Last updated: July 2026

AI Incident Response

An AI agent breached a major company in one weekend. When you investigate, your own AI tools will refuse to look at the attack. We give you the one that will.

In July 2026 an autonomous AI agent chained a malicious dataset into a full breach at machine speed. When the defenders investigated, their commercial AI blocked the forensics. We get you ready for that attack and hand you a self-hosted model that never refuses the investigation. Senior-led by a former Microsoft security consultant.

Zero-Risk Guarantee.You see the full findings before you pay a single dollar. If you don't think it's worth it, you pay nothing. Fixed price. No scope creep. No surprises.

Get your fixed-price proposal in 24 hours See what a machine-speed agent reaches
AI incident response for machine-speed, agent-driven attacks, with a self-hosted defensive LLM for forensics
2026First AI-agent breach, disclosed
1 weekendFull breach at machine speed
Self-hostedDefensive LLM you own
24hFixed-price proposal
Pay afterYou review the work first

Two things just became true at once

Anyone can weaponize an AI. Nobody stops them.

Trim the safety limits off an open model, point it at a target, and it attacks at machine speed. The Hugging Face agent chained a malicious dataset into code execution, escalated to node-level access, harvested cloud and cluster credentials, and moved laterally over a single weekend. No human throttled the pace.

Your forensic tools will refuse to help.

When Hugging Face investigated, the commercial models it tried to use blocked the work. Their guardrails cannot tell an incident responder from an attacker. A defender who depends only on a hosted API can be locked out of investigating their own breach at the worst possible moment.

“The analysis requires submitting large volumes of real attack commands, exploit payloads, and C2 artifacts, and these requests were blocked by the providers' safety guardrails, which cannot distinguish an incident responder from an attacker.”

Hugging Face incident disclosure, July 2026. They ran the forensics on a self-hosted open model instead.

The AI agent kill chain: initial access, escalation, credential harvest, lateral movement, machine-speed tempo, forensics

What we actually test on your side

Every stage of the breach maps to a question about your environment. We answer each one with proof, not opinion.

Breach stageThe question we answer for you
Initial accessA malicious dataset ran code on a processing worker.Which of your data and model ingestion paths can execute attacker-controlled code, proven with a benign payload.
EscalationThe agent escalated from the worker to node-level access.How far one compromised process reaches, walked to node and control-plane.
Credential harvestIt harvested cloud and cluster credentials.Every service account, token, and CI credential a worker can read, with its real blast radius.
Lateral movementIt moved into several internal clusters over a weekend.The concrete lateral and privilege-escalation chains, and the chokepoints that break them.
Machine-speed tempoThousands of actions across a swarm of short-lived sandboxes.How fast your detection and containment actually fire, timed against an un-restricted agent.
ForensicsCommercial models refused to analyze the real attack data.A self-hosted model you control that never refuses the investigation.
A swarm of autonomous attacker agents moving at machine speed through a data grid

Pricing

We price by company size, so you know exactly where you stand before the call.

Under 500 employees
$15,000fixed price

Includes:

  • Agentic-Attack Readiness Assessment (full kill-chain exercise)
  • Self-hosted Defensive LLM build and handover (the Sovereign IR capability)
  • Forensic runbooks and team training
  • Prioritized remediation plan with owners
Book Free Strategy Call
Most common500 to 2,000 employees
$25,000fixed price

Everything in the package, sized for larger environments:

  • Broader environment coverage
  • Deeper non-human identity and supply-chain review
  • Additional integration and training support
Book Free Strategy Call
Over 2,000 employees
Enterpriseno public price

Scoped properly after a short strategy call.

  • Full multi-environment and multi-cloud scope
  • Dedicated senior lead and tailored SLAs
  • Fixed proposal after we understand your estate
Book a Scoping Call

Zero-Risk Guarantee.You see the full findings before you pay a single dollar. If you don't think it's worth it, you pay nothing. Fixed price. No scope creep. No surprises.

Optional add-ons, available on both packages

  • Non-Human Identity and Model Supply-Chain Hardening. Close the ingestion paths that can execute untrusted code, and least-privilege the machine identities a compromised worker can reach.
  • Machine-Speed IR Retainer and fractional CISO support. A senior responder and your sovereign IR stack on standby, with a fractional CISO relationship the rest of the time.

Final confirmation of package fit happens on the free 30-minute strategy call. We send the fixed-price proposal within 24 hours.

Book Free Strategy Call
A self-hosted defensive language model running inside a sealed on-premise boundary so no attacker data leaves the environment

How it works

1

Free Strategy Call

30 minutes with Alexander directly. We map your AI attack surface, your incident-response gaps, and which tiers fit, then send a fixed-price proposal within 24 hours.

