Offensive security at a different level
TexaTenet takes offensive security beyond brute force. A patent-pending, reasoning-based method drives AI agents that attack your applications, cloud and networks continuously, inside a scope you approve. World-class offensive engineers verify every serious finding, and attacker-intent intelligence shows you which targets adversaries actually value.
Authorized testing only, within a scope you approve in writing.
Choose a target and watch the agent reason its way in.
One continuous loop, from reconnaissance to verified fix
Every engagement runs the same five stages. The first three show you what an adversary can see and reach. The last two close it and keep it closed.
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Map everything you expose
We build a complete picture of your external and internal attack surface: domains, cloud accounts, APIs, code repositories and the servers no one remembers. Every weakness is then ranked by whether an adversary can actually reach and use it, so your team fixes the few that matter instead of triaging thousands that don’t.
Asset Type Owner Exposure api.acme.io API Platform Public staging-api.acme.io API Unknown Public jenkins-legacy.acme.io CI server Unknown Public vpn.acme.io VPN IT Public acme-exports Storage bucket Unknown Public read db-replica-3 Database Platform Internal 842 assets found. The 17 that weren’t in your inventory are highlighted; three are shown here.1,436 raw scanner findings96 are reachable by an attacker12 are exploitable, proven by an agentDrawn to scale. Ranked by what an adversary can do with it, not by scanner severity. -
Attack it the way a skilled adversary would
Autonomous agents reason about how your environment fits together and choose their next move the way an experienced operator does, chaining small weaknesses into complete paths to your data rather than firing every payload at every endpoint. They stay inside your approved scope, keep load low, and stop at proof: they demonstrate access without exfiltrating anything.
One path an agent proved
- ReachThe image proxy fetches any address it’s given, including the cloud metadata service at
169.254.169.254. - ObtainThe response contains temporary credentials for the role
billing-worker. - PivotThose credentials can list the bucket
acme-billing-exports. - Prove14,203 customer invoices are readable. The agent stops there and exfiltrates nothing.
What the agents attack
- Web applications and APIs
- Cloud accounts and Kubernetes
- Internal networks and Active Directory
- Mobile apps
- CI/CD pipelines
- LLM apps and AI agents
- ReachThe image proxy fetches any address it’s given, including the cloud metadata service at
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Verify what’s real
An offensive-security engineer reproduces every critical and high finding before it reaches you. Each arrives with the request that proves it, the business impact in plain language, and the steps to reproduce it yourself. No false positives, no unverified severity.
CriticalVerified by an engineerCustomers can read each other’s invoices
Broken object-level authorization on
/api/v2/invoices/{id}Evidence
Signed in as a user of tenant B, the agent asked for an invoice that belongs to tenant A. The server returned it.
Request GET /api/v2/invoices/48213 HTTP/1.1 Authorization: Bearer <token for a tenant B user> Response HTTP/1.1 200 OK { "invoice_id": 48213, "tenant": "tenant-A", "total": 12400.00, "bill_to": "[redacted]" }
Business impact
- Any signed-in user can read invoices that belong to other customers.
- Invoice numbers are sequential, so all of them can be collected with a simple loop.
- Invoices hold billing contacts and amounts. That is personal and financial data, which privacy rules such as GDPR cover.
- The same weakness is the last step of the attack path shown above.
Reproduce
- Sign in as any user of tenant B.
- Send
GET /api/v2/invoices/48213with that user’s token. - Check that the response contains an invoice owned by tenant A. It should have been refused.
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Remediate, don’t just report
Fixes arrive in the form your team already works in: pull requests, infrastructure-as-code changes, and WAF rules that hold the line until the patch ships. For structural gaps, our engineers carry out the hardening alongside your team.
Pull request #1287Scope invoice lookups to the caller’s tenantapi/invoices.py- invoice = db.invoices.get(invoice_id)+ invoice = db.invoices.get(invoice_id, tenant_id=ctx.tenant_id)+ if invoice is None:+ raise NotFound()
- Regression test added
- WAF rule live while the fix ships
- Re-test passed. The attack path is closed.
Hardening our engineers implement with your team
Before After Long-lived cloud keys stored in CI Short-lived tokens issued for each build One shared admin login Individual SSO accounts with step-up MFA Secrets committed to repositories Secrets in a vault, rotated automatically Storage buckets open to the public Private buckets with expiring signed links -
Stay verified
Your attack surface changes with every deployment. TexaTenet re-tests what changed, confirms that each fix closed its path, and keeps your audit evidence current between assessments.
Activity this week
- Deploy v4.18.2 detected. Re-testing the 31 endpoints that changed.
- New public storage bucket found. Its owner was notified.
- Fix for the invoice issue merged. Re-test passed and the path is closed.
Evidence maps to the controls auditors ask about
Framework Control What you can show SOC 2 CC7.1 Ongoing detection of new vulnerabilities ISO 27001 A.8.8 Management of technical vulnerabilities PCI DSS 4.0 11.4 Internal and external penetration testing NIST CSF 2.0 ID.RA Vulnerabilities identified, validated and recorded
What sets TexaTenet apart
Most testing addresses the problem with brute force: more scans, more payloads, more noise. TexaTenet’s approach is built on knowledge and reasoning about your environment, the way a skilled adversary actually works.
