Scope a single penetration test
Define the systems, the attack paths and the report for one engagement with a fixed start and finish.
A recurring testing cycle that follows your environment
Your Environment Changes Every Sprint. So Should the Test
A penetration test describes your environment on the day it ran, and the environment stopped looking like that the following week. Our continuous program uses AI tooling to map every new release, permission and endpoint and senior testers to prove what matters, so the picture you report to leadership is never stale. To see what a cycle needs from your team, read the assessment preparation guide.
Choose the Testing Approach Your Team Needs
A single penetration test and a recurring program answer different operational questions, and the two pages below set out each one plainly.
Understand the AI assisted method
See how human directed testing uses AI assistance inside an individual engagement before you commit to a program.
Ask who designs the program and reviews each cycle; the testers are named before the first window.
Keep Testing Current as Applications, APIs and Cloud Change
New releases, new cloud resources, new integrations and changed permissions create exposure between scheduled assessments, and an attacker does not wait for your next annual test. Global Digital Forensics has operated since 1992, and our recurring program applies current AI assistance and human validation to the systems in your scope so that what we examined last quarter is examined again when it changes.
A completed test documents the environment examined at that moment. A new endpoint, a release or a permission change needs a fresh look, and repeated assessment lets your team see the change that matters and decide what deserves attention before someone else finds it.
GDF uses AI to map that exposure, hunt for candidate vulnerabilities and correlate weaknesses into a proposed attack plan. Experienced testers review and run the authorized tests, separate real findings from false positives and give your team remediation priorities they can act on.
In November 2025, Anthropic reported AI use in a real espionage campaign that included reconnaissance and vulnerability testing, and it also documented errors in the AI output. In February 2026, AISLE reported previously undisclosed vulnerabilities found with its AI analyzer. These dated examples show that the capability is real; they do not promise speed or accuracy in every environment, and neither do we.
If your release cadence has outrun your assessment schedule, describe the environment and how often it changes and a senior tester will propose a cadence.
From discovery to demonstrated impact
AI Analysis With Human Validation at Every Decision That Matters
Large volumes of discovery signals become a focused testing plan, and human judgment stands between a possible attack path and a confirmed finding.
- 01
Map the attack surface
We identify the systems and connections in scope.
We discover and organize the authorized networks, applications, APIs, identities and cloud access so the plan reflects the assets and connections that exist today, not the ones on last year’s diagram.
The connected asset map records the discovery context for later analysis.
- 02
Find candidate weaknesses
We evaluate the discovery results for weaknesses worth a controlled test.
We compare discovery results, configurations and security signals to find the gaps that merit a controlled test rather than another alert.
Candidate findings stay linked to their supporting observations for tester review.
- 03
Connect the possible attack paths
We rank hypotheses into a proposed attack plan.
We connect weaknesses, permissions and trust relationships into possible paths to sensitive information or critical systems and name the prerequisites that would have to be true.
The plan ranks hypotheses for testing instead of treating a possible path as an established compromise.
- 04
Review the proposed test plan
A tester approves what is permitted to run.
A GDF tester checks the evidence, prerequisites, scope and operational risk before approving the plan, so proposed activity stays inside the authorized boundaries.
The reviewed plan identifies the tests approved by the human team.
- 05
Validate the security impact
We run the permitted paths and record what happened.
Human testers execute the approved plan, reproduce findings and document the paths that succeeded and the paths a control blocked, so the record shows what was actually demonstrated.
The resulting evidence records the demonstrated impact and the conditions behind it.
- 06
Retest fixes and update the evidence
We check agreed corrections and refresh the map.
We retest the agreed fixes and carry new discoveries and environment changes into the next cycle, so each assessment starts from updated evidence.
The retest record separates verified corrections from open risks and items needing further examination.
Repeat as the environment changes. New assets, releases, permissions and threat information feed the next agreed testing cycle.
Test How a Single Application Could Expose Your Data
Illustrative scenario
Internet facing application→Overprivileged service identity→Sensitive cloud storage
The AI correlates the observations and poses a question: could a weakness in this application expose data through the identity it runs under? A tester checks whether the prerequisites are real and whether the proposed test is authorized before anything runs.
The report separates a demonstrated path from a plausible path that was not validated. If a control blocked the access, that result is recorded too, because a relationship on a diagram is not proof of compromise and your board should not be told that it is.
If a single application or identity is the one you worry about, call (800) 868-8189 and we will scope a first cycle around it.
