Pensar
Pensar provides a continuous adversarial testing platform that uses autonomous offensive AI agents to discover, provably exploit, and patch real vulnerabilities in an automated loop. The platform integrates with CI/CD pipelines, ships every finding with a working proof-of-concept exploit and a reviewable patch, and includes a retest loop that runs variant analysis to ensure all exploit paths are closed. It also offers human-attested penetration test reports from OSCP-certified pentesters for compliance and audit purposes.
- Cybersecurity
- AI Agents
- Artificial Intelligence
- Developer Tools
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
AI-enabled threats are outpacing traditional security defenses. Signature-based tools miss chained, multi-step attacks and business-logic flaws, while manual penetration testing is too slow and expensive to keep pace with continuous code deployment. Attackers can now scale their operations horizontally by spending money on tokens, giving them effectively infinite attempts to find critical vulnerabilities.
Solution
Pensar provides a continuous adversarial testing platform that uses frontier offensive AI agents to map, discover, exploit, and patch real vulnerabilities in an automated loop. The platform continuously monitors repositories, domains, and applications, updates living threat models as code changes, and dispatches agents to test every endpoint with working proof-of-concept exploits. Each validated exploit is automatically remediated, and a retest loop deploys agents to attempt re-exploitation through variant analysis, ensuring all potential exploit paths are closed before a finding is marked resolved. The entire system integrates with CI/CD pipelines and existing agent harnesses, allowing security testing to occur on every deployment without manual intervention.
Target Audience
Primary customers are security engineers, CISOs, and development teams at organizations with continuous deployment practices who need to secure applications and infrastructure against AI-enabled threats and meet penetration testing requirements.
Features
- Continuous reconnaissance that automatically maps attack surfaces across multi-repo workspaces and re-runs as code changes
- Living threat models at the endpoint level that update in place with business logic, attacker objectives, and risk scores
- Autonomous offensive agents that discover and provably exploit vulnerabilities including chained attacks and business-logic flaws
- Auto-remediation that opens fix for review, with a retest loop that runs variant analysis to ensure no exploit paths remain
- Per-application access control with three-tier workspace membership for least-privilege security data access
- CLI, webhooks, and agent skills to integrate retesting into existing remediation workflows or bring your own coding agent
- Human-attested penetration test reports delivered by OSCP-certified, US-based pentesters for compliance and audit purposes