Reasoning, not brute force
Our patent-pending approach solves a problem that most of the industry still attacks with volume. Instead of running every check against every asset, our agents reason about how your systems fit together and where the leverage is. The result is fewer, higher-confidence findings, far less noise for your team, and far less load on production.
Full offense, end to end
We go fully on the offensive. Reconnaissance, initial access, privilege escalation, lateral movement and proof of impact are run the way a real intrusion unfolds, chaining the small weaknesses that checklists and scanners never connect.
Attacker-intent intelligence
Knowing how an adversary could get in is half the picture. We also identify what current and prospective attackers are trying to achieve: bulk data, a specific data set, access to a particular system, or your customers’ information. Your remediation roadmap is prioritized by real intent, not by a generic severity score.
World-class offensive talent
Every engagement is led by operators with deep, hands-on hacking expertise, among the strongest in the field. They direct the agents, reproduce every critical finding themselves, and work shoulder to shoulder with your engineers on the fix.
Attacker-intent assessment
| Observed activity | Probable objective | Priority |
|---|---|---|
| Systematic enumeration of /api/v2/invoices/{id} | Financial records for a specific customer segment | Critical |
| Sustained credential stuffing against customer sign-in | Account takeover and customer personal data | High |
| Probing of CI runners and artifact storage | Access to signing keys and the release pipeline | High |
| Broad scanning of public IP ranges | Opportunistic; no specific target identified | Monitor |
Delivered with every engagement
- Attack-path findings with proof of exploitation
- Attacker-intent assessment, prioritized by objective
- Remediation as pull requests, WAF rules and hardening
- Re-test confirmation that every path is closed
Autonomous doesn’t mean unsupervised
Letting AI attack your systems only works if the limits are absolute. These are ours.
Scope is enforced, not suggested
Agents can reach only the assets on the allow-list you approve in writing. Everything else is blocked at the platform level.
Non-destructive by default
Payloads that could affect data integrity or availability stay disabled unless you enable them, and rate limits keep production load low.
High-impact steps wait for approval
Any action that could affect production pauses until a named member of your team approves it.
One switch halts everything
Every engagement has a kill switch. Activate it and every agent stops immediately.
Experts own the outcome
An offensive-security engineer reproduces every critical and high finding before it reaches you, and stays accountable for the result.
Your data stays yours
Each customer’s findings are isolated, encrypted, and never used to train models available to anyone else.
Compared with the alternatives
An annual test is a snapshot. Brute-force automation is noise. Neither tells you what an adversary actually wants.
| Topic | Annual pentest | Brute-force automation | TexaTenet |
|---|---|---|---|
| Method | Manual, checklist-driven | Exhaustive scanning and fuzzing | Knowledge-based reasoning, patent pending |
| Cadence | Once or twice a year | Continuous, but shallow | Continuous, and after every significant change |
| Time to first result | Weeks after kickoff | Immediate, unprioritized | Hours after you approve the scope |
| Signal quality | A PDF of findings, many unverified | Thousands of alerts, most unreachable | Proven attack paths, verified by an engineer |
| Attacker intent | Not addressed | Not addressed | Identified and used to prioritize remediation |
| Remediation | Left to your team | Left to your team | Pull requests, WAF rules and hands-on hardening |
| Confirmation | At next year’s test | A re-scan, with the same noise | A re-test of every fix, path confirmed closed |
Questions, answered
Can’t find yours? Ask us during the demo.
What is patent-pending about your approach?
Most of the industry addresses offensive testing by brute force: run every check against every asset and sort through the noise afterwards. TexaTenet’s method is built on knowledge and reasoning about the target environment, deciding what to attack and how, the way a skilled operator does. That method is the subject of a pending patent application. We are glad to go deeper under NDA.
What is attacker-intent intelligence?
A penetration test tells you how an attacker could get in. Intent intelligence tells you what they are trying to achieve: whether they are after data in bulk, a specific data set, access to a particular system, or your customers’ information. We deliver it as a prioritized assessment alongside your findings, so remediation starts with the targets adversaries actually value.
Is it safe to run against production?
It is built for that, within limits you control. Agents touch only assets on your approved allow-list, use non-destructive payloads by default, and run rate-limited. Any action that could affect production pauses for your approval, and a kill switch stops every agent immediately.
How is this different from a vulnerability scanner?
A scanner lists weaknesses that might exist and leaves the triage to you. Our agents reason about which weaknesses matter, exploit them, and chain them together, so you see what an adversary could actually do. Findings are ranked by demonstrated impact and arrive with proof.
Who does the work?
Agents run the attacks; people own the outcome. Our operators are experienced offensive-security practitioners with deep hands-on hacking expertise. They direct the agents, reproduce and review every critical and high finding before you see it, and join your engineers to walk through the fixes.
What can you test?
Web applications and APIs, cloud environments (AWS, Azure and Google Cloud), Kubernetes, internal networks and Active Directory, mobile applications, CI/CD pipelines, and applications built on large language models and AI agents.
Does this help with compliance?
Findings, fixes and re-tests are mapped to controls in SOC 2, ISO 27001, PCI DSS and NIST CSF, so the evidence is ready when auditors ask. Your assessor remains the authority on what satisfies a requirement.
What happens to our data?
Each customer’s data is isolated, encrypted in transit and at rest, and never used to train models available to anyone else. You can request deletion at any time.
See what an adversary would find, and what they’d want
In 30 minutes we’ll walk through a live run, show you a sample intent assessment, and scope a pilot for your environment.