Comparison Overview
Cadagua, a Ferrovial company

Cadagua, a Ferrovial company
Gran Vía Don Diego López de Haro, 45, 8th Floor, Bilbao-Bilbo, Basque Country, ES, 48011
Last Update: 02/04/2026
We specialize in the design, construction, and operation of water treatment facilities. With almost 50 years of experience, we have offered solutions for over 400 projects, both in industrial facilities and urban environments. We aim to ensure the drinking water suppl...

Fugro
Veurse Achterweg 10, Leidschendam, 2264 SG, NL
Last Update: 01/04/2026
We are the world’s leading Geo-data specialist, collecting and analysing comprehensive information about the Earth and the structures built upon it. Through integrated data acquisition, analysis and advice, we unlock insights from Geo-data to help our clients design, bu...
Compliance Ranges Comparison

Cadagua, a Ferrovial company







Fugro






Benchmark & Cyber Underwriting Signals
Incidents vs Civil Engineering Industry Avg (This Year)
No incidents recorded for Cadagua, a Ferrovial company in 2026.
Incidents vs Civil Engineering Industry Avg (This Year)
No incidents recorded for Fugro in 2026.
Incident History - Cadagua, a Ferrovial company (X = Date, Y = Severity)
Cadagua, a Ferrovial company cyber incidents detection timeline including parent company and subsidiaries.
Incident History - Fugro (X = Date, Y = Severity)
Fugro cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents

Cadagua, a Ferrovial company

Fugro
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.