsequent execute_command calls to bypass approval prompts. Attackers can exploit this by obtaining initial approval for a benign command, then silently exfiltrate API keys and credentials via subsequent shell commands without user consent.