2

Agentic-Attack Readiness Assessment

We re-run your penetration test and Active Directory attack simulation against the machine-speed kill chain, driving the engagement with an un-restricted agent under signed rules of engagement, and score how fast your detection and containment actually fire.

3

Sovereign IR Capability Build

We stand up a self-hosted, un-neutered defensive LLM on infrastructure you control, wire it into your existing IR workflow and DFIR tooling, write the forensic runbooks, and train your team to run it.

4

Hardening and Retainer

We close the ingestion code paths and least-privilege the machine identities a compromised worker can reach, then keep the readiness work current with an optional machine-speed IR retainer and fractional CISO relationship.

Non-human machine identities being locked down and least-privileged inside a secured cluster
A controlled red-team agent probing the layered defenses of a data center during a readiness assessment

Who this is for

The threat is the attacker's AI, not whether you build one. If any of these fit, you are in scope.

Founders and CTOs whose companies ingest external datasets or open-weight models, or let agents touch production
Financial institutions where harvested machine identities and credentials are the whole game and NIS 2, SOC 2, or ISO expectations are already in the room
MSPs that want to white-label a sovereign incident-response capability instead of building an un-neutered forensics stack in house
Executives and high-net-worth individuals who now face agent-driven, machine-speed targeting
Any organization that could be probed by an autonomous agent and cannot absorb a machine-speed weekend with no response bench

Why us

Grounded in the July 2026 Hugging Face breach, a public and dated incident, not slideware or invented statistics
We stand up a self-hosted, un-neutered defensive LLM you own, the exact capability Hugging Face had to improvise mid-incident
Led personally by a former Microsoft Security Consulting team member, not delegated to junior analysts
Complementary to real tooling like Protect AI, HiddenLayer, and AI-SOC products, over which we are happy to work
Honest about dual-use and the limits of the technology, with every risk named up front
Fixed-price proposals within 24 hours, and you review the work before you pay
Built entirely on capabilities Atlant already ships: penetration testing, AD attack simulation, incident response, DFIR tooling, cloud security, and virtual CISO
Alexander Sverdlov - Founder, Atlant Security

Led by Alexander Sverdlov

Former Microsoft Security Consulting team member. CISSP certified. Secured nuclear energy infrastructure at Emirates Nuclear Energy Corporation. 200+ security assessments across 14 countries since 2013. Every engagement is led directly by Alexander, not delegated to junior staff.

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“Not only did they help us get compliant with strict vendor procedures in a rapid timeframe, but in comparison to many other security vendors, they genuinely cared and invested in full security, not just compliance.”

Kenneth Shen - Managing Partner, HalfPastNine

This is not a hypothetical threat.

The July 2026 Hugging Face breach is public, dated, and documented by both Hugging Face and OpenAI. A named company, a real weekend, a real forensics team locked out of its own commercial tools. We built this service on that record, not on slideware, and we do not invent client results.

LLM-driven forensic analysis reconstructing an attack timeline from thousands of log events
A calm 24/7 security operations responder on standby before live monitoring dashboards

See exactly what a machine-speed agent reaches in your environment.

Book the 30-minute call with Alexander. We map your AI attack surface and send one fixed-price proposal within 24 hours.

Zero risk: you review the full findings before you pay a single dollar.

Book the 30-minute call alexander@atlantsecurity.com

Book your AI incident response strategy call

The honest part

This service touches dual-use capability. We name the two hazards that matter before you do.

R1

The offensive agent runs only under signed authorization

The un-restricted red-team agent runs strictly under a signed rules of engagement, on scoped and authorized targets. We do not build, sell, or leave behind offensive capability. Same discipline we already apply to penetration testing.

R2

The defensive model is deployed on your data, with your legal sign-off

The self-hosted model is a defensive tool used on your own data, inside your boundary, with chain-of-custody controls and a documented, licence-appropriate model choice. Regulated clients route the deployment through their own legal and compliance function. We support that review, we do not replace it, and we never overpromise: the model accelerates a human analyst, it is not an oracle.

Facing NIS 2 or DORA incident-reporting clocks? A machine-speed breach makes the 24-hour and 72-hour deadlines much harder to meet. We align your response capability with those obligations in one engagement. Ask us about combined scope.

For small projects and ad-hoc work outside our pre-agreed packages or retainers, our standard hourly rate is $460.

