Security teams can now simulate what happens after an attacker bypasses their endpoint defenses, thanks to a $7 million pre-seed funding round behind a new offensive cyber operations platform. RemoteThreat, founded in 2025, gives in-house red teams a platform to run adversary simulations, build fresh tooling for each engagement, and stress-test the controls that activate once an intruder is already inside the network.
Why post-breach testing matters now
The premise behind the platform is simple: traditional penetration testing asks whether an attacker can get in, while RemoteThreat focuses on what happens next. The founders argue that endpoint detection and response (EDR) products can no longer be treated as the only line of defense, and that organizations need to prove their compensating controls actually work once a skilled actor slips past those products.
Ransomware operators and other criminal groups have grown skilled at bypassing Tier 1 EDR, and frontier AI models are accelerating that capability. The platform is built around the idea that defenders should assume a breach and rehearse the response, rather than treat perimeter and endpoint products as infallible.
How the platform works
RemoteThreat is an integrated offensive cyber operations platform that uses AI to assist human red teams, not replace them. Internal teams can run it with their own AI models, operate it as a fully human red-team engagement, or use a hybrid of both.
The platform helps enterprise and government teams test mission-critical objectives against threats that evolve quickly. The tooling is rebuilt from scratch each engagement rather than relying on static payloads that security tools can signature and block, so simulations match the adaptable tradecraft of real nation-state actors.
What the platform lets teams do
- Build and run their own offensive tooling instead of outsourcing long assessments to external providers.
- Simulate adversaries that have already bypassed EDR and are moving toward critical assets.
- Test whether compensating controls will actually slow or stop an intruder already inside the network.
- Design defenses that force attackers to generate enough activity for detection tools to spot them.
- Bring their own AI models or run the platform without AI at all.
The shift away from three-week engagements
The traditional model of a few senior testers managing 20 junior analysts across one- to three-week engagements is breaking down under economic pressure. Large banks have historically paid around $400,000 for three-month penetration testing programs, but organizations are no longer willing to fund long engagements at that price.
Pen testing is heading toward a commodity market run at scale, and the same pressure is expected to reach high-end red-team work soon. The platform is built for in-house teams to run themselves, so they can test more often than the one- to three-week outsourced engagements that large banks have historically paid around $400,000 for over three months.
Preparing for frontier-model attackers
The platform targets a scenario in which small criminal groups rent frontier AI models to automate stages of attacks that today require manual effort.
The toolset bypasses endpoint and security controls so defenders can see what their networks actually look like to a motivated intruder rather than to last year’s scanner. It exposes which compensating controls fire, which ones fail silently, and where an attacker can move unnoticed.
FAQ
What is RemoteThreat?
RemoteThreat is an offensive cyber operations platform founded in 2025 that helps enterprise and government security teams run adversary simulations, build fresh offensive tooling, and test what happens after an attacker bypasses their defenses.
How much funding has RemoteThreat raised?
The company emerged from stealth with $7 million in pre-seed funding.
Does RemoteThreat replace human red-team operators?
No. The platform uses AI to assist human teams, and organizations can run it as a fully human red-team engagement, a hybrid with some AI assistance, or with their own AI models. It can also be used without AI.
This article summarizes reporting from darkreading.com.