Dynamic control recommendation & tracking
Raptor Control
Apply the right controls — turn each system's risk context into proportionate security controls, then track who's implementing them and how far along they are.
The problem
What it addresses
- Teams struggle to translate high-level frameworks into controls proportionate to each product or system.
- Control libraries grow large and static, and become hard for engineering teams to consume.
- Leadership rarely has a reliable view of which controls are implemented, in progress or outstanding.
Capabilities
What it does
- Dynamic control recommendations driven by asset classification and risk context.
- Mapping to a large control library, including NIST-aligned structures and other frameworks.
- Implementation tracking: Not Started, In Progress, percentage complete, Done.
- Role-based visibility for control owners, engineering, managers and executives.
- Prioritisation of control work based on business criticality and risk.
Differentiators
Why it's different
- Moves from static control catalogues to context-aware control selection.
- Connects Raptor Bucket tiers to control depth — less over-control of low-risk, less under-control of critical.
- Pairs control recommendation with implementation tracking, not just assessment.
- Creates a shared language between GRC and engineering / control owners.
In practice
A Platinum internet-facing system receives a stronger control baseline than a Bronze internal one, with progress visible to both the engineers doing the work and the leadership tracking it.
Where it fits
Part of one connected lifecycle
ClassifyControlDesignComplyGovern
Risk context created upstream is reused here, instead of being rebuilt independently by GRC, AppSec and engineering.
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