A plain language reference for the terms around autonomous and agentic penetration testing. Each entry is a short, quotable definition, updated as the category moves.
Penetration testing performed by an autonomous AI agent that plans and carries out an assessment on its own, reasoning about what to test, chaining real exploits, and reporting verified findings continuously.
Security testing that discovers, exploits, and verifies vulnerabilities without a human driving each step, replacing point-in-time scans with ongoing, evidence based testing.
Testing that runs fixed scripts and tools against known signatures. Faster than manual work, but it does not reason across steps or prove exploitability the way an agent does.
An overloaded term. It can mean using AI to perform a pentest, or testing the security of an AI system. Planck Operator is the former, and also tests AI systems as one of its disciplines.
Everything an attacker can reach: domains, subdomains, hosts, ports, endpoints, APIs, cloud storage, and the services behind them, including assets no one remembered to decommission.
The ongoing practice of discovering and monitoring your external footprint so exposure introduced by drift and new deployments is found before an attacker finds it.
Combining several findings, each harmless alone, into a real path in. A leaked key becomes an authenticated request, which becomes access to data. The heart of what an agent does.
Evidence that a vulnerability is genuinely exploitable: the exact requests, responses, and steps that reproduce it, rather than a version match or a theoretical rating.
A reported issue that is not actually exploitable. The core weakness of scanners. An agentic pentester reproduces each finding first, so unprovable results never reach you.
The Common Vulnerability Scoring System, the standard for rating severity. A finding either follows a verifiable CVSS vector or the number should not be printed.
Penetration testing as a service. A subscription model for testing, often blending a platform with human testers, delivered continuously rather than as a one-off engagement.
CTEM, a program for continuously discovering, validating, and prioritizing exposure. Autonomous validation is the testing engine inside a mature CTEM practice.
AEV, the category term for proving which exposures are actually exploitable, rather than assuming a scanner result is real. Validation over assumption.
Objective driven adversary emulation against an organization as a whole, testing people, process, and technology, and measuring detection and response rather than listing flaws.
An attack on LLM features where untrusted content becomes instructions the model follows. A core class in the OWASP Top 10 for LLM Applications, and part of AI system testing.
The sequence of steps an intruder walks from first reconnaissance to impact. Mapping a finding onto the kill chain shows what it actually lets an attacker do.
Give us a domain and the rules of engagement, and we will show you what a proven finding looks like.