01 / Agentic Pentesting

Continuous coverage, not a snapshot

Autonomous discovery and exploitation across your estate, running on a schedule instead of a calendar quarter.

Problem

A manual pentest is a point-in-time sample. New assets, configurations, and code ship every week, and the gap between engagements is where exposure accumulates unseen.

Approach

Our agents map the attack surface continuously, chain findings the way a human operator would, and re-verify exploitability after every change, not just once a year.

Outcome

Broader, more repeatable coverage than a fixed-scope manual test, at a cadence that keeps pace with how fast your environment actually changes.

Coverage cadence
Manual test
Sablewire

Discovery and exploitation runs, month over month.

Engagement chain
  1. Reconnaissance01
  2. Exploitation02
  3. Post-exploitation03
  4. Lateral movement04
  5. Persistence05

Every step mapped to MITRE ATT&CK, every action logged as evidence.

02 / Red Teaming

A realistic adversary, on the record

Full-spectrum engagements that go beyond initial access to test how far a real intrusion would travel.

Problem

Knowing a door is unlocked is not the same as knowing what happens once someone walks through it. Most tests stop before the chain does.

Approach

We run the full campaign, recon through exploitation, post-exploitation, lateral movement, and persistence, aligned to MITRE ATT&CK, with every step captured in an auditable chain of evidence.

Outcome

A realistic simulation of what a determined adversary would achieve, backed by a defensible record your team and your auditors can both stand behind. Lateral movement targets only hosts the engagement has actually discovered, not everything nominally in scope. That mirrors how a real intruder works: from what it has found, not from what it was told exists.

03 / Advisory

Adopt agentic AI without giving up the wheel

Guidance for security teams bringing agentic AI into defense and security auditing, safely and on their own terms.

Problem

Agentic tools move fast, and that speed is exactly what makes teams hesitate to put them near production systems or sensitive audits.

Approach

We help you design the governance around the agent: human-in-the-loop approval gates, clear separation between what an agent can propose and what it can execute, and audit trails for every decision. The model proposes; the graph disposes.

Outcome

The confidence to deploy agentic security tooling in your environment, with controls that keep a human in charge of every consequential action.

Control gate
Agent proposes -> Human approves -> Action executes

No high-impact action runs without an approval gate in the path.

Ready to see what an adversary would find?

Start a conversation about an engagement or a briefing on agentic security.

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