Comparison Overview
Goossen Te Pas

Goossen Te Pas
Marssteden 200, Enschede, undefined, 7547 TD, NL
Last Update: 22/02/2026
Wij zijn Goossen Te Pas. Wij ontwikkelen en realiseren uiteenlopende projecten op het gebied van wonen, werken, winkelen en recreëren. Dat doen wij voor gemeenten, corporaties en andere opdrachtgevers, al dan niet in samenwerking met partners. Kleinschalig, maar ook vee...

Royal BAM Group
Runnenburg 9, Bunnik, NL, 3981 AZ
Last Update: 01/04/2026
🏗️ Building a sustainable tomorrow at BAM! As leaders in the construction industry, we are committed to pioneering sustainable practices that not only enhance our projects but also contribute to a better future for generations to come. Our strategy revolves around f...
Compliance Ranges Comparison

Goossen Te Pas







Royal BAM Group






Benchmark & Cyber Underwriting Signals
Incidents vs Construction Industry Avg (This Year)
No incidents recorded for Goossen Te Pas in 2026.
Incidents vs Construction Industry Avg (This Year)
No incidents recorded for Royal BAM Group in 2026.
Incident History - Goossen Te Pas (X = Date, Y = Severity)
Goossen Te Pas cyber incidents detection timeline including parent company and subsidiaries.
Incident History - Royal BAM Group (X = Date, Y = Severity)
Royal BAM Group cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents

Goossen Te Pas

Royal BAM Group
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.