// Offensive security for AI systems

antagon@redteamshell:~$

We attack your AI before something else does.

Adversarial testing for LLM apps, agents, and the AI supply chain. Every finding is proven with a working exploit and signed off by a certified operator — not a scanner's guess. Mapped to the OWASP LLM Top 10 and MITRE ATLAS.

Request an engagement See how it works ↓

Confirmed · exploited // what a finding looks like

Finding: Indirect prompt injection reaches a shell tool support-agent · tool:shell
Exploit: Reproduced in an isolated replica — 3-turn chain, guardrail bypassed reproducible PoC attached
Sign-off: Exploited and verified by hand certified operator
Mapping: OWASP LLM01 · LLM07 · MITRE ATLAS

// How it works

Scanners tell you what might be wrong. We prove what is.

Three stages, and nothing reaches your report until it has survived all of them.

Attack

Multi-agent adversarial testing across the model, the agent, its tooling, and the supply chain behind it — multi-turn chains, not one-shot payloads.

Prove

Every candidate is reproduced with a working exploit in an isolated replica. A red agent argues the path, a blue agent challenges it. What cannot be exploited is not a finding.

Sign off

A certified operator exploits every critical by hand, documents the proof, and writes the remediation. Your report carries a human signature, not a confidence score.

// Three fronts, one adversary

Built to cover everything your AI touches.

Each front has its own attack surface, its own failure modes, and its own proof.

[01]

Agent & LLM Red Teaming

Break the model. Break the agent. Prove it.

The surfaces scanners can't reason about — attacked in multi-turn chains, not one-shot payloads. Every bypass documented with a reproducible proof-of-concept.

Direct + indirect prompt injection
Jailbreak & guardrail bypass (multi-turn)
System-prompt / context extraction
Tool, function-call & MCP abuse
Agent hijacking, memory & RAG poisoning
Data exfiltration via agent actions

[02]

Agentic Code-Review & PR Gate

Every commit reviewed. Every AI-written line questioned.

Semantic, data-flow-aware review that runs in the pull request — not a pattern matcher that buries you in false positives. Confirmed issues come back as a fix PR.

Data-flow analysis across files & frameworks
Access control, IDOR/BOLA & business logic
Insecure AI-generated pattern detection
Fix delivered as a reviewable PR
CI/CD merge gate, low-noise by design

[03]

AI Supply-Chain & Model-Trust

Your model stack is attack surface. We audit it.

The AI supply chain fails quietly — untrusted loads, poisoned dependencies, over-trusted plugins. We audit it before any of it reaches production.

Model provenance & integrity checks
trust_remote_code & untrusted loads
Unsafe deserialization / pickle fallbacks
Dependency & model-poisoning review
MCP server, plugin & tool vetting

// The pipeline

Not one model with a security prompt.

A hierarchy of agents, each with one job, arguing with each other — and a human at the end who owns the verdict.

Planner

Reads the scope and decides which surfaces matter: model, agent, tooling, supply chain, external perimeter.

Red agents

Build and execute attack paths. Stateful, multi-turn, chained — they carry context between attempts instead of replaying payloads.

Blue agents

Challenge every claim the red side makes. Multi-round debate kills the findings that do not hold up, before you ever see them.

Certified operator

A human exploits whatever survived, signs it off, and writes the fix. This is the step a scanner cannot sell you.

// Also from RedTeamShell

External attack surface assessment

Our original engagement — the classic external pentest, run through the same multi-agent pipeline. From domain to deliverable, faster than a traditional assessment and at a fraction of the cost.

[01] RECON

Full attack surface mapping

Passive OSINT across Shodan, SecurityTrails, WHOIS, DNS, cert transparency, and more — assembled into a unified target profile.

[02] INTEL

Threat intel & CVE mapping

Discovered services matched against live vulnerability databases. Exploitability scoring with MITRE ATT&CK technique mapping.

[03] DEBATE

Red vs Blue adversarial AI

A red team agent argues attack paths. A blue team agent challenges each finding. Multi-round debate produces accurate, peer-reviewed risk ratings.

[04] SCAN

Active vulnerability verification

Active scanning via an AI-powered engine — verifies findings against live targets within your authorised scope.

[05] HUMAN

Certified pentester review

Managed tier: a certified operator manually exploits confirmed findings and documents proof-of-concept evidence.

[06] REPORT

Executive + technical PDF

Branded PDF report covering executive summary, technical findings, CVSS scores, remediation roadmap, and engagement notes.

// operator-led, not scanner-led — both offerings run on the same multi-agent pipeline, and every critical finding is exploited and signed off by a certified operator. Proof, not probability.

Professional

Full analysis

One AI system or one domain. Full pipeline, OWASP LLM Top 10 + ATLAS or CVE coverage, PoC evidence, remediation roadmap, PDF report.

Managed

Human-verified

AI pipeline plus a certified operator who manually exploits and demonstrates every critical finding. For anything customer-facing.

Enterprise

White-label

API access, custom branding, CI/CD-gated PR review, dedicated SLA, team seats, and integration support.

We go first.

If you ship an AI system that touches real data or real tools, it is already attack surface. The only open question is who maps it first.

Request an engagement Read the research ↗

Onboarding design partners — validating findings on live AI systems before public launch.