Agentic AI systems take penetration testing to a level far beyond traditional methods. In the words of a former Synack Red Team member and security engineer, Max Moroz, “Traditional pentesting is like checking your locks and windows once a year while a swarm of AI-powered burglars are constantly probing your house.” Companies are now considering pentesting powered by agentic AI (i.e. Synack’s Sara Pentest) to achieve the level of scale, speed and cost effectiveness that attackers are already leveraging.
To achieve the many benefits of agentic AI for penetration testing, it is imperative to understand and follow proven best practices.
Benefits of Using Agentic AI in Penetration Testing
Scale Broader Coverage
AI agents can run continuous, parallel vulnerability discovery across thousands of web and host assets. This breadth of coverage significantly reduces blind spots and security gaps. For instance, an AI agent can be assigned to assess a new product for potentially critical vulnerabilities like SQLi, or do a quick risk assessment on a newly acquired startup.
Faster Test Cycles and Time to Detection
AI agents can conduct a pentest in hours instead of days. They can move at machine speed and with more efficiency. This pace of testing allows for quick identification and validation of critical exposures, reducing the mean time to detect and remediate.
Automated Triage
AI agents can validate vulnerabilities by using agents to prove exploitability before reporting. This reduces noisy reports, reduces the triage cost per a vulnerability by as much as 80%, and provides actionable, exploitable vulnerabilities.
Adaptive Testing
Because AI agents learn from failures and re-plan dynamically rather than repeating ineffective steps, hit rates are improved, and wasted cycles are reduced. For example, if a brute-force attempt fails repeatedly, the agent backs off and tries credential stuffing with different wordlists.
Guardrails for Using Agentic AI in Pentesting
The following best practices will help organizations maximize the benefits of agentic AI for pentesting and minimize risks.
Vendor Governance & Legal Liability
Verify the vendor’s security (SOC 2, ISO 27001) and legal framework. The Master Services Agreement (MSA) and insurance policies must explicitly cover liability for the AI’s autonomous actions and clearly state how your data is used.
Model Integrity & Training
Vet the agents training data, its testing methodologies (e.g., OWASP), and all third-party LLMs used. The platform must have robust, provable defenses against “model jailbreaking” and prompt injection attacks.
Technical Containment & Hard-Coded Safety
The agents “contract” must be technically enforced. This includes a non-bypassable blocklist for all destructive commands (e.g., rm -rf, DROP TABLE), strict rate-limiting, and egress filters to make it impossible for the AI to go out-of-scope.
Human-in-the-Loop & Real-Time Control
The system must not be fully autonomous. It must include a real-time “emergency stop” button and require mandatory human approval for any ambiguous, high-risk, or post-exploitation actions.
Data Security & Privacy
Enforce a “zero-trust” approach to your data. All sensitive data (PII) must be masked in prompts, logs, and reports. The vendor must provide a clear policy on data retention and options for customer opt-out rights for using data in model training.
Validation & Explainability
The system must provide provable, step-by-step validation to eliminate false positives. It must also maintain a complete, immutable audit log explaining why the agent made every decision
Agentic pentesting can provide a lot of benefits for your organization, but guardrails should also be considered. With Synack’s 13 years of pentesting experience, we have carefully thought through how to build a agentic AI pentest that has many of these benefits while providing a high level of human oversight and control.
See Sara Pentest in action in product webinar.
