Protectiv / Security services
A closer look at the systems that matter.
Protectiv evaluates web and mobile applications, APIs, and exposed systems through attack-surface mapping, manual and AI-assisted testing, and targeted technical investigation. Every reported finding is reproduced and verified by a security researcher.
- Offering
- Technical Security Assessment
- Scope
- Web, mobile, APIs, and exposed systems
- Standard
- Human-verified findings
One focused offering
Adapt the scope, keep the standard consistent.
The assessment follows the system and the question rather than forcing every engagement into the same checklist.
- 01
Web and mobile application behavior
Authentication, authorization, session handling, business logic, data flow, and the conditions created by real user actions.
- 02
API boundaries
Exposed endpoints, object access, trust relationships, state transitions, integrations, and undocumented behavior.
- 03
External exposure
Public applications, services, infrastructure, forgotten assets, and the paths that connect them to important systems.
- 04
Complex technical conditions
Suspected weaknesses, unusual behavior, or high-risk questions that need focused investigation beyond routine scanning.
Assessment method
Follow the evidence from scope to retest.
Progress is visible at every stage. Material findings are validated before they enter the report.
- 01
Scope
Define the system, permissions, operating constraints, and the questions the assessment must answer.
- 02
Map
Understand the exposed surface, important components, data paths, and trust boundaries.
- 03
Test
Exercise the system through manual, automated, and AI-assisted security testing.
- 04
Investigate
Follow unusual behavior far enough to understand the condition and its possible impact.
- 05
Validate
Reproduce each material finding and separate evidence from scanner or model output.
- 06
Report
Document the evidence, root cause, impact, and practical remediation path.
- 07
Retest
Verify agreed fixes and record whether the original condition remains reachable.
AI-assisted testing
AI expands coverage. Researchers own the conclusion.
Machine learning systems, LLMs, and agents can generate test paths, vary inputs, correlate signals, and help prioritize unusual behavior. They extend the investigation without lowering the standard of proof.
Controlled scope
Tools operate within the target, permissions, and constraints agreed for the engagement.
Repeatable behavior
Potential weaknesses are reproduced against the system rather than accepted from model output.
Human verification
A security researcher determines the evidence, impact, and final claim.
Client deliverables
A technical record your team can act on.
- 01Verified findings with technical evidence
- 02Clear reproduction steps
- 03Root-cause and attack-path analysis
- 04Prioritized remediation guidance
- 05Technical findings briefing
- 06Retesting of agreed fixes
Good fit
Engage when the system needs a defensible answer.
- A high-impact application or API is approaching launch or a major release.
- The system has changed enough that its current security boundaries are unclear.
- External exposure has grown across web or mobile applications, APIs, services, or infrastructure.
- A suspected weakness or unusual behavior needs a defensible technical answer.
Not designed for
Work that rewards volume over understanding.
- Automated scan-only reports
- Checkbox compliance exercises
- Staff augmentation
- Continuous SOC or 24-hour monitoring
Start an assessment
Bring us the system and the question.
Tell us what needs to be assessed, why it matters, and any timing or operational constraints. We will respond with the questions needed to define a responsible scope.