Agents that do real security work, inside limits you can explain.
Seven agents that find, fix and document, each with a demonstration of under a minute on a fictional company. And the same discipline for the agents you put to work yourselves: least privilege, approvals and a log of every call.
Try an agent
- PCI Scope AgentCard-data discovery$864K at risk, found, fixed with the owner’s yes and proved by rescan▶ Try it
- SLO Velocity AgentFindings intake and routing$2M revenue at risk in 8 findings past due or close to it▶ Try it
- CUI Shield AgentCUI tracing and boundary$4.2M contract value at risk, and a 12-system boundary▶ Try it
- ISO Evidence AgentControls matched to evidence$830K pipeline waiting on the certificate, 6 gaps named▶ Try it
- Agent GuardAI agents, permissions, injection$540K blast radius of one CI agent with a deploy token▶ Try it
- Program PulseForecasts from the work itself10 days launch slip found while every team reported green▶ Try it
- Architecture Review AgentWeak points priced in downtime$706K a year of expected downtime, priced and ranked▶ Try it
Every agent
- Runs in your environment
- Read-only access; sensitive data is masked before any model sees it.
- Prices what it finds
- Every figure opens its chain: what it allows, who is affected, how the number is reached.
- People decide
- Every verdict, fix and boundary is a proposal until someone accepts it.
- Measured, not claimed
- Planted answers on every run, and an accuracy record you keep.
Your own agents
- Our engineers use coding agents, and no one has set the rules.
- An agent can read our tickets, our code and our customer data. Can it be talked into misusing them?
- The board asks for our AI strategy, and our answer is a list of pilots.
Agents multiply whatever they are given: speed, access and mistakes alike. Without limits, one injected instruction can move data, merge code or spend money with your credentials, at machine speed.
Putting them to work
- Find
Where agents pay off
The work in engineering, security and operations that agents can take on now, ranked by value and by risk.
- Bound
Least privilege for agents
Narrow tools, scoped data, short-lived credentials, human approval for anything irreversible, and a log of every call. Agent Guard tests it.
- Ship
Into real workflows
Coding agents in your delivery pipeline with review and tests as gates, and agents in triage, reporting and operations.
- Govern
Measured and accountable
Agent risks in the register, red-teamed for prompt injection, and governed against NIST AI RMF and ISO/IEC 42001.
What you keep
- Agent map
- Where agents work, what they can reach, and who owns each.
- Permission model
- Tools, data and approvals per agent.
- Engineering playbook
- How your teams work with coding agents, from prompt to merge.
- Threat model
- Prompt injection, data exfiltration and tool misuse, with tests.
- Governance
- Policy, risk register and metrics leadership can read.
Questions
Which agents and models do you work with?
The ones you already use or choose. Our work is the operating model, permissions and controls around them, which outlast any single vendor.
Will agents replace our engineers?
They change what engineers spend their day on. People still decide what to build, review what ships, and answer for it.
How do you test an agent’s security?
We attack it the way an adversary would: injected instructions in documents, tickets and web pages, and attempts to stretch its tools beyond their purpose.
What about regulated data?
Agents inherit the scope of the data they touch. We keep CUI, card data and health data inside approved boundaries, or away from agents entirely.