Comparison Overview
Pak-it Displays

Pak-it Displays
1324-1344 Adams Rd., Bensalem, 19020, US
Last Update: 03/04/2026
Pak-it Displays is a leading designer and manufacturer of custom point-of-purchase (POP) displays, specializing in creative solutions that drive retail sales. With decades of experience, we partner with top national brands and retailers to develop eye-catching displays ...

O'Reilly Auto Parts
233 S Patterson Ave, Springfield, MO, US, 65802
Last Update: 01/04/2026
O’Reilly Auto Parts started as a single store and has grown into a leading retailer in the automotive aftermarket industry with more than 6,100 locations and counting. With more than 94,000 team members, O’Reilly has expanded into 48 states, Puerto Rico, Mexico, and Can...
Compliance Ranges Comparison

Pak-it Displays







O'Reilly Auto Parts






Benchmark & Cyber Underwriting Signals
Incidents vs Retail Industry Avg (This Year)
No incidents recorded for Pak-it Displays in 2026.
Incidents vs Retail Industry Avg (This Year)
No incidents recorded for O'Reilly Auto Parts in 2026.
Incident History - Pak-it Displays (X = Date, Y = Severity)
Pak-it Displays cyber incidents detection timeline including parent company and subsidiaries.
Incident History - O'Reilly Auto Parts (X = Date, Y = Severity)
O'Reilly Auto Parts cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents

Pak-it Displays

O'Reilly Auto Parts
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.