Comparison Overview
Tiendas Neto

Tiendas Neto
Mexico City, MX
Last Update: 29/03/2026
Somos una empresa 100% mexicana, con más de 16 años en el mercado. Estamos omprometidos con el país CREANDO VALOR NETO PARA MÉXICO. Contamos con más de 1,700 tiendas en 23 estados del país ofreciendo los mejores precios a las familias mexicanas. Somos casi 13,000 co...

Target
1000 Nicollet Mall, Minneapolis, 55403, US
Last Update: 06/05/2026
Target is one of the world’s most recognized brands — and one of America’s leading retailers — known for bringing joy to everyday life. We create meaningful experiences for our guests by combining value, inspiration and innovation in ways no one else can. Beyond our sto...
Compliance Ranges Comparison

Tiendas Neto







Target






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

Tiendas Neto

Target
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.