Set Your Testing Cadence and Human Review Windows
A penetration test describes the environment examined during that engagement, and new releases, cloud resources, integrations and permission changes alter the picture afterwards. Continuous AI penetration testing gives you a recurring discovery, analysis, validation and retesting cycle across an agreed scope, so the picture is refreshed as often as your environment warrants.
We agree monitoring intervals based on the technologies in scope and the value of the data, alongside human testing windows, escalation, retest coverage, operating constraints and stop conditions. Continuous means a recurring program inside those arrangements; it does not mean unrestricted activity, and it does not imply a round the clock staffing commitment unless your engagement specifies one.
This service is for organizations that need to keep reassessing a changing exposure. Our AI powered penetration testing page explains how AI is used inside a single engagement.
An Attack Plan Your Testers Can Explain to Your Board
AI can organize large collections of observations, compare combinations of access and generate candidate test sequences, which points attention toward relationships a tester might not have time to explore by hand. Its value depends on the quality and coverage of the underlying information, and we are candid about both.
GDF testers review the proposed paths, reject unsupported assumptions and choose the tests capable of demonstrating material impact. They retain the observations, prerequisites and reproduction evidence behind every accepted finding, and the report identifies the scope and the coverage that remains. Confidence expressed by an AI model is not validation, and no finite test guarantees discovery of every vulnerability.
Before your board meets, review the assessment preparation guide so the questions about scope, authorization and evidence are settled in advance.
What your security team receives
The attack surface record identifies the assets and relationships examined, the changes discovered since the last cycle and the coverage gaps we know about. Prioritized findings connect each validated weakness and attack path with the affected systems, the business impact and the supporting evidence. Remediation guidance names the actions that break the path, reduce excessive access and correct the underlying weakness, and the retest results show whether the agreed corrections worked, what remains open and what needs further examination.
Priorities reflect the evidence, the reachability, the data affected and your operating context rather than a vulnerability score alone, so the first item on the list is the one that would hurt most.
Tell us which audience each deliverable serves and we will shape the report around it before the first cycle.
Set the Boundaries Before Testing Begins
We agree the systems, accounts and data that may be examined, the permitted techniques, the testing windows and the escalation contacts. Third party systems require their owner’s authorization. Testing that could affect availability or sensitive data gets explicit treatment in the plan, with stop conditions your operations team has seen in advance.
The engagement also defines the approved AI tools, where information is processed and which records may be retained. Client credentials, source code and sensitive findings travel only through approved workflows. Your team should always know what is being tested, by whom and how the evidence is handled.
Boundaries are agreed in writing before the first cycle. Send us your systems, exclusions and escalation contacts and we will draft the rules of engagement.
Questions About Continuous AI Penetration Testing
Is this an automated vulnerability scan?
No. Scanning provides observations. This program adds correlation, human review, authorized testing and evidence of impact, and scanner results and AI proposed paths remain candidates until a tester validates them.
Will AI execute attacks without a tester reviewing them?
No. The workflow puts human review before execution. GDF testers review the proposed plan and run the authorized tests within the agreed scope, and a model cannot widen that scope on its own.
Does continuous mean a human tester is working on our environment 24/7?
Continuous describes a recurring program. We tailor monitoring intervals to your technologies and the value of the data and agree human testing windows and response arrangements. The engagement specifies any staffing or response commitment; the service name alone does not establish a 24/7 human testing commitment.
Can AI find vulnerabilities that people cannot?
AI can organize patterns and combinations across a larger set of observations than a person can hold in mind, which produces candidate paths for the tester to assess. Human validation then establishes whether a candidate is a real weakness in your environment or an artifact of the data.
Does this test our own AI models and chatbots?
No. This page describes using AI to support security testing of your environment. Assessing AI applications, models and their integrations is a separate scope described on our AI security testing and AI security consulting pages.
Define Your Recurring Testing Scope and Cadence
Tell us which networks, applications, APIs and cloud environments you need to keep under review, how often they change and what you need to protect. A senior tester will discuss the scope, the cadence and the evidence your team needs, and the first consultation is free.
Standards the Program Can Be Mapped To
NIST SP 800-115 provides guidance on assessment planning, findings and mitigation. The NCCoE DevSecOps live reference model was updated in September 2026 and was open for public comment as described in the cited source; it discusses human oversight and validation of generated content. These are methodological references, not certifications or performance evidence for this service.
Reviewed by Joseph Caruso, Founder, CEO and CTO, CISSP. Last reviewed .