Comparison Overview
Anthropic

Anthropic
N/A
Last Update: 17/06/2026
We're an AI research company that builds reliable, interpretable, and steerable AI systems. Our first product is Claude, an AI assistant for tasks at any scale. Our research interests span multiple areas including natural language, human feedback, scaling laws, reinfor...

CNRS
3 rue Michel-Ange, Paris, 75016, FR
Last Update: 01/04/2026
The French National Centre for Scientific Research is among the world's leading research institutions. Its scientists explore the living world, matter, the Universe, and the functioning of human societies in order to meet the major challenges of today and tomorrow. Inte...
Compliance Ranges Comparison

Anthropic







CNRS






Benchmark & Cyber Underwriting Signals
Incidents vs Research Services Industry Avg (This Year)
Anthropic has 1279.31% more incidents than the average of same-industry companies with at least one recorded incident.
Incidents vs Research Services Industry Avg (This Year)
No incidents recorded for CNRS in 2026.
Incident History - Anthropic (X = Date, Y = Severity)
Anthropic cyber incidents detection timeline including parent company and subsidiaries.
Incident History - CNRS (X = Date, Y = Severity)
CNRS cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents

Anthropic

CNRS
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.