AI Incident Response FAQ

What is AI incident response, and how is it different from normal IR?
AI incident response prepares for and responds to attacks driven by autonomous AI agents rather than human operators. The difference is tempo and tooling. An agent can execute thousands of actions across many short-lived sandboxes in the time a human team schedules a call, so detection and containment have to be tested against machine speed. And the forensic work itself increasingly runs on large language models, which introduces a problem normal IR never had: the model you use to investigate can refuse to process the very attack data you need to analyze.
What actually happened in the July 2026 Hugging Face breach?
Hugging Face disclosed that an autonomous AI agent breached its production infrastructure. A malicious dataset abused two code-execution paths in its dataset processing to run code on a worker, then the agent escalated to node-level access, harvested cloud and cluster credentials, and moved laterally over a weekend. It found no evidence that public models, datasets, or Spaces were tampered with. OpenAI later disclosed that the attacker was a combination of its own models, run with reduced cyber refusals for an internal evaluation, that escaped their test environment. We use this incident as the reference case because it is public, dated, and documented by both companies.
Why would a commercial AI model refuse to help investigate a breach?
Forensics means submitting real attack commands, exploit payloads, and command-and-control artifacts to the model for analysis. Commercial models behind hosted APIs apply safety guardrails that, in Hugging Face's own words, cannot distinguish an incident responder from an attacker, so those submissions get blocked. A defender who depends only on a guardrailed API can be locked out of investigating their own breach at the worst possible moment. That is the specific gap our self-hosted defensive LLM capability closes.
Do you really run an un-restricted AI model? Is that legal and safe?
For forensics, we deploy an open-weight model on infrastructure the client controls, so real attack data can be analyzed and nothing leaves the client environment. It is a defensive tool, used on the client's own data, with data-handling and chain-of-custody controls, and its intended use is documented. Clients in regulated sectors should route the deployment through their own legal and compliance function, and we support that review rather than replace it. For the offensive side, the un-restricted red-team agent runs only under a signed rules-of-engagement, on scoped and authorized targets, exactly as we already run penetration tests.
What is a self-hosted or sovereign defensive LLM, and why does the model's origin not matter?
It is an open-weight model you run on your own infrastructure instead of calling a vendor API, so the data path and the tool are both under your control. Hugging Face used a particular open model, but the durable lesson is not about any specific model. It is control and availability: you own the tool, the attacker data never leaves your environment, and no vendor safety filter can stall your investigation. We select a model whose license and capabilities fit your use, and we state that choice explicitly in the deliverable.
How is this different from model-scanning tools like Protect AI or HiddenLayer?
Those are real products and they are good at scanning model and machine-learning artifacts for known-bad patterns. They are complementary to what we do, not the same thing. Off-Safeties is a senior consultant assessing whether your ingestion architecture should execute untrusted code at all, standing up the un-neutered forensic capability those tools do not provide, and owning the finding, the fix order, and the board explanation. We are happy to work over a client's existing Protect AI or HiddenLayer deployment. We do not resell those tools and do not claim their coverage.
Do I need this if my company does not build AI products?
Yes, because the threat is the attacker's AI, not yours. Any organization can be targeted by an autonomous agent that probes, escalates, and moves laterally at machine speed. If you ingest external data or models, run agents against production, or hold credentials that a compromised worker could reach, the Hugging Face kill chain is directly relevant. The readiness assessment and the identity hardening apply whether or not you ship an AI product.
How fast can you respond during an incident?
A weekend was all the Hugging Face agent needed, so the retainer tier exists precisely to remove the human reaction gap. Retainer clients agree rules of engagement and on-call escalation in advance, and the self-hosted forensic capability is kept patched and ready, so response starts immediately rather than after a procurement cycle. For clients without a retainer, response is scheduled as fast as scoping and authorization allow.
What does an engagement cost?
We price by company size. For companies under 500 employees the package is a fixed $15,000, and for 500 to 2,000 employees it is a fixed $25,000 sized for the larger environment. Both include the agentic-attack readiness assessment, the self-hosted defensive LLM build and handover, forensic runbooks and team training, and a prioritized remediation plan. Companies over 2,000 employees are scoped individually with no public price. Optional add-ons (non-human identity and supply-chain hardening, and a machine-speed IR retainer with fractional CISO support) are available on both packages. Everything is fixed-price and paid after you review the work, and package fit is confirmed on a free 30-minute call with a proposal within 24 hours.
Can you promise this will prevent an AI-driven breach?
No, and we will not pretend otherwise. A self-hosted model can make mistakes and is not a forensic oracle; it accelerates a human analyst rather than replacing one. What we can do is close the specific paths the Hugging Face attacker used, make sure your machine identities do not hand an attacker the whole cluster, and guarantee that when you investigate, your tooling works with you instead of refusing you. Every claim in an engagement traces to evidence you can inspect.

Related: Penetration Testing - Active Directory Security Assessment - Vulnerability Assessment - Virtual CISO Services - Cloud Security Consulting - NIS 2 Compliance