ITL-07 CONSULTING SERVICE
Vulnerability Management
The problem is rarely finding vulnerabilities — it's deciding, among thousands, which ones truly matter this week, and fixing them where they actually live: in the infrastructure, in the code, and in the dependencies.
The problem
Scanners produce backlogs of thousands of "critical" vulnerabilities that no team can (or should) fix in full. The severity score alone measures theoretical risk, not exploitation probability: a 9.8 flaw with no known exploitation may matter less than a 7.5 being actively exploited. And a growing share of the risk isn't in the infrastructure at all — it's in the company's own code and in the third-party libraries it imports.
How we work
Prioritization by real risk
A composite scoring model that combines severity (CVSS), exploitation probability (EPSS), and confirmed active exploitation (the CISA KEV catalog) into a single index, consumable by integration and applicable across the entire pipeline — from discovery to the executive dashboard.
Remediation in first-party code
Integration of security analysis into the development cycle: identification of flaws in source code, triage with the engineering team, and remediation prioritized by the same risk criteria — closing the vulnerability at the source, not at the symptom.
Third-party dependencies and supply chain
Software composition analysis: inventory of third-party libraries and components (including generation of a formal component inventory), inherited vulnerabilities, licenses, and a continuous dependency update strategy.
AI-assisted remediation, under supervision
Using AI to accelerate remediation — generating proposed code fixes, dependency updates, and finding triage — always with specialized human review before any change. AI provides the speed; supervision ensures the fix doesn't introduce a new problem.
Process and technical triage
Design of the full cycle — discovery, enrichment, prioritization, ownership, remediation deadlines per risk tier, and aging metrics — with manual validation of applicability before mobilizing teams, eliminating false positives.
Applied experience
Composite prioritization models in production and vulnerability management programs designed for high-volume digital operations, integrating infrastructure, applications, and development pipelines.
Frequently asked questions
Why isn't the severity score alone enough to prioritize?
Because it measures potential severity under generic conditions, not the real chance of exploitation in your context. Estimated exploitation probability and confirmed active exploitation radically change the order of the queue — and the return on remediation effort. Combining the three dimensions produces a queue ten times smaller and far more defensible before an audit.
How does AI-assisted remediation work in practice?
AI acts where it provides speed with controlled risk: proposing the fix for a code flaw, preparing a dependency update with compatibility changes mapped, grouping duplicate findings. Every proposal goes through specialist review and the pipeline's tests before reaching production. The typical gain is reducing the remediation cycle from weeks to days — without giving up control.
Does this replace our vulnerability scanner?
No — it uses its data. The scanner keeps discovering; the model enriches, prioritizes, and connects discovery to remediation, including when the fix is in code or in a third-party library that the infrastructure scanner doesn't see.
Need a conversation about Vulnerability Management?
Describe the scenario in two lines. We'll answer with an honest read — including if the answer is that you don